Virtual water trade, AY Hoekstra, PQ Hung

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Content: A.Y. Hoekstra P.Q. Hung September 2002
Virtual water trade A quantification of virtual water flows between nations in relation to international crop trade
Value of Water Research Report Series No.11
VIRTUAL WATER TRADE A QUANTIFICATION OF VIRTUAL WATER FLOWS BETWEEN NATIONS IN RELATION TO INTERNATIONAL CROP TRADE A.Y. HOEKSTRA P.Q. HUNG SEPTEMBER 2002 VALUE OF WATER RESEARCH REPORT SERIES NO. 11
IHE DELFT P.O. BOX 3015 2601 DA DELFT THE NETHERLANDS
Contact author: A.Y. Hoekstra Tel. +31 15 2151828 E-mail [email protected]
Contents Summary ...................................................................................................................................................................................7 1. Introduction .........................................................................................................................................................................9 1.1. The economics of water use........................................................................................................................................9 1.2. Virtual water trade......................................................................................................................................................10 1.3. The objective of this study........................................................................................................................................11 2. Method................................................................................................................................................................................ 13 2.1. Calculation of specific water demand per crop type ............................................................................................13 2.2. Calculation of virtual water trade flows and the national virtual water trade balance....................................14 2.3. Calculation of a nation's `water footprint'.............................................................................................................15 2.4. Calculation of national water scarcity, water dependency and water self-sufficiency ...................................16 3. Data sources ...................................................................................................................................................................... 19 4. Specific water demand per crop type per country................................................................................................. 23 5. Global trade in virtual water....................................................................................................................................... 25 5.1. international trade in virtual water...........................................................................................................................25 5.1.1. Overview of international virtual water trade.............................................................................................. 25 5.1.2. Virtual water trade balance per country....................................................................................................... 28 5.1.3. International virtual water trade by product................................................................................................ 34 5.2. Inter-regional trade in virtual water.........................................................................................................................35 5.2.1. Inter-regional virtual water trade relations................................................................................................. 35 5.2.2. Virtual water trade balance per world region ............................................................................................. 40 5.2.3. Gross virtual water trade between countries within regions..................................................................... 50 5.3. Intercontinental trade in virtual water.....................................................................................................................51 5.3.1. Intercontinental virtual water trade relations.............................................................................................. 51 5.3.2. Virtual water trade balance per continent.................................................................................................... 53 5.3.3. Gross virtual water trade between countries within continents................................................................ 54 6. Virtual water trade of nations in relation to national water needs and availability..................................... 55 6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations ..........................55 6.2. The relation between water scarcity and water dependency ...............................................................................60 7. Concluding remarks....................................................................................................................................................... 63 References .............................................................................................................................................................................. 65 5
Appendices
I.
Crop water requirements (m3/ha)
II.
Actual crop yields (ton/ha) in 1999
III. Specific water demands (m3/ton) in 1999
IV.
FAO guidelines on crop water requirements in mm [=10 m3/ha]
Va. Gross virtual water import per country for the years 1995-1999 (106 m3)
Vb. Gross virtual water export per country for the years 1995-1999 (106 m3)
Vc. Net virtual water import per country for the years 1995-1999 (106 m3)
VI. Classification of countries into thirteen world regions VII. Gross virtual water trade between and within regions (Gm3)
6
Summary The water that is used in the production process of an agricultural or industrial product is called the 'virtual water' contained in the product. A water-scarce country might wish to import products that require a lot of water in their production (water-intensive products) and export products or services that require less water (waterextensive products). This implies net import of `virtual water' (as opposed to import of real water, which is generally too expensive) and will relieve the pressure on the nation's own water resources. Until date little is known on the actual volumes of virtual water trade flows between countries. The objective of this study is to quantify the volumes of all virtual water trade flows between nations in the period 1995-1999 and to put the virtual water trade balances of nations within the context of national water needs and water availability. The study has been limited to the quantification of virtual water trade flows related to international crop trade. The basic approach has been to multiply international crop trade flows (ton/yr) by their associated virtual water content (m3/ton). The required crop trade data have been taken from the United Nations Statistics Division in New York. The required data on virtual water content of crops originating from different countries have been estimated on the basis of various FAO databases (CropWat, ClimWat, FAOSTAT). The calculations show that the global volume of crop-related virtual water trade between nations was 695 Gm3/yr in average over the period 1995-1999. For comparison: the total water use by crops in the world has been estimated at 5400 Gm3/yr (Rockstrцm and Gordon, 2001). This means that 13% of the water used for crop production in the world is not used for domestic consumption but for export (in virtual form). This is the global percentage; the situation strongly varies between countries. Considering the period 1995-1999, the countries with largest net virtual water export are: United States, Canada, Thailand, Argentina, and India. The countries with largest net virtual water import in the same period are: Sri Lanka, Japan, the Netherlands, the Republic of Korea, and China. For each nation of the world a `water footprint' has been calculated (a term chosen on the analogy of the `ecological footprint'). The water footprint, equal to the sum of the domestic water use and net virtual water import, is proposed here as a measure of a nation's actual appropriation of the global water resources. It gives a more complete picture than if one looks at domestic water use only, as is being done until date. In addition to the water footprint, indicators are proposed for a nation's `water self-sufficiency' and a nation's `water dependency'. In studying global virtual water trade flows, it is recommended to start working on other products than crops as well, for instance livestock products such as meat. Another next step is to start interpreting the data and to study how governments can deliberately interfere in the current national virtual water trade balances in order to achieve higher global water use efficiency. 7
8
1. Introduction 1.1. The economics of water use Water should be considered an economic good. Ten years after the Dublin conference this sounds like a mantra for water policy makers. The sentence is repeated again and again, conference after conference. It is suggested that problems of water scarcity, water excess and deterioration of water quality would be solved if the resource `water' were properly treated as an economic good. The logic is clear: clean fresh water is a scarce good and thus should be treated economically. There is an urgent need to develop appropriate concepts and tools to do so. In dealing with the available water resources in an economically efficient way, there are three different levels at which decisions can be made and improvements be achieved. The first level is the user level, where price and technology play a key role. This is the level where the `local water use efficiency' can be increased by creating awareness, charging prices based on full marginal cost and by stimulating water-saving technology. Second, at a higher level, a choice has to be made on how to allocate the available water resources to the different sectors of economy (including public health and the environment). Water is used for the production of several `goods' and `services'. People allocate water to serve certain purposes, which generally implies that other, alternative purposes are not served. Choices on the allocation of water can be more or less `efficient', depending on the value of water in its alternative uses. At this level we speak of `water allocation efficiency'. Water is a public good, so water allocation at the country or catchment level is principally a governmental issue. The question is here how all demands for water can best be met and where ­ in case of water shortage ­ supply should be restricted. Beyond `local water use efficiency' and `water allocation efficiency' there is a level at which one could talk about `global water use efficiency'. It is a fact that some regions of the world are water-scarce and other regions are water-abundant. It is also a fact that in some regions there is a low demand for water and in other regions a high demand. Unfortunately there is no general positive relation between water demand and availability. Until recently people have focussed very much on considering how to meet demand based on the available water resources at national or river basin scale. The issue is then how to most efficiently allocate and use the available water. There is no reason to restrict the analysis to that. In a protected economy, a nation will have to achieve its development goals with its own resources. In an open economy, however, a nation can import products that are produced from resources that are scarcely available within the country and export products that are produced with resources that are abundantly available within the country. A water-scarce country can thus aim at importing products that require a lot of water in their production (water-intensive products) and exporting products or services that require less water (water-extensive products). This is called import of virtual water (as opposed to import of real water, which is generally too expensive) and will relieve the pressure on the nation's own water resources. For water-abundant countries an argumentation can be made for export of virtual water. Import of water-intensive products by some nations and export of these products by others includes what is called `virtual water trade' between nations. 9
Global water use efficiency Water allocation efficiency
virtual water trade between water-scarce and water-abundant regions value of water in its alternative uses
Local water use efficiency
technology, water price, environmental awareness of water user
In summary, the overall efficiency in the appropriation of the global water resources can be defined as the `sum' of local water use efficiencies, meso-scale water allocation efficiencies and global water use efficiency. So far most attention of scientists and politicians has gone to local water use efficiency. There is quite some knowledge available and improvements have actually been achieved already. More efficient allocation of water as a means to improved Water Management has got quite same attention as well, but if it comes to the implementation of improved allocation schemes there is still a long way to go. At the global level, it is even more severe, since basic data on virtual water trade and water dependency of nations are generally even lacking. This has been the incentive for this study. 1.2. Virtual water trade
For the production of nearly all goods water is required. The water that is used in the production process of an agricultural or industrial product is called the 'virtual water' contained in the product. For example, for producing a kilogram of grain, grown under rain-fed and favourable climatic conditions, we need about one to two cubic metres of water, that is 1000 to 2000 kg of water. For the same amount of grain, but growing in an arid country, where the climatic conditions are not favourable (high temperature, high evapotranspiration) we need up to 3000 to 5000 kg of water.
If one country exports a water-intensive product to another country, it exports water in virtual form. In this way some countries support other countries in their water needs. For water-scarce countries it could be attractive to achieve water security by importing water-intensive products instead of producing all water-demanding products domestically. Reversibly, water-rich countries could profit from their abundance of water resources by producing water-intensive products for export. Trade of real water between water-rich and water-poor regions is generally impossible due to the large distances and associated costs, but trade in water-intensive products (virtual water trade) is realistic. Virtual water trade between nations and even continents could thus be used as an instrument to improve global water use efficiency and to achieve water security in water-poor regions of the world.
World-wide both politicians and the general public increasingly show interest in the pros and cons of `globalisation' of trade. This can be understood from the fact that increasing global trade implies increased
10
interdependence of nations. The tension in the debate relates to the fact that the game of global competition is played with rules that many see as unfair. Knowing that economically sound water pricing is poorly developed in many regions of the world, this means that many products are put on the world market at a price that does not properly include the cost of the water contained in the product. This leads to situations in which some regions in fact subsidise export of scarce water. 1.3. The objective of this study The objectives of this study are: 1. To estimate the amount of water needed to produce crops in different countries of the world; 2. To quantify the volume of virtual water trade flows between nations in the period 1995-1999; 3. To put the virtual water trade balances of nations within the context of national water needs and water availability. This report is primarily meant as a data report. We do not pretend to give an in-depth interpretation of the results. Besides, we limit ourselves to virtual water trade in relation to international crop trade, thus excluding virtual water trade related to international trade of livestock products and industrial products. 11
2. Method
2.1. Calculation of specific water demand per crop type
Per crop type, average specific water demand has been calculated separately for each relevant nation on the basis of FAO data on crop water requirements and crop yields:
SWD[n,
c]
=
CWR[n, c] CY[n, c]
(1)
Here, SWD denotes the specific water demand (m3 ton-1) of crop c in country n, CWR the crop water requirement (m3 ha-1) and CY the crop yield (ton ha-1).
The crop water requirement CWR (in m3 ha-1) is calculated from the accumulated crop evapotranspiration ETc (in mm/day) over the complete growing period. The crop evapotranspiration ETc follows from multiplying the `reference crop evapotranspiration' ET0 with the crop coefficient Kc:
ETc = K c Ч ET0
(2)
The concept of `reference crop evapotranspiration' was introduced by FAO to study the evaporative demand of the atmosphere independently of crop type, crop development and management practices. The only factors affecting ET0 are climatic parameters. The reference crop evapotranspiration ET0 is defined as the rate of evapotranspiration from a hypothetical reference crop with an assumed crop height of 12 cm, a fixed crop surface resistance of 70 s m-1 and an albedo of 0.23. This reference crop evapotranspiration closely resembles the evapotranspiration from an extensive surface of green grass cover of uniform height, actively growing, completely shading the ground and with adequate water (Smith et al., 1992). Reference crop evapotranspiration is calculated on the basis of the FAO Penman-Monteith equation (Smith et al., 1992; Allen et al., 1994a, 1994b; Allen et al., 1998):
ET0
=
0.408 ( Rn
-G) +
+
T
900 + 273
U2
( ea
(1+ 0.34U 2 )
-ed
)
(3)
in which:
ET0 = reference crop evapotranspiration [mm day-1];
Rn
= net radiation at the crop surface [MJ m-2 day-1];
G
= soil heat flux [MJ m-2 day-1];
T
= average air temperature [°C];
U2
= wind speed measured at 2 m height [m s-1];
ea
= saturation vapour pressure [kPa];
13
ed ea-ed
= actual vapour pressure [kPa]; = vapour pressure deficit [kPa]; = slope of the vapour pressure curve [kPa °C-1]; = psychrometric constant [kPa °C-1].
The crop coefficient accounts for the actual crop canopy and aerodynamic resistance relative to the hypothetical reference crop. The crop coefficient serves as an aggregation of the physical and physiological differences between a certain crop and the reference crop.
The overall scheme for the calculation of specific water demand is drawn in Figure 1.1. This figure also shows the next step: the calculation of the virtual water trade flows between nations.
Climatic parameters
Ref. crop evapotransp. E0 [mm day-1]
Crop coefficient Kc [-]
Crop evapotranspiration Ec [mm day-1]
Crop water requirement CWR [m3 ha-1]
Crop yield CY [ton ha-1]
Specific water demand SWD [m3 ton-1]
Global crop trade CT [ton yr-1]
Global virtual water trade VWT [m3 yr-1]
Figure 1.1. Steps in the calculation of global virtual water trade.
2.2. Calculation of virtual water trade flows and the national virtual water trade balance
Virtual water trade flows between nations have been calculated by multiplying international crop trade flows by their associated virtual water content. The latter depends on the specific water demand of the crop in the exporting country where the crop is produced. Virtual water trade is thus calculated as:
VWT [ne , ni , c, t] = CT[ne , ni , c,t ]Ч SWD[ne ,c]
(4)
14
in which VWT denotes the virtual water trade (m3yr-1) from exporting country ne to importing country ni in year t as a result of trade in crop c. C T represents the crop trade (ton yr-1) from exporting country ne to importing country ni in year t for crop c. SWD represents the specific water demand (m3 ton-1) of crop c in the exporting country. Above equation assumes that if a certain crop is exported from a certain country, this crop is actually grown in this country (and not in another country from which the crop was just imported for further export). Although a certain error will be made in this way, it is estimated that this error will not substantially influence the overall virtual water trade balance of a country. Besides, it is practically impossible to track the sources of all exported products.
The gross virtual water import to a country ni is the sum of all imports:
GVWI[ni ,t ] = VWT [ne , ni , c, t]
(5)
ne ,c
The gross virtual water export from a country ne is the sum of all exports:
GVWE[ne , t ] = VWT [ne , ni , c, t]
(6)
ni ,c
The net virtual water import of a country is equal to the gross virtual water import minus the gross virtual water export. The virtual water trade balance of country x for year t can thus be written as:
NVWI[x,t ] = GVWI [x, t]- GVWE [x,t ]
(7)
where NVWI stands for the net virtual water import (m3 yr-1) to the country. Net virtual water import to a country has either a positive or a negative sign. The latter indicates that there is net virtual water export from the country.
2.3. Calculation of a nation's `water footprint'
The total water use within a country itself is not the right measure of a nation's actual appropriation of the global water resources. In the case of net import of virtual water import into a country, this virtual water volume should be added to the total domestic water use in order to get a picture of a nation's real call on the global water resources. Similarly, in the case of net export of virtual water from a country, this virtual water volume should be subtracted from the volume of domestic water use. The sum of domestic water use and net virtual water import can be seen as a kind of `water footprint' of a country, on the analogy of the `ecological footprint' of a nation. In simplified terms, the latter refers to the amount of land needed for the production of the goods and services consumed by the inhabitants of a country. Studies have shown that for some countries the ecological footprint is smaller than the area of the nation's territory, but in other cases much bigger (Wackernagel and Rees, 1996; Wackernagel et al., 1997). The latter means that apparently some nations need land outside their own territory to provide in their goods and services. 15
The `water footprint' of a country (expressed as a volume of water per year) is defined as:
Water footprint = WU + NVWI
(8)
in which WU denotes the total domestic water use (m3yr-1) and NVWI the net virtual water import of a country (m3yr-1). As noted earlier, the latter can have a negative sign as well.
Total domestic water use WU should ideally refer to the sum of `blue' water use (referring to the use of groundand surface water) and `green' water use (referring to the use of precipitation). However, since data on green water use on country basis are not easily obtainable, we have provisionally chosen in this report to limit the definition of water use to blue water use. It should be noted that `net virtual water import' as defined in the previous section includes both `blue' and `green' water.
2.4. Calculation of national water scarcity, water dependency and water self-sufficiency
At the start of this study we expected to find a relation between national water scarcity and net virtual water import. One would logically assume that a country with high water scarcity would seek to profit from net virtual water import. On the other hand, countries with abundant water resources could make profit by exporting water in virtual form. In order to check this hypothesis we need indices of both water scarcity and virtual water import dependency. Plotting countries in a graph with water scarcity on the x-axis and virtual water import dependency on the y-axis, would expectedly result in some positive relation.
As an index of national water scarcity we use the ratio of total water use to water availability:
WS = WU Ч100
(9)
WA
In this equation, WS denotes national water scarcity (%), WU the total water use in the country (m3yr-1) and WA the national water availability (m3yr-1). Defined in this way, water scarcity will generally range between zero and hundred per cent, but can in exceptional cases (e.g. groundwater mining) be above hundred per cent. As a measure of the national water availability WA we take the annual internal renewable water resources, that are the average fresh water resources renewably available over a year from precipitation falling within a country's borders (see for instance Gleick, 1993). As noted in the previous section, total water use WU should ideally refer to the sum of blue and green water use, but for practical reasons we have provisionally chosen in this report to define water scarcity as the ratio of blue water use to water availability, which is generally done by others as well.
Next, we have looked for a proper indicator of `virtual water import dependency' or `water dependency' in brief. The indicator should reflect the level to which a nation relies on foreign water resources (through import
16
of water in virtual form). The water dependency WD of a nation is in this report calculated as the ratio of the net virtual water import into a country to the total national water appropriation:
WD
=
NVWI WU + NVWI
Ч 100
if NVWI 0
(10)

0
if NVWI < 0
The value of the water dependency index will per definition vary between zero and hundred per cent. A value of zero means that gross virtual water import and export are in balance or that there is net virtual water export. If on the other extreme the water dependency of a nation approaches hundred percent, the nation nearly completely relies on virtual water import.
As the counterpart of the water dependency index, the water self-sufficiency index is defined as follows:
WSS
=
WU
WU + NVWI
Ч 100
if NVWI 0
(11)

100
if NVWI < 0
The water self-sufficiency of a nation relates to the water dependency of a nation in the following simple way:
WSS = 1 -WD
(12)
The level of water self-sufficiency WSS denotes the national capability of supplying the water needed for the production of the domestic demand for goods and services. Self-sufficiency is hundred per cent if all the water needed is available and indeed taken from within the own territory. Water self-sufficiently approaches zero if a country heavily relies on virtual water imports.
17
3. Data sources Data on crop water requirements are calculated with FAO's CropWat model for Windows, which is available through the web site of FAO (www.fao.org). The CropWat model uses the FAO Penman-Monteith equation for calculating reference crop evapotranspiration as described in the previous chapter (Clarke et al., 1998). The CropWat model calculates crop water requirement of different crop types on the basis of the following assumptions: (1) Crops are planted under optimum soil water conditions without any effective rainfall during their life; the crop is developed under irrigation conditions. (2) Crop evapotranspiration under standard conditions (ETc), this is the evapotranspiration from disease-free, well-fertilised crops, grown in large fields with 100% coverage. (3) Crop coefficients are selected depending on the single crop coefficient approach, that means single cropping pattern, not dual or triple cropping pattern. Climatic data The climatic data needed as input to CropWat have been taken from FAO's climatic database ClimWat, which is also available through FAO's web site. The ClimWat database contains climatic data for more than hundred countries. For many countries climatic data are available for different climatic stations. As a crude approach, the capital climatic station data have been taken as the country representative. For the countries, where the required climatic input data are not available in ClimWat, the crop water requirement is taken from the guideline of FAO as reported by Gleick (1993) (Appendix IV). Depending on the country, the authors made an estimate somewhere between the minimum and maximum estimate given in the FAO guideline. If still data were lacking, data were taken from a neighbouring country. Crop parameters In the crop directory of the CropWat package sets of crop parameters are available for 24 different crops (Table 3.1). The crop parameters used as input data to CropWat are: the crop coefficients in different crop development stages (initial, middle and late stage), the length of each crop in each development stage, the root depth, and the planting date. For the 14 crops where crop parameters are not available in the CropWat package, crop parameters have been based on Allen et al. (1998). Crop yields Data on crop yields have been taken from the FAOSTAT database, again available through FAO's web site. 19
Table 3.1. Availability of crop parameters.
Crops for which crop parameters have been taken from FAO's Crops for which crop parameters have been
CropWat package
taken from Allen et al. (1998)
Banana
Maize
Sugar beet
Artichoke
Onion dry
Barley
Mango
Sugar cane
Carrots
Peas
Bean dry
Millet
Sunflower
Cauliflower
Rice
Bean green
Oil palm fruit
Tobacco
Citrus
Safflower
Cabbage
Pepper
Tomato
Cucumber
Spinach
Cotton seeds
Potato
Vegetable
Lettuce
Sweet potato
Grape
Sorghum
Watermelon
Oats
Groundnut
Soybean
Wheat
Onion green
Global trade in crops As a source for the global trade in crops, we have used the 1995-1999 data contained in the Personal Computer Trade Analysis System (PC-TAS), a cd-rom produced by the United Nations Statistics Division (UNSD) in New York in collaboration with the International Trade Centre (ITC) in Geneva. These data are based on the Commodity Trade Statistics Data Base (COMTRADE) of the UNSD. Every year individual countries supply the UNSD with their annual international trade statistics, detailed by commodity and partner country. These data are processed into a standard format with consistent coding and valuation. Commodities are classified according the Harmonised System (HS) classification of the World Customs Organization.
Link between two crop classifications Specific water demand is calculated for 38 crop types as distinguished by the FAO in CropWat. The Harmonised System (HS) classification used in the COMTRADE database is a much more detailed classification. For our purpose we therefore have to link the two classifications, which has been done as shown in Table 3.2.
Table 3.2. The link between FAO's crop types and the Harmonised System classification.
FAO crop types Artichoke Banana
Commodities in the Harmonised System classification Global artichoke, fresh or chilled Banana, including plantains
Barley
Barley
Bean dry
Bean dried
Bean, small red, dried
Bean green
Bean, frozen
Bean, shelled or unshelled, fresh or chilled
Cabbage
Cabbage lettuce, fresh or chilled
Cabbages, konrabi
Carrots Cauliflower Citrus
Carrot, fresh or chilled Cauliflower and headed broccoli, fresh or chilled Citrus fruit, fresh or dried Grapefruit, fresh or chilled
20
FAO crop types Cotton seeds Cucumber Sorghum Grape Groundnut Lettuce Maize Millet Oats Onion dry Onion green Oil palm fruit Peas Pepper Potato Sugar beet Sugar cane Rice Safflower Soybean Spinach Sunflower Sweet potato Tobacco Tomato Vegetable Wheat
Commodities in the Harmonised System classification Cotton seed, whether or not broken Cucumber and gherkins provisionally preserved but not immediately consumption Cucumber and gherkins, fresh or chilled Grain sorghum Grape dried Grape fresh Groundnut in shell whether or not broken Groundnuts in shell or roasted Lettuce, fresh or chilled Maize (corn) Millet Oats Onion dried, but not further prepared Onion and shallots, fresh or chilled Onion, provisionally preserved Palm nut Peas, dried, shelled Peas, frozen Peas, shelled or unshelled, fresh or chilled Pepper of the genius capsuis Potato, fresh or chilled Potatoes, frozen Raw sugar beet Raw sugar can Rice, broken Rice, husked, (brown) Rice, in the husk (paddy or rough) Safflower seed, whether or not broken Soybean Spinach, N-Z spinach orache spinach Sunflower seed Sweet potatoes, fresh or dried Tobacco, unmanufactured, not stemmed Tobacco, unmanufactured, partly or wholly stemmed Tomatoes, fresh or chilled Vegetable, fresh or chilled vegetable, frozen Wheat Durum wheat Buck wheat
21
4. Specific water demand per crop type per country The calculated crop water requirements for different crops in different countries are shown in Appendix I. The crop water requirements as calculated here refer to the evapotranspiration under optimal growth conditions (see Chapter 3). This means that the calculated values are overestimates, because in reality there are often water shortage conditions. On the other hand, the calculated values can also be seen as conservative, because they exclude inevitable losses (e.g. during transport and application of water) and required losses such as drainage. The calculated crop water requirements differ considerably over countries, which is mainly due to the differences in climatic conditions. Data on actual crop yields in the year 1999 have been retrieved from the FAOSTAT database. The data, which are country averages, are shown in Appendix II. Where country specific crop yield data are lacking in FAOSTAT, regional averages have been taken. The values that have been assessed in this way are presented in grey-shadow cells in Appendix II. The differences between countries are here even larger than in the case of the crop water requirements. This is due to the impact of the human factor on the actual crop yields. Specific water demand (m3/ton) per crop type has been calculated for different countries by dividing the crop water requirement (m3/ha) by the crop yield (ton/ha). The results are shown in Appendix III. Because both crop water requirements and crop yields strongly vary between countries, specific water demands vary as well. It is noted here that the specific water demand data for 1999 will be used to calculate the virtual water trade flows in the whole period 1995-1999 (see Chapter 5). This is acceptable because country crop yield data appear not to vary considerably over years. 23
5. Global trade in virtual water 5.1. International trade in virtual water 5.1.1. Overview of international virtual water trade The calculation results show that the global volume of crop-related virtual water trade between nations was 695 Gm3/yr in average over the period 1995-1999. For comparison: the global water withdrawal for agriculture (water use for irrigation) was about 2500 Gm3/yr in 1995 and 2600 Gm3/yr in 2000 (Shiklomanov, 1997, p.61). Taking into account the use of rainwater by crops as well, the total water use by crops in the world has been estimated at 5400 Gm3/yr (Rockstrцm and Gordon, 2001, p.847). This means that 13% of the water used for crop production in the world is not used for domestic consumption but for export (in virtual form). This is the global percentage; the situation strongly varies between countries. Considering the period 1995-1999, the top-5 list of countries with net virtual water export is: 1st. United States, 2nd. Canada, 3rd. Thailand, 4th. Argentina, and 5th. India. The top-5 list of countries in terms of net virtual water import for the same period is: 1st. Sri Lanka, 2nd. Japan, 3rd. Netherlands, 4th. Republic of Korea, and 5th. China. Top-30 lists are given in Table 5.1. The ranking lists do not considerably change if we look into particular years within the five-year period 1995-1999. Net virtual water import, Gm3 -100- -800 -10- -100 -1- -10 0- -1 0- 1 1- 10 10- 50 50- 100 100- 500 No Data Figure 5.1. National virtual water trade balances over the period 1995-1999. Green coloured countries have net virtual water export. Red coloured countries have net virtual water import. 25
National virtual water trade balances over the period 1995-1999 are shown in the coloured world map of Figure 5.1. Countries with net virtual water export are green and countries with net virtual water import are red. Appendix V presents the complete set of calculated data with respect to gross import, gross export and net import of virtual water for all countries of the world for the years 1995 up to 1999. Some countries have net export of virtual water over the period 1995-1999, but net import of virtual water in one or more particular years in this period (Table 5.2). There are also countries that show the reverse (Table 5.3).
Table 5.1. Top-30 of virtual water export countries and top-30 of virtual water import countries (over 1995-1999).
Country
Net export volume (109 m3)
United States
758.3
1
Canada
272.5
2
Thailand
233.3
3
Argentina
226.3
4
India
161.1
5
Australia
145.6
6
Vietnam
90.2
7
France
88.4
8
Guatemala
71.7
9
Brazil
45.0
10
Paraguay
42.1
11
Kazakhstan
39.2
12
Ukraine
31.8
13
Syria
21.5
14
Hungary
19.8
15
Myanmar
17.4
16
Uruguay
12.1
17
Greece
9.8
18
Dominican Republic
9.7
19
Romania
9.1
20
Sudan
5.8
21
Bolivia
5.3
22
Saint Lucia
5.2
23
United Kingdom
4.8
24
Burkina Faso
4.5
25
Sweden
4.2
26
Malawi
3.8
27
Dominica
3.1
28
Benin
3.0
29
Slovakia
3.0
30
Country Sri Lanka Japan Netherlands Korea Rep. China Indonesia Spain Egypt Germany Italy Belgium Saudi Arabia Malaysia Algeria Mexico Taiwan Colombia Portugal Iran Bangladesh Morocco Peru Venezuela Nigeria Israel Jordan South Africa Tunisia Poland Singapore
Net import volume (109 m3) 428.5 297.4 147.7 112.6 101.9 101.7 82.5 80.2 67.9 64.3 59.6 54.4 51.3 49.0 44.9 35.2 33.4 31.1 29.1 28.7 27.7 27.1 24.6 24.0 23.0 22.4 21.8 19.3 18.8 16.9
26
Table 5.2. Countries with net export of virtual water in the period 1995-1999 that have however net import in particular years. A `minus' indicates a negative virtual water trade balance (i.e. net export of virtual water). A `plus' indicates a positive virtual water trade balance (i.e. net import of virtual water).
Country
1995
1996
1997
1998
1999
Brazil
-
+
-
-
-
Syria
-
-
-
-
+
Greece
-
-
-
+
-
Sudan
-
+
+
+
-
United Kingdom
+
+
-
+
+
Burkina Faso
-
+
+
-
-
Benin
+
-
-
-
-
Slovakia
-
-
+
-
-
Ecuador
-
-
-
+
-
Bulgaria
-
+
+
-
-
Cuba
+
-
-
+
-
Finland
-
-
-
-
+
Yugoslavia
-
-
+
-
-
Uganda
-
-
+
+
+
Papua N. Guinea
-
-
+
-
+
Bahamas
+
-
-
-
-
Montserrat
-
-
-
-
+
Tajikistan
+
-
-
-
-
Cameroon
-
-
+
+
-
Martinique
-
+
+
+
+
Pakistan
-
-
+
-
+
Solomon Islands
-
+
-
+
+
Central Africa
-
+
-
+
-
Samoa
-
-
-
+
-
Wallis Island
-
+
+
+
+
Table 5.3. Countries with net import of virtual water in the period 1995-1999 that have however net export in particular years. A `minus' indicates a negative virtual water trade balance (i.e. net export of virtual water). A `plus' indicates a positive virtual water trade balance (i.e. net import of virtual water).
Country
1995
1996
1997
1998
1999
St. Kitts & Nevis
-
+
-
+
+
Guinea Bissau
+
+
-
-
+
Burundi
+
+
-
+
+
Tonga
+
+
-
+
+
Mongolia
-
+
+
+
+
Nepal
+
+
+
-
+
Kyrgyzstan
+
+
-
-
-
27
Country Macedonia Lithuania Bermuda Bahrain Gambia Bosnia Madagascar George Croatia Nicaragua Uzbekistan Czech Republic Philippines Russian Fed. Mexico
1995 + + + + + + + + + +
1996 + + + + + + + + + +
1997 + + + + + + + + + + + + -
1998 + + + + + + + + + + +
1999 + + + + + + + + + +
5.1.2. Virtual water trade balance per country In this section we present the virtual water trade balances of a few selected countries. For each country, we give the annual balances for the individual years 1995-1999 and the overall five-year balance. Figures 5.2-5.11 show the virtual water trade balances for the ten biggest net export countries: United States, Canada, Thailand, Argentina, India, Australia, Vietnam, France, Guatemala and Brazil. Figures 5.12-5.21 show the balances for the ten biggest net import countries: Sri Lanka, Japan, Netherlands, Korea Rep., China, Indonesia, Spain, Egypt, Germany and Italy. The Figures 5.22-5.29 show the balances for a few other countries which have been chosen a bit arbitrarily. For the balances of those countries that are not shown here, the reader is referred to the data in Appendix V. It is not the intention of this report to make an in-depth analysis and interpretation of the calculated national virtual water trade balances. Instead, we limit ourselves here to make just a few observations. First, the data show that developed countries generally have a more stable virtual water trade balance than the developing countries. Peak years in virtual water export were for instance found for Thailand, India, Vietnam, Guatemala and Syria. The opposite, the occurrence of peak years with relatively high virtual water import, was found for Sri Lanka and Jordan. Second, we see that countries that are relatively close to each other in terms of geography and development level can have a rather different virtual water trade balance. While European countries such as the Netherlands, Belgium, Germany, Spain and Italy import virtual water in the form of crops, France exports a large amount of virtual water. In the Middle East we see that Syria has net export of virtual water related to crop trade, but Jordan and Israel have net import. In Southern Africa, Zimbabwe and Zambia had net export in the period 1995- 28
1999, but South Africa had net import. [It should be noted that the trade balance of Zimbabwe has recently turned due to the recent political and economic developments.] In the regions of the Former Soviet Union, countries such as Kazakhstan and the Ukraine have net export of virtual water, but the Russian Federation has net import. It is hard to put the data presented here in the context of earlier studies, for the simple reason that few quantitative studies into virtual water trade between nations have been carried out. A few interesting studies have been done for the Middle East and Africa (Allan, 1997, 2001; Wichelns, 2001; Nyagwambo, 1998; Earle, 2001). One study was done by Buchvald for Israel and is available in Hebrew only. The main results of this study are cited in Yegnes-Botzer (2001). According to Buchvald's estimation Israel exported 377 million m3 of virtual water in 1999 and imported more than 6900 million m3. The current study calculates for Israel an export of 700 million m3 of virtual water in 1999 and an import of 7400 million m3.
1.0E+12 9.0E+11 8.0E+11
Export Import
7.0E+11
6.0E+11
5.0E+11
4.0E+11
3.0E+11
2.0E+11
1.0E+11
0.0E+00 1995 1996 1997 1998 1999 Total
3.5E+11 3.0E+11 2.5E+11
Export Import
2.0E+11
1.5E+11
1.0E+11
5.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.2. Gross virtual water import into and export Figure 5.3. Gross virtual water import into and export from the United States in the period 1995-1999 (m3yr-1). from Canada in the period 1995-1999 (m 3yr-1).
3.0E+11 2.5E+11 2.0E+11 1.5E+11 1.0E+11 5.0E+10
Export Import
2.5E+11 2.0E+11
Export Import
1.5E+11
1.0E+11
5.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.4. Gross virtual water import into and export from Thailand in the period 1995-1999 (m 3yr-1).
Figure 5.5. Gross virtual water import into and export from Argentina in the period 1995-1999 (m 3yr-1).
29
2.0E+11 1.8E+11 1.6E+11
Export Import
1.4E+11
1.2E+11
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
1.6E+11 1.4E+11 1.2E+11
Export Import
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.6. Gross virtual water import into and export from India in the period 1995-1999 (m3yr-1).
Figure 5.7. Gross virtual water import into and export from Australia in the period 1995-1999 (m3yr-1).
1.0E+11 9.0E+10 8.0E+10
Export Import
7.0E+10
6.0E+10
5.0E+10
4.0E+10
3.0E+10
2.0E+10
1.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
1.6E+11 1.4E+11 1.2E+11
Export Import
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.8. Gross virtual water import into and export from Vietnam in the period 1995-1999 (m 3yr-1).
9.0E+10 8.0E+10 7.0E+10
Export Import
6.0E+10
5.0E+10
4.0E+10
3.0E+10
2.0E+10
1.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.9. Gross virtual water import into and export from France in the period 1995-1999 (m 3yr-1).
1.8E+11 1.6E+11 1.4E+11
Export Import
1.2E+11
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.10. Gross virtual water import into and export Figure 5.11. Gross virtual water import into and export
from Guatemala in the period 1995-1999 (m3yr-1).
from Brazil in the period 1995-1999 (m 3yr-1).
30
5.0E+11 4.5E+11 4.0E+11
Export Import
3.5E+11
3.0E+11
2.5E+11
2.0E+11
1.5E+11
1.0E+11
5.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
3.5E+11 3.0E+11 2.5E+11
Export Import
2.0E+11
1.5E+11
1.0E+11
5.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.12. Gross virtual water import into and export Figure 5.13. Gross virtual water import into and export
from Sri Lanka in the period 1995-1999 (m3yr-1).
from Japan in the period 1995-1999 (m3yr-1).
2.0E+11 1.8E+11 1.6E+11
Export Import
1.4E+11
1.2E+11
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
1.2E+11 1.0E+11
Export Import
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.14. Gross virtual water import into and export Figure 5.15. Gross virtual water import into and export from the Netherlands in the period 1995-1999 (m3yr-1). from the Korea Republic in the period 1995-1999 (m 3yr-1).
1.8E+11 1.6E+11 1.4E+11
Export Import
1.2E+11
1.0E+11
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
1.2E+11 1.0E+11
Export Import
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.16. Gross virtual water import into and export Figure 5.17. Gross virtual water import into and export
from China in the period 1995-1999 (m 3yr-1).
from Indonesia in the period 1995-1999 (m 3yr-1).
31
1.2E+11 1.0E+11
Export Import
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
9.0E+10 8.0E+10 7.0E+10
Export Import
6.0E+10
5.0E+10
4.0E+10
3.0E+10
2.0E+10
1.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.18. Gross virtual water import into and export Figure 5.19. Gross virtual water import into and export
from Spain in the period 1995-1999 (m3yr-1).
from Egypt in the period 1995-1999 (m 3yr-1).
1.4E+11 1.2E+11 1.0E+11
Export Import
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
1.2E+11 1.0E+11
Export Import
8.0E+10
6.0E+10
4.0E+10
2.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.20. Gross virtual water import into and export Figure 5.21. Gross virtual water import into and export
from Germany in the period 1995-1999 (m 3yr-1).
from Italy in the period 1995-1999 (m 3yr-1).
3.0E+10 2.5E+10 2.0E+10 1.5E+10 1.0E+10 5.0E+09
Export Import
2.5E+10 2.0E+10
Export Import
1.5E+10
1.0E+10
5.0E+09
0.0E+00 1995 1996 1997 1998 1999 Total
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.22. Gross virtual water import into and export Figure 5.23. Gross virtual water import into and export
from Syria in the period 1995-1999 (m 3yr-1).
from Jordan in the period 1995-1999 (m 3yr-1).
32
3.0E+10 2.5E+10
Export Import
2.0E+10
1.5E+10
1.0E+10
5.0E+09
0.0E+00 1995 1996 1997 1998 1999 Total
6.0E+10 5.0E+10
Export Import
4.0E+10
3.0E+10
2.0E+10
1.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.24. Gross virtual water import into and export Figure 5.25. Gross virtual water import into and export
from Israel in the period 1995-1999 (m 3yr-1).
from Saudi Arabia in the period 1995-1999 (m 3yr-1).
4.0E+10 3.5E+10 3.0E+10
Export Import
2.5E+10
2.0E+10
1.5E+10
1.0E+10
5.0E+09
0.0E+00 1995 1996 1997 1998 1999 Total
3.5E+09 3.0E+09 2.5E+09
Export Import
2.0E+09
1.5E+09
1.0E+09
5.0E+08
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.26. Gross virtual water import into and export Figure 5.27. Gross virtual water import into and export
from South Africa in the period 1995-1999 (m 3yr-1).
from Zimbabwe in the period 1995-1999 (m 3yr-1).
8.0E+10 7.0E+10 6.0E+10
Export Import
5.0E+10
4.0E+10
3.0E+10
2.0E+10
1.0E+10
0.0E+00 1995 1996 1997 1998 1999 Total
4.5E+10 4.0E+10 3.5E+10
Export Import
3.0E+10
2.5E+10
2.0E+10
1.5E+10
1.0E+10
5.0E+09
0.0E+00 1995 1996 1997 1998 1999 Total
Figure 5.28. Gross virtual water import into and export Figure 5.29. Gross virtual water import into and export from the Russian Federation in the period 1995-1999 (m3yr-1). from Kazakhstan in the period 1995-1999 (m 3yr-1).
33
5.1.3. International virtual water trade by product
The total volume of crop-related virtual water trade between nations in the period 1995-1999 can for 30% be explained by trade in wheat (Table 5.4). Next come soybeans and rice, which account respectively for 17% and 15% of global crop-related virtual water trade.
Table 5.4. Global virtual water trade between nations by product (Gm3).
Product
1995 % 1996 % 1997 % 1998 % 1999 % Total %
Wheat
181 32.35 215 26.49 254 32.01 203 29.00 197 32.73 1049 30.20
Soybean
103 18.37 108 13.28 125 15.79 122 17.47 135 22.45 593 17.07
Rice
81 14.57 198 24.35 71 8.95 119 16.95 65 10.78 534 15.36
Maize
58 10.40 56 6.93 67 8.51 65 9.22 61 10.14 307 8.85
Raw sugar
9 1.60 68 8.35 119 14.99 42 5.99 13 2.09 250 7.20
Barley
36 6.41 30 3.67 35 4.41 29 4.15 30 5.05 170 4.88
Sunflower
12 2.17 24 2.97 20 2.50 20 2.92 18 2.94 94 2.71
Sorghum
12 2.14 26 3.21 12 1.49 10 1.39 10 1.73 70 2.01
Bananas
11 1.88 16 2.00 15 1.95 15 2.15 11 1.83 68 1.97
Grapes
12 2.07 13 1.64 13 1.65 13 1.87 13 2.24 65 1.86
Oats
9 1.67 10 1.25 11 1.41
9 1.34 10 1.61 50 1.43
Tobacco
5 0.98 10 1.19 11 1.33 13 1.90
7 1.10 46 1.31
Ground-nuts
6 1.10
7 0.84
8 1.02
6 0.90
4 0.70 32 0.91
Peppers
4 0.80
5 0.62
9 1.12
6 0.84
6 1.02 30 0.87
Cotton seeds 5 0.83
5 0.56
5 0.64
6 0.92
7 1.24 28 0.81
Peas
3 0.46
4 0.48
4 0.57
5 0.67
2 0.31 18 0.50
Beans
3 0.47
6 0.68
3 0.35
2 0.36
2 0.38 16 0.45
Potatoes
2 0.40
2 0.26
2 0.31
2 0.33
2 0.37 11 0.33
Onions
2 0.28
3 0.33
2 0.19
2 0.35
1 0.25 10 0.28
Vegetables
1 0.14
1 0.10
1 0.12
4 0.50
1 0.17
7 0.20
Millet
1 0.23
1 0.14
1 0.16
1 0.17
1 0.22
6 0.18
Tomatoes
1 0.14
1 0.12
1 0.13
1 0.17
1 0.19
5 0.15
Palm nuts
1 0.12
1 0.12
1 0.07
1 0.08
0 0.08
3 0.09
Safflower
1 0.12
1 0.09
1 0.08
1 0.09
1 0.09
3 0.09
Cucumbers
0 0.06
1 0.12
1 0.07
0 0.06
0 0.07
3 0.08
Cauliflower
0 0.06
0 0.05
0 0.05
0 0.06
0 0.07
2 0.06
Cabbages
0 0.05
0 0.04
0 0.04
0 0.05
0 0.06
2 0.05
Carrots
0 0.04
0 0.03
0 0.03
0 0.04
0 0.05
1 0.04
Citrus
0 0.04
0 0.03
0 0.02
0 0.01
0 0.01
1 0.02
Artichokes
0 0.02
0 0.01
0 0.01
0 0.01
0 0.02
1 0.01
Lettuce
0 0.01
0 0.01
0 0.01
0 0.01
0 0.02
0 0.01
Sweet potato 0 0.02
0 0.01
0 0.01
0 0.01
0 0.01
0 0.01
Spinach
0 0.00
0 0.00
0 0.00
0 0.00
0 0.01
0 0.00
Grand total 559 100.00 813 100.00 793 100.00 700 100.00 601 100.00 3475 100.00
34
5.2. Inter-regional trade in virtual water 5.2.1. Inter-regional virtual water trade relations In order to show virtual water trade between major world regions, the world has been classified into thirteen regions: North America, Central America, South America, Eastern Europe, Western Europe, Central and South Asia, the Middle East, South-East Asia, North Africa, Central Africa, Southern Africa, the Former Soviet Union, and Oceania. A list of countries per world region is given in Appendix VI. The gross virtual water trade between and within regions in the period 1995-1999 is presented in Table 5.5. The details of the regional trade data are presented in Appendix VII. Net virtual water trade between regions in the period 1995-1999 is presented in Table 5.6 and Figure 5.30. In the figure the largest trade flows are indicated with arrows. The regions that have net import are marked in red colour and the regions that have net export are marked in green colour. For each world region, a ranking has been made of the most important regions for gross import and gross export of virtual water (Table 5.7). Also a ranking has been made of the most important regions for net import and net export (Table 5.8).
North America Central America
Net virtual water import, Gm3 -1030 -240 -140 -135 -45 -22 -5 12 20 151 222 380 833 No Data
South America
Western Europe Eastern Europe
FSU
North Africa
Middle East
Central Africa
Central and South Asia SOUTH EAST ASIA
Southern Africa
Oceania
Figure 5.30. Virtual water trade balances of thirteen world regions over the period 1995-1999. Green coloured regions have net virtual water export; red coloured regions have net virtual water import. The arrows show the largest net virtual water flows between regions (>100 Gm3).
35
Table 5.5. Gross virtual water trade between world regions in the period 1995-1999 (Gm 3). The grey-shaded cells refer to gross trade between countries within the regions.
Exporter
Importer
Central Central Central & Eastern Africa America South Europe Asia
Middle East
North North Oceania Africa America
FSU
Southern South South- Western Africa America east Asia Europe
Total gross export
Central Africa
1.65
0.00
0.11
0.12
0.07
0.05
0.05
0.02
0.01
0.64
0.00
0.05
1.99
3.11
Central America
0.25
4.62 124.52
0.78
0.43
1.53 40.37
0.01
4.29
0.17
2.45
0.41 14.33 189.52
Central and South Asia
3.53
0.67 100.40
3.07 21.64 13.76
3.32
0.40
9.88
9.44
0.87 64.89 17.77 149.25
Eastern Europe
0.02
0.15
2.82 20.40 10.37
7.56
0.56
0.21
5.23
0.12
0.08
0.55 37.42 65.09
Middle East
0.79
0.13 11.56
2.54 25.65 13.21
2.35
0.82
1.21
0.03
0.48
2.72 18.37 54.21
North Africa
0.13
0.15
2.46
1.14
3.74
2.74
4.18
0.00
0.22
0.43
4.61
0.16 13.79 30.99
North America
2.87 153.24 395.21
9.51 63.77 128.51 82.78
4.02
9.65
9.84 88.67 82.80 170.27 1118.38
Oceania
0.81
0.40 83.26
0.07
9.47
9.31
2.69
2.80
0.06
2.84
3.66 31.56
4.41 148.54
FSU
0.01
0.33
8.00 13.06 29.26
3.07
0.96
0.01 48.68
0.00
0.06
0.40 35.00 90.17
Southern Africa
0.73
0.68
5.38
0.50
0.37
0.42
1.74
0.10
0.26
2.78
1.31
1.21
7.66 20.33
South America
1.63
7.16 62.29
7.83 20.26 18.63 13.37
0.34
4.85
2.75 146.73 16.50 191.21 346.83
South-east Asia
1.81
2.14 226.63
2.56 25.76 31.56 12.97
2.63
5.98 11.81
3.45 87.20 11.08 338.38
Western Europe
2.00
2.26 59.53 18.97 20.20 25.45
5.08
0.15
3.89
2.03
1.59
1.78 250.46 142.95
Total gross import
14.60 167.30 981.76 60.16 205.35 253.06 87.62
8.71 45.53 40.11 107.24 203.03 523.28 2698
Table 5.6. Net virtual water trade between regions in the period 1995-1999 (Gm 3).
Exporter
Importer
Central Africa
Central Central & Eastern America South Europe Asia
Middle East
North North Oceania Africa America
Central Africa
-0.25 -3.43
0.1 -0.73 -0.08 -2.82 -0.79
Central America
0.25
123.84
0.62
0.3
1.38 -112.87
-0.4
Central and South Asia
3.43 -123.84
0.25 10.08 11.31 -391.89 -82.86
Eastern Europe
-0.1 -0.62 -0.25
7.83
6.42 -8.96
0.14
Middle East
0.73
-0.3 -10.08 -7.83
9.47 -61.43 -8.65
North Africa
0.08 -1.38 -11.31 -6.42 -9.47
-124.34 -9.31
North America
2.82 112.87 391.89
8.96 61.43 124.34
1.33
Oceania
0.79
0.4 82.86 -0.14
8.65
9.31 -1.33
FSU
0 -3.96 -1.89
7.83 28.05
2.86 -8.69 -0.04
Southern Africa
0.09
0.51 -4.06
0.38
0.34 -0.02
-8.1 -2.74
South America
1.63
4.71 61.42
7.75 19.79 14.02 -75.31 -3.32
South-east Asia
1.77
1.73 161.74
2 23.04 31.41 -69.84 -28.94
Western Europe
0.02 -12.07 41.76 -18.44
1.84 11.66 -165.19 -4.26
Total net import
11.51 -22.2 832.49 -4.94 151.15 222.08 -1030.77 -139.84
FSU Southern South South- Western Total net Africa America east Asia Europe export
0 3.96 1.89 -7.83 -28.05 -2.86 8.69 0.04 0.26 4.79 5.57 -31.11 -44.65
-0.09 -1.63 -1.77
-0.51 -4.71 -1.73
4.06 -61.42 -161.74
-0.38 -7.75
-2
-0.34 -19.79 -23.04
0.02 -14.02 -31.41
8.1 75.31 69.84
2.74
3.32 28.94
-0.26 -4.79 -5.57
-1.44 -10.6
1.44
13.05
10.6 -13.05
-5.62 -189.62
-9.3
19.76 -239.59 -135.33
-0.02 -11.51
12.07
22.2
-41.76 -832.49
18.44
4.94
-1.84 -151.15
-11.66 -222.08
165.19 1030.77
4.26 139.84
31.11 44.65
5.62 -19.76
189.62 239.59
9.3 135.33
-380.33
380.33
Table 5.7. Ranking of gross import and gross export regions for each of the thirteen world regions.
Region
Gross import from
Gross export to
First
Second
Third
Fourth
First
Central Africa
Central and South Asia
North America
Western Europe South-east Asia Western Europe
North Africa
North America
South-east Asia Western Europe South America Western Europe
Southern Africa
South-east Asia North America
Central and South Asia
Oceania
Western Europe
South America
North America
North Africa
South-east Asia Oceania
Western Europe
Central America North America Central Asia Middle East South-east Asia Eastern Europe Western Europe Oceania Russian Fed
North America Central America North America North America North America Western Europe South America North America Central and South Asia
South America Southern Africa South-east Asia Russian Fed Central and South Asia Russian Fed North America South-east Asia North America
Western Europe South-east Asia Central America South-east Asia Oceania North America Eastern Europe Middle East South-east Asia
South-east Asia Western Europe Oceania Central and South Asia Southern Africa South America Middle East Central and South Asia Eastern Europe
Central and South Asia Central and South Asia South-east Asia Western Europe Central and South Asia Western Europe Central and South Asia Central and South Asia Western Europe
Second Southern Africa South America South and Central Asia Central and South Asia North America Western Europe Middle East North Africa North Africa Middle East North Africa South-east Asia Middle East
Third Eastern Europe North America North America Middle East Western Europe Central America Western Europe Central and South Asia Middle East North Africa Middle East Middle East Eastern Europe
Fourth Central and South Asia Middle East South America North Africa Russian Fed North Africa North Africa South-east Asia North America Russian Fed Eastern Europe North Africa Central and South Asia
Table 5.8. Ranking of net import and net export regions for each of the thirteen world regions.
Region
Net import from
First
Second
Third
Fourth
Central Africa
Central and South Asia
North America South-east Asia South America
North Africa
North America
South-east Asia South America
Western Europe
Southern Africa
South-east Asia North America
Central and South Asia
Oceania
South America
North America
Oceania
Net export to First Eastern Europe Central Africa Western Europe Western Europe
Central America North America
North America
Central and South Asia Middle East South-east Asia
North America North America North America
Eastern Europe Western Europe
North America South America
Ocean
North America
Russian Fed
North America
South America South-east Asia
South-east Asia Central America
Southern Africa Oceania
Central and South Asia Central and South Asia North Africa
Russian Fed Oceania Russian Fed North America South-east Asia
South-east Asia South America South America Russian Fed South America
South America North Africa
Ocean
Central and South Asia
South-east Asia Western Europe
Eastern Europe Central and South Asia
Central and South Asia
Central America Western Europe
Second Central America Central and South Asia Western Europe Western Europe Middle East Central Africa North Africa Middle East North Africa South-east Asia Middle East
Third Eastern Europe Middle East Russian Fed North Africa Southern Africa Middle East North Africa Middle East North Africa Eastern Europe
Fourth Middle East North Africa Central Africa Central Africa Southern Africa Oceania Central Africa Middle East North Africa
5.2.2. Virtual water trade balance per world region The virtual water trade balances of the thirteen world regions are shown in Figures 5.31a and 5.31b. The former shows the gross import and export of virtual water for each region. The latter shows the difference between the two, the net import, which is positive in some cases and negative in others. Regions with a significant net virtual water import are: Central and South Asia, Western Europe, North Africa, and the Middle East. Two other regions with net virtual water import, but less substantial, are Southern Africa and Central Africa. Regions with substantial net virtual water export are: North America, South America, Oceania, and South-east Asia. Three other regions with net virtual water export, but less substantial, are the FSU, Central America and Eastern Europe. North America is by far the biggest virtual water exporter in the world, while Central and South Asia is by far the biggest virtual water importer. A further ranking of the world regions is given in Table 5.9.
1200 1000 800 600
Export Import
400 200
0 Central Central Central Eastern Middle North North Oceania FSU Africa America and South Europe East Africa America Asia
South South South Western Africa America east Asia Europe
Figure 5.31a. Gross virtual water import and export per region in the period 1995-1999 (Gm3).
1000
500
0
-500
-1000
-1500 Central Central Central Eastern Middle North North Oceania FSU Africa America and South Europe East Africa America Asia
South South South Western Africa America east Asia Europe
Figure 5.31b. Net virtual water import per region in the period 1995-1999 (Gm3).
40
Table 5.9. Ranking of regions in terms of gross virtual water import and gross virtual water export.
Gross virtual water import (1995-1999)
Region
Gm 3
Ranking
Gross virtual water export (1995-1999)
Region
Gm 3
Central and South Asia
982
1
North America
1118
Western Europe
523
2
South America
347
North Africa
253
3
South-east Asia
338
Middle East
205
4
Central America
190
South-east Asia
203
5
Central and South Asia
149
Central America
167
6
Oceania
149
South America
107
7
Western Europe
143
North America
88
8
FSU
90
Eastern Europe
60
9
Eastern Europe
65
FSU
46
10
Middle East
54
Southern Africa
40
11
North Africa
31
Central Africa
15
12
Southern Africa
20
Oceania
9
13
Central Africa
3
In the remaining part of this section, an overview will be given of the import and export of virtual water for each of the thirteen world regions. Figures 5.32a to 5.44a give the gross virtual water import and export of the thirteen world regions for the period 1995-1999. Figures 5.32b to 5.44b give the net virtual water import of the world regions for this period.
450
400
350
300
250
200
150
100
50
0
Central Central Central Eastern Middle
Africa America and South Europe
East
Asia
North Africa
Oceania
FSU
Export Import
South Africa
South South east Western
America Asia
Europe
Figure 5.32a. Gross virtual water import and export of North America in the period 1995-1999 (Gm3).
41
Central Africa 0
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
Oceania
FSU
-50
-100
-150
-200
-250
-300
-350
-400
-450
South Africa
South South east Western
America Asia
Europe
Figure 5. 32b. Net virtual water import of North America in the period 1995-1999 (Gm3).
180
160
140
120
100
80
60
40
20
0
Central Central Eastern Middle North
North Oceania
FSU
Africa and South Europe
East
Africa America
Asia
Export Import
South Africa
South South east Western
America Asia
Europe
Figure 5.33a. Gross virtual water import and export of Central America in the period 1995-1999 (Gm3).
150 100 50 0
-50 -100
-150
Central Central Eastern Middle
North
North Oceania
FSU
Africa and South Europe
East
Africa America
Asia
South Africa
South South east Western
America Asia
Europe
Figure 5.33b. Net virtual water import of Central America in the period 1995-1999 (Gm3).
42
250
Export
200
Import
150
100
50
0
Central Central Central Eastern Middle
Africa America and South Europe
East
Asia
North Africa
North Oceania America
FSU
South South east Western
Africa
Asia
Europe
Figure 5.34a. Gross virtual water import and export of South America in the period 1995-1999 (Gm 3).
100
50
0
-50
-100
-150
-200
-250
Central Central Central Eastern Middle North
North Oceania
FSU
Africa America and South Europe
East
Africa America
Asia
South South east Western
Africa
Asia
Europe
Figure 5.34b. Net virtual water import of South America in the period 1995-1999 (Gm3).
40
Export
35
Import
30
25
20
15
10
5
0
Central Central Central Middle North
North Oceania
Africa America and South East
Africa America
Asia
FSU
South Africa
South South east Western
America Asia
Europe
Figure 5.35a. Gross virtual water import and export of Eastern Europe in the period 1995-1999 (Gm3).
43
15
10
5
0 -5 -10
-15
-20
Central Central Central Middle
North
North Oceania
FSU
Africa America and South East
Africa America
Asia
South Africa
South South east Western
America
Asia
Europe
Figure 5.35b. Net virtual water import of Eastern Europe in the period 1995-1999 (Gm3).
250
Export
200
Import
150
100
50
0
Central Central Central Eastern Middle North
North Oceania
FSU
Africa America and South Europe
East
Africa America
Asia
South Africa
South South east America Asia
Figure 5.36a. Gross virtual water import and export of Western Europe in the period 1995-1999 (Gm 3).
250
200 150
100
50
0 -50
-100
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North Oceania America
FSU
South Africa
South South east America Asia
Figure 5.36b. Net virtual water import of Western Europe in the period 1995-1999 (Gm3).
44
450
400
350
300
250
200
150
100
50
0 Central Central Eastern Middle
North
North Oceania
Africa America Europe
East
Africa America
FSU
Export Import
South Africa
South South east Western
America Asia
Europe
Figure 5.37a. Gross virtual water import and export of Central and South Asia in the period 1995-1999 (Gm3).
450
400 350
300
250
200
150
100
50
0
-50
Central Central Eastern Middle North
North Oceania
FSU
Africa America Europe
East
Africa America
South Africa
South South east Western
America
Asia
Europe
Figure 5.37b. Net virtual water import of Central and South Asia in the period 1995-1999 (Gm3).
70
60
50
40 30
20
10
0
Central Central Central Eastern North
North Oceania
Africa America and South Europe Africa America
Asia
FSU
Export Import
South Africa
South South east Western
America Asia
Europe
Figure 5.38a. Gross virtual water import and export of the Middle East in the period 1995-1999 (Gm 3).
45
70
60
50
40
30
20
10
0
-10
-20
Central Central Central Eastern North
North Oceania
FSU
Africa America and South Europe Africa America
Asia
South South South east Western
Africa America
Asia
Europe
Figure 5.38b. Net virtual water import of the Middle East in the period 1995-1999 (Gm3).
250
Export
200
Import
150
100
50
0
Central Central Central Eastern Middle
North
North Oceania
Africa America and South Europe
East
Africa America
Asia
FSU
South Africa
South Western America Europe
Figure 5.39a. Gross virtual water import and export of South-east Asia in the period 1995-1999 (Gm 3).
100
50
0
-50
-100 -150
-200
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North Oceania America
FSU
South Africa
South Western America Europe
Figure 5.39b. Net virtual water import of South-east Asia in the period 1995-1999 (Gm3).
46
140
120
100
80
60
40
20
0
Central Central Central Eastern Middle
North Oceania
Africa America and South Europe
East
America
Asia
FSU
Export Import
South Africa
South South east Western
America
Asia
Europe
Figure 5.40a. Gross virtual water import and export of North Africa in the period 1995-1999 (Gm3).
140
120
100
80
60
40
20
0
-20
Central Central Central Eastern Middle
North Oceania
FSU
Africa America and South Europe
East
America
Asia
South Africa
South South east Western
America Asia
Europe
Figure 5.40b. Net virtual water import of North Africa in the period 1995-1999 (Gm 3).
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Central Central
Eastern Middle
North
North Oceania
FSU
America and South Europe
East
Africa America
Asia
Export Import
South Africa
South South east Western
America
Asia
Europe
Figure 5.41a. Gross virtual water import and export of Central Africa in the period 1995-1999 (Gm3).
47
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
Central Central Eastern Middle North
North Oceania
FSU
America and South Europe
East
Africa America
Asia
South Africa
South South east Western
America Asia
Europe
Figure 5.41b. Net virtual water import of Central Africa in the period 1995-1999 (Gm3).
14
Export
12
Import
10
8
6
4
2
0
Central Central Central Eastern Middle North
North Oceania
Africa America and South Europe
East
Africa America
Asia
FSU
South South east Western
America
Asia
Europe
Figure 5.42a. Gross virtual water import and export of Southern Africa in the period 1995-1999 (Gm 3).
12
10
8
6
4
2
0
-2
-4
-6
-8 Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North America
Oceania
FSU
South South east Western
America Asia
Europe
Figure 5.42b. Net virtual water import of Southern Africa in the period 1995-1999 (Gm3).
48
40
Export
35
Import
30
25
20
15
10
5
0
Central Central Central Eastern Middle North
North Oceania South
South South east Western
Africa America and South Europe
East
Africa America
Africa America
Asia
Europe
Asia
Figure 5.43a. Gross virtual water import and export of the Former Soviet Union in the period 1995-1999 (Gm3).
15
10
5
0
-5
-10
-15
-20
-25
-30
-35
Central Africa
Central America
Central and South Asia
Eastern Europe
Middle East
North Africa
North Oceania America
South Africa
South South east Western
America
Asia
Europe
Figure 5.43b. Net virtual water import of the Former Soviet Union in the period 1995-1999 (Gm3).
90
80
70
60
50 40
30
20
10
0
Central Central Central Eastern Middle
Africa America and South Europe
East
Asia
North Africa
North America
FSU
Export Import
South Africa
South South east Western
America
Asia
Europe
Figure 5.44a. Gross virtual water import and export of Oceania in the period 1995-1999 (Gm3).
49
10
0
-10
-20
-30
-40
-50
-60
-70
-80
-90
Central Central Central Eastern Middle North
North
FSU
Africa America and South Europe
East
Africa America
Asia
South Africa
South South east Western
America Asia
Europe
Figure 5.44b. Net virtual water import of Oceania in the period 1995-1999 (Gm3).
5.2.3. Gross virtual water trade between countries within regions
The virtual water trade flows between countries in each of the thirteen world regions are shown in Figures 5.45 and 5.46. The gross trade in virtual water within a region has been calculated by summing up all virtual water imports of the countries of the region that originate from other countries in the same region. Note that it yields the same result as if we would have added all virtual water exports of the countries in a region that go to other countries in the same region.
Western Europe is the region with the biggest internal trade in virtual water. Besides, the trade volume is rather stable here. South America is second in the ranking of internal trade volume. Central and South Asia is a rather unstable region if we look at the annual volume of virtual water traded between the countries of the region. Central and South Asia is the largest region in terms of population, so food demand is higher than in the other regions. This explains why the region is the biggest virtual water importer (see Figure 5.31b). The virtual water trade between countries within the region is also high, thus the countries within the region highly depend on both countries outside and countries within the region.
70 60 1995 1996 1997 1998 1999 50 40 30 20 10 0 Central Central Central Eastern Middle North North Oceania FSU Africa America and South Europe East Africa America Asian
Average
South South Africa America
South East Asian
Western Europe
Figure 5.45. Gross virtual water trade between countries within each region in the years 1995-1999 (Gm3).
50
300
250
200
150
100
50
0
Central Central Central Eastern Middle North North Oceania
Africa America and South Europe East
Africa America
Asia
FSU
South South South Western Africa America east Asia Europe
Figure 5.46. Gross virtual water trade between countries within each region in the total period 1995-1999 (Gm3).
5.3. Intercontinental trade in virtual water
5.3.1. Intercontinental virtual water trade relations
In the previous section the world was divided into thirteen `world regions'. In the current section, virtual water trade will be presented at the level of `continents'. The six continents ­ Africa, America, Asia, Europe, Oceania and the Former Soviet Union (FSU) ­ correspond to the world regions as indicated in Table 5.10. The volumes of gross virtual water trade between continents in the period 1995-1999 are presented in Table 5.11. The gross virtual water trade between countries within the continents is given in the same table (the greyshaded cells). The net virtual water trade between continents is presented in Table 5.12.
Table 5.10. Correspondence between the six `continents' and the thirteen `world regions'.
Continent
Region
America
North America
Central America
South America
Europe
Eastern Europe
Western Europe
Asia
Middle East
Central and South Asia
South-east Asia
Africa
North Africa
Central Africa
Southern Africa
FSU
FSU
Ocean
Oceania
51
Table 5.11. Gross virtual water trade between continents in the years 1995-1999 (Gm3). The grey-shaded cells refer to gross trade between countries within the continents.
Importer Exporter
Africa
America
Asia
Europe
Oceania
FSU
Africa
1995
1.874
0.442
4.204
5.980
0.029
0.005
1996
2.201
1.651
3.247
4.708
0.018
0.115
1997
1.560
1.106
2.071
3.967
0.022
0.094
1998
2.060
3.121
2.463
5.380
0.020
0.130
1999
1.873
6.393
1.542
5.154
0.024
0.145
Total
9.568
12.713
13.527
25.188
0.113
0.488
America
1995
32.655
83.598
136.725
78.196
1.239
1.523
1996
31.882
107.887
146.857
73.898
0.755
3.028
1997
33.980
115.344
227.862
77.621
1.023
2.640
1998
35.488
114.888
138.451
79.397
0.646
3.206
1999
32.187
117.654
116.306
84.815
0.705
8.392
Total
166.193
539.371
766.201
393.934
4.370
18.790
Asia
1995
16.082
4.593
73.852
8.580
0.599
0.855
1996
12.549
6.212
243.549
12.740
0.715
3.524
1997
16.918
5.375
90.138
12.797
0.881
3.394
1998
20.624
6.023
108.184
11.345
0.810
7.120
1999
17.804
4.175
43.626
9.353
0.844
2.179
Total
85.951
26.379
566.451
55.379
3.851
17.072
Europe
1995
9.390
1.607
8.782
61.467
0.129
1.818
1996
5.008
1.117
8.737
65.128
0.032
1.748
1997
7.549
1.973
52.808
65.571
0.066
1.476
1998
7.611
2.727
13.979
67.163
0.048
1.225
1999
7.624
2.297
10.948
67.857
0.089
2.855
Total
37.181
9.722
95.253
327.254
0.366
9.121
Oceania
1995
0.178
0.363
13.247
0.474
0.547
0.000
1996
3.028
1.847
36.723
1.021
0.646
0.023
1997
4.889
1.950
27.316
0.921
0.476
0.013
1998
2.799
0.949
26.480
1.139
0.393
0.018
1999
2.064
1.641
20.527
0.935
0.738
0.002
Total
12.958
6.751
124.293
4.482
2.796
0.057
FSU
1995
0.694
0.003
3.813
4.757
0.000
0.545
1996
0.575
0.547
7.066
14.002
0.000
9.740
1997
0.776
0.416
5.533
12.495
0.013
11.843
1998
0.673
0.308
13.261
11.171
0.000
10.695
1999
0.365
0.076
7.985
5.644
0.000
15.862
Total
3.082
1.350
37.659
48.066
0.013
48.682
Table 5.12. Net virtual water trade between continents in the period 1995-1999 (Gm 3).
Importer Exporter Africa
Africa
America -153.48
Asia
Europe Oceania
-72.42
-11.99
-12.84
America Asia Europe
153.48 72.42 11.99
-739.82 -384.21
739.82 39.87
384.21 -39.87
-2.38 -120.44 -4.12
Oceania FSU Total net import
12.84 2.59 253.32
2.38 -17.44 -1292.57
120.44 20.59 848.3
4.12 38.94 375.41
-0.04 -139.82
FSU -2.59 17.44 -20.59 -38.94 0.04 -44.64
Total net export -253.32 1292.57 -848.3 -375.41 139.82 44.64 0
52
5.3.2. Virtual water trade balance per continent Figure 5.47a shows the gross virtual water import and gross virtual water export for each continent for the whole period 1995-1999. Figure 5.47b shows the net import per continent. Net import is negative - this means there is net export ­ for America, Oceania and the Former Soviet Union. Net import is positive for Asia, Europe and Africa. Table 5.13 ranks the continents according their gross import and gross export of virtual water. America is by far the largest export continent, with an average gross export of 270 Gm3 per year (over the period 1995-1999). The USA takes the largest share in this total export. Gross import to the American continent as a whole is only 11 Gm3 per year in average, which results in a net export of virtual water of 259 Gm3 per year. Asia is the largest importer of virtual water. Average gross import amounts to 207 Gm3 per year (over the years 1995-1999). Average gross export amounts to 38 Gm3 per year, resulting in an average annual import of 169 Gm3 .
1600 1400 1200 1000 800 600 400 200 0
Africa
America
Asia
Europe
Oceania
Export Import FSU
Figure 5.47a. Gross virtual water import and export per continent in the period 1995-1999 (Gm3).
1000
500
0
-500
-1000
-1500
Africa
America
Asia
Europe
Oceania
FSU
Figure 5.47b. Net virtual water import per continent in the period 1995-1999 (Gm3).
53
Table 5.13. Ranking of continents in terms of gross virtual water import and gross virtual water export.
Gross virtual water import (1995-1999)
Rank
Continent
Gm 3
Gross virtual water export (1995-1999)
Continent
Gm 3
Asia Europe Africa
1037
1
America
527
2
Asia
305
3
Europe
1350 189 152
America
57 4
Oceania
149
FSU
46
5
FSU
90
Oceania
9
6
Africa
65
5.3.3. Gross virtual water trade between countries within continents
Data on gross virtual water trade between countries within continents are shown in Table 5.11 (the grey-shaded cells). Asia and America have the biggest internal gross virtual water trade (Figures 5.48-5.49). The virtual water trade between the American countries seems to be rather stable, which is not the case for the trade between the countries of the Asian continent. If compared to Asia and America, virtual water trade between countries within the area of the Former Soviet Union, within Africa and within Oceania is very small.
300 250 200 150 100 50 0 Africa
America
1995 1996 1997 1998 1999 Average
Asian
Europe
Oceania
FSU
Figure 5.48. Gross virtual water trade between countries within each continent in the years 1995-1999 (Gm 3).
600
500
400
300
200
100
0 Africa
America
Asia
Europe
Oceania
FSU
Figure 5.49. Gross virtual water trade between countries within each continent in the period 1995-1999 (Gm 3).
54
6. Virtual water trade of nations in relation to national water needs and availability
6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations
Using the definition given in Section 2.3, a `water footprint' has been calculated for each nation. Next, given the definitions in Section 2.4, indicators of national water scarcity, water self-sufficiency and water dependency have been calculated. The basic data on national water withdrawal and water availability have been taken from Raskin et al. (1997). The data on net virtual water import per country are taken from Appendix Vc. The results are shown in Table 6.1.
The level of water self-sufficiency has been classified into six categories: 0-20%; 20-50%; 50-70%; 70-90%; 90-99%; and 100%. Table 6.2 lists the countries in each of the categories.
Table 6.1. Water footprints, water scarcity, water self-sufficiency and water dependency of nations in 1995.
Country
Water
Water
Net virtual Water
withdrawal availability1 water import footprint
(106 m3)
(106 m3)
(106 m3)
(106 m3)
Water scarcity (%)
Water self- Water
sufficiency dependency
(%)
(%)
Afghanistan
35704
50000
29
35733
71.4
99.9
0.1
Albania
356
21300
100
456
1.7
78.1
21.9
Algeria
5042
14300
9523
14565
35.3
34.6
65.4
Angola
628 184000
224
852
0.3
73.7
26.3
Argentina
35812 994000
-36742
-930
3.6
100.0
0.0
Armenia
4109
13300
308
4417
30.9
93.0
7.0
Australia
27312 343000
-13269
14043
8.0
100.0
0.0
Austria
2424
90300
-42
2382
2.7
100.0
0.0
Azerbaijan
17061
33000
158
17219
51.7
99.1
0.9
Bahrain
334
290
144
478
115.2
69.8
30.2
Bangladesh
26467 2,357,000
12391
38858
1.1
68.1
31.9
Belarus
2979
73800
142
3121
4.0
95.4
4.6
Belgium
9237
12500
11730
20967
73.9
44.1
55.9
Benin
154
25800
97
251
0.6
61.4
38.6
Bhutan
23
95000
10
33
0.0
70.2
29.8
Bolivia
1557 300000
-1409
148
0.5
100.0
0.0
Bosnia/Herzeg.
1354 265000
83
1437
0.5
94.3
5.7
Brazil
46856 6,950,000
-1933
44923
0.7
100.0
0.0
Bulgaria
13576 205000
-1128
12448
6.6
100.0
0.0
Burkina Faso
412
17500
-10
402
2.4
100.0
0.0
Burundi
127
3600
2
129
3.5
98.8
1.2
Cambodia
660 498100
201
861
0.1
76.7
23.3
1 Data refer to the sum of internal and external water resources. 55
Country
Water
Water
Net virtual Water
withdrawal availability1 water import footprint
(106 m3)
(106 m3)
(106 m3)
(106 m3)
Water scarcity (%)
Water self- Water
sufficiency dependency
(%)
(%)
Cameroon
500 268000
-15
485
0.2
100.0
0.0
Canada
47246 2,901,000
-55330
-8084
1.6
100.0
0.0
Cape Verde
30 300000
40
70
0.0
43.0
57.0
Cent. African Rep.
85 141000
-1
84
0.1
100.0
0.0
Chad
218
43000
3
221
0.5
98.6
1.4
Chile
23203 468000
1509
24712
5.0
93.9
6.1
China
504315 2,800,000
42189 546504
18.0
92.3
7.7
Colombia
6031 1,070,000
5604
11635
0.6
51.8
48.2
Comoros
13
1020
13
26
1.3
50.2
49.8
Congo
51 832000
636
687
0.0
7.4
92.6
Costa Rica
1464
95000
932
2396
1.5
61.1
38.9
Cote d'Ivoire
941
77700
578
1519
1.2
62.0
38.0
Croatia
1760 265000
-166
1594
0.7
100.0
0.0
Cuba
9585
34500
203
9788
27.8
97.9
2.1
Czech Rep.
2727
58200
-610
2117
4.7
100.0
0.0
Denmark
1210
13000
-1029
181
9.3
100.0
0.0
Djibouti
11
2300
102
113
0.5
9.7
90.3
Dominican R.
3483
20000
-1190
2293
17.4
100.0
0.0
Ecuador
6677 314000
-516
6161
2.1
100.0
0.0
Egypt
55432
68500
15302
70734
80.9
78.4
21.6
El Salvador
1084
19000
918
2002
5.7
54.1
45.9
Eritrea
240
8800
27
267
2.7
90.0
10.0
Estonia
3220
17600
194
3414
18.3
94.3
5.7
Ethiopia
2156 110000
487
2643
2.0
81.6
18.4
Fiji
33
28600
68
101
0.1
32.6
67.4
Finland
2243 113000
-431
1812
2.0
100.0
0.0
France
38570 198000
-18454
20116
19.5
100.0
0.0
Gabon
78 164000
64
142
0.0
55.0
45.0
Gambia
36
8000
150
186
0.5
19.3
80.7
Georgia
4054
65200
207
4261
6.2
95.1
4.9
Germany
47303 171000
12228
59531
27.7
79.5
20.5
Ghana
325
53200
229
554
0.6
58.7
41.3
Greece
7109
58700
-2989
4120
12.1
100.0
0.0
Guatemala
1501 116000
-883
618
1.3
100.0
0.0
Guinea-Bissau
22
27000
8
30
0.1
72.8
27.2
Guyana
1501 241000
-14
1487
0.6
100.0
0.0
Haiti
47
11000
364
411
0.4
11.4
88.6
Honduras
1656
63400
315
1971
2.6
84.0
16.0
Hungary
6678 120000
-5536
1142
5.6
100.0
0.0
56
Country Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea (DPR) Korea (Rep.) Kuwait Kyrgyzstan Laos Latvia Lebanon Liberia Libya Lithuania Macedonia Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Nepal Netherlands New Zealand
Water
Water
Net virtual Water
withdrawal availability1 water import footprint
(106 m3)
(106 m3)
(106 m3)
(106 m3)
Water scarcity (%)
Water self- Water
sufficiency dependency
(%)
(%)
167 168000
56
223
0.1
74.9
25.1
607227 2,085,000
-24610 582617
29.1
100.0
0.0
83061 2,530,000
25256 108317
3.3
76.7
23.3
85608 117500
5494
91102
72.9
94.0
6.0
52259 109200
51
52310
47.9
99.9
0.1
808
50000
675
1483
1.6
54.5
45.5
2277
2200
2021
4298
103.5
53.0
47.0
56362 167000
12706
69068
33.7
81.6
18.4
414
8300
271
685
5.0
60.4
39.6
91945 547000
55416 147361
16.8
62.4
37.6
907
1700
7629
8536
53.4
10.6
89.4
44138 169400
-658
43480
26.1
100.0
0.0
2454
30200
1667
4121
8.1
59.5
40.5
16407
67000
561
16968
24.5
96.7
3.3
29558
66100
18964
48522
44.7
60.9
39.1
472 758000
472
944
0.1
50.0
50.0
12953
61700
143
13096
21.0
98.9
1.1
1260 270000
86
1346
0.5
93.6
6.4
673
34000
224
897
2.0
75.0
25.0
1178
5600
727
1905
21.0
61.8
38.2
168 232000
67
235
0.1
71.5
28.5
4751 600000
610
5361
0.8
88.6
11.4
4416
24200
443
4859
18.2
90.9
9.1
847 265000
-32
815
0.3
100.0
0.0
23135 337000
447
23582
6.9
98.1
1.9
971
18700
-387
584
5.2
100.0
0.0
13058 456000
9983
23041
2.9
56.7
43.3
1746 100000
67
1813
1.7
96.3
3.7
1851
11400
161
2012
16.2
92.0
8.0
390
2200
250
640
17.7
60.9
39.1
84209 357400
12432
96641
23.6
87.1
12.9
3787
13700
-210
3577
27.6
100.0
0.0
657
24600
-27
630
2.7
100.0
0.0
11540
30000
6710
18250
38.5
63.2
36.8
655 216000
376
1031
0.3
63.5
36.5
4694 1,082,000
-1477
3217
0.4
100.0
0.0
3284 170000
129
3413
1.9
96.2
3.8
8039
90000
29315
37354
8.9
21.5
78.5
1992 327000
845
2837
0.6
70.2
29.8
57
Country
Water
Water
Net virtual Water
withdrawal availability1 water import footprint
(106 m3)
(106 m3)
(106 m3)
(106 m3)
Water scarcity (%)
Water self- Water
sufficiency dependency
(%)
(%)
Nicaragua
1688 175000
168
1856
1.0
90.9
9.1
Niger
628
32500
106
734
1.9
85.5
14.5
Nigeria
4648 280000
628
5276
1.7
88.1
11.9
Norway
2077 392000
2548
4625
0.5
44.9
55.1
Oman
524
2103
1158
1682
24.9
31.1
68.9
Pakistan
278844 468000
-429 278415
59.6
100.0
0.0
Panama
1975 144000
68
2043
1.4
96.7
3.3
Papua New Guinea
120 801000
-81
39
0.0
100.0
0.0
Paraguay
541 314000
-6914
-6373
0.2
100.0
0.0
Peru
18726
40000
4789
23515
46.8
79.6
20.4
Philippines
49035 323000
-654
48381
15.2
100.0
0.0
Poland
12349
56200
4298
16647
22.0
74.2
25.8
Portugal
7257
69600
6154
13411
10.4
54.1
45.9
Qatar
226
195
49
275
115.9
82.2
17.8
Romania
25173 208000
-740
24433
12.1
100.0
0.0
Russia
116422 4,498,000
-4000 112422
2.6
100.0
0.0
Rwanda
809
6300
112
921
12.8
87.9
12.1
Saudi Arabia
5092
8760
10241
15333
58.1
33.2
66.8
Senegal
1702
39400
1282
2984
4.3
57.0
43.0
Sierra Leone
445 160000
324
769
0.3
57.9
42.1
Singapore
211
600
3599
3810
35.2
5.5
94.5
Slovakia
1818
30800
-1149
669
5.9
100.0
0.0
Slovenia
762 265000
1255
2017
0.3
37.8
62.2
Somalia
914
13500
138
1052
6.8
86.9
13.1
South Africa
14890
50000
6334
21224
29.8
70.2
29.8
Spain
30968 111300
17348
48316
27.8
64.1
35.9
Sri Lanka
10410
43200
1333
11743
24.1
88.6
11.4
Sudan
17800 154000
-5159
12641
11.6
100.0
0.0
Suriname
518 200000
-31
487
0.3
100.0
0.0
Sweden
2990 180000
-220
2770
1.7
100.0
0.0
Switzerland
1146
50000
2045
3191
2.3
35.9
64.1
Syria
10907
53700
-8414
2493
20.3
100.0
0.0
Tajikistan
14950 101300
49
14999
14.8
99.7
0.3
Tanzania
1193
89000
606
1799
1.3
66.3
33.7
Thailand
35042 179000
-39010
-3968
19.6
100.0
0.0
Togo
115
12000
598
713
1.0
16.1
83.9
Trinidad & Tobago
163
5100
707
870
3.2
18.7
81.3
Tunisia
3391
9000
6048
9439
37.7
35.9
64.1
Turkey
36237 193100
1206
37443
18.8
96.8
3.2
58
Country Turkmenistan UAE Uganda UK Ukraine Uruguay USA Uzbekistan Venezuela Viet Nam Yemen Yugoslavia Zambia Zimbabwe Grand total
Water
Water
Net virtual Water
withdrawal availability1 water import footprint
(106 m3)
(106 m3)
(106 m3)
(106 m3)
Water scarcity (%)
Water self- Water
sufficiency dependency
(%)
(%)
26186
72000
139
26325
36.4
99.5
0.5
657
797
2282
2939
82.4
22.4
77.6
217
66000
-338
-121
0.3
100.0
0.0
11929
71000
6390
18319
16.8
65.1
34.9
34623 231000
-1779
32844
15.0
100.0
0.0
4325 124000
-998
3327
3.5
100.0
0.0
492259 2,478,000 -168000 324259
19.9
100.0
0.0
91842 129600
434
92276
70.9
99.5
0.5
4446 1,317,000
4031
8477
0.3
52.5
47.5
30851 376000
-2596
28255
8.2
100.0
0.0
3397
4902
1416
4813
69.3
70.6
29.4
4248 265000
-1
4247
1.6
100.0
0.0
1759 116000
-38
1721
1.5
100.0
0.0
1527
20000
-340
1187
7.6
100.0
0.0
3696312 50547567
Table 6.2. Countries categorised into different levels of water self-sufficiency (data for 1995).
Level of water self-sufficiency
0-20% Congo Djibouti Gambia Haiti Jordan Singapore Togo Trinidad Tobago
20-50 % Algeria Belgium Cape Verde Fiji Kuwait Netherlands Norway Oman Saudi Arabia Slovenia Switzerland Tunisia UAE
50-70% Bahrain Bangladesh Benin Colombia Comoros Costa Rica Cфte d'Ivoire El Salvador Gabon Ghana Ireland Israel Jamaica Japan Kenya Korea (Rep.) Lebanon Malaysia Mauritius Morocco Mozambique Portugal Senegal Sierra Leone Spain Tanzania UK Venezuela
70-90%
90-99 %
Albania
Afghanistan
Angola
Armenia
Bhutan
Azerbaijan
Cambodia Belarus
Egypt
Bosnia
Eritrea
Burundi
Ethiopia
Chad
Germany
Chile
Guinea-Bissau China
Honduras
Cuba
Iceland
Estonia
Indonesia
Georgia
Italy
Iran
Latvia
Iraq
Liberia
Korea
Libya
Kyrgyzstan
Mexico
Laos
New Zealand Lithuania
Niger
Madagascar
Nigeria
Mali
Peru
Mauritania
Poland
Nepal
Qatar
Nicaragua
Rwanda
Panama
Somalia
Tajikistan
Southern
Turkey
Africa
Turkmenistan
Sri Lanka
Uzbekistan
Yemen
100% Argentina Australia Austria Bolivia Brazil Bulgaria Burkina Faso Cameroon Canada Central Africa Croatia Czech Rep Denmark Dominican R. Ecuador Finland France Greece Guatemala Guyana Hungary India Kazakhstan Macedonia
Malawi Moldova Mongolia Myanmar Pakistan Paraguay Philippines Papua/NG Russia Syria Slovakia Suriname Sweden Thailand Uganda Ukraine USA Vietnam Yugoslavia Romania Sudan Uruguay Zambia Zimbabwe
59
6.2. The relation between water scarcity and water dependency One would expect that in general terms there is a positive relationship between water scarcity and water dependency, because high water scarcity will make it attractive to import virtual water and thus become water dependent. One would logically suppose: the higher the scarcity within a country, the more dependency on water in other countries. To test this hypothesis, all countries of the world have been plotted in a scarcitydependency graph. The result is shown in Figure 6.1. Surprisingly, there seems to be no relation as hypothesised. Let us for simplicity schematise the scarcity-dependency graph into four areas or `classes'. See Figure 6.2. In Table 6.3 we can see that most of the countries fall in class I.
100
90
80
70
60
50
0
10
20
30
40
50
60 *
70
80
90
100
110
120
40
30
20
10
0 Water scarcity
Figure 6.1. Water dependency versus water scarcity for all countries of the world (1995).
Water dependency 100 50
Class II Class I
Class III Class IV
0
50
100
Water scarcity
Figure 6.2. Four classes in the scarcity-dependency graph. The grey-shaded areas refer to combinations of water scarcity and water dependency that can difficult be understood at first sight: high water scarcity but low water dependency, and low water scarcity but high water dependency.
60
Table 6.3. Position of countries in the scarcity-dependency graph. The grey-shaded countries fall in one of the grey-shaded areas of Figure 6.2.
Class I
Class II
Class III
Class IV
Angola
Costa Rica India
Mexico
South Africa Algeria
Belgium
Afghanistan
Albania
Cote d'Ivoire Indonesia Moldova
Spain
Cape Verde Jordan
Azerbaijan
Argentina Croatia
Italy
Mongolia
Sri Lanka Congo
Saudi Arabia Bahrain
Armenia
Cuba
Iraq
Morocco
Sudan
Djibouti
UAE
Egypt
Australia
Czech Rep. Ireland
Mozambique Suriname
Fiji
Iran
Austria
Denmark
Jamaica
Myanmar
Syria
Gambia
Israel
Bangladesh Dominican R. Japan
Nepal
Sweden
Haiti
Pakistan
Belarus
Ecuador
Kazakhstan New Zealand Tajikistan Kuwait
Qatar
Benin
El Salvador Kenya
Nicaragua Tanzania
Netherlands
Uzbekistan
Bhutan
Eritrea
Korea (DPR) Niger
Thailand
Norway
Yemen
Bosnia
Estonia
Korea (Rep.) Nigeria
Turkey
Oman
Bolivia
Ethiopia
Kyrgyztan Panama
Turkmenistan Singapore
Brazil
Finland
Laos
Papua/NG Uganda
Slovenia
Bulgaria
France
Latvia
Paraguay
UK
Switzerland
Burkina Faso Gabon
Lebanon
Peru
Ukraine
Togo
Burundi
Georgia
Liberia
Philippines Uruguay
Trinidad
Canada
Germany
Libya
Poland
USA
Tunisia
Cambodia Ghana
Lithuania
Portugal
Venezuela
Cameroon Greece
Macedonia Romania
Vietnam
Central Africa Guatemala Madagascar Russia
Yugoslavia
Chad
Guinea-Bissau Malawi
Rwanda
Zambia
Chile
Guyana
Malaysia
Senegal
Zimbabwe
China
Honduras
Mali
Sierra Leone
Colombia
Hungary
Mauritania Slovakia
Comoros
Iceland
Mauritius
Somalia
61
7. Concluding remarks This study was limited to virtual water trade related to crop trade between nations. Also other goods contain virtual water, for instance meat, diary products, cotton, paper, etc. In order to get a complete picture of the global virtual water trade flows, also other products than crops have to be taken into account. For instance, the virtual water trade balance of the Netherlands drawn in the current study suggests that this country has an incredibly high net import of virtual water, due to the large import of feed for the Dutch bio-industry. The balance will look quite differently if we would take into account the export of virtual water that relates to the export of meat from the Netherlands. As stated in the introductory chapter, the current study is primarily a data report, aimed at disclosing the numbers. A next step is of course to interpret the results and ask the question why the global virtual water trade flows are as they are. What are the explanatory factors behind changes in national virtual water trade balances? What is for instance the relative importance of year-to-year fluctuations in agricultural yields, subsidies in agriculture, national water scarcity, the development of domestic demand for agriculture products? Another next step is to go beyond `explanation' and to study how governments can deliberately interfere in the current national virtual water trade balances in order to achieve a higher global water use efficiency. Knowing the national virtual water trade balance is essential for developing a rational national policy with respect to virtual water trade. But for some large countries it might be as relevant to know the internal trade of virtual water within the country. For China for instance, relatively dry in the north and relatively wet in the south, domestic virtual water trade is a relevant issue. The method used for the calculation of the virtual water content of different types of crops has a few weak points. As explained, the crop water requirement estimates used in this study are conservative on the one hand (due to the water losses that are not taken into account), but they are overestimates on the other hand (because they are based on the assumption of optimal growth conditions, an assumption which is generally not met in reality). Improvements to the calculated figures can be made if we could make better estimates of actual specific water use per crop. 63
References Allan, J.A. (1997) ''Virtual water': A long term solution for water short Middle Eastern economies?' Occasional Paper 3, School of Oriental and African Studies (SOAS), University of London. Allan, J.A. (2001) The Middle East water question: Hydropolitics and the global economy I.B. Tauris, London. Allen, R.G., M. Smith, A. Perrier, and L.S. Pereira (1994a) An update for the definition of reference evapotranspiration ICID Bulletin 43(2): 1-34. Allen, R.G., M. Smith, A. Perrier, and L.S. Pereira (1994b) An update for the calculation of reference evapotranspiration ICID Bulletin 43(2): 35-92. Allen, R.G., L.S. Pereira, D. Raes, and M. Smith (1998) Crop evapotranspiration: Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper 56, FAO, Rome, Italy. Clarke, D., M. Smith, and K. El-Askari (1998) CropWat for Windows: User guide, Version 4.2, www.fao.org. Earle, A. (2001) 'The role of virtual water in food security in Southern Africa' Occasional Paper 33, School of Oriental and African Studies (SOAS), University of London. Gleick, P.H. (ed.) (1993) Water in crisis: A guide to the world's fresh water resources, Oxford University Press, New York, USA. Nyagwambo, N.L. (1998) ''Virtual water' as a water demand management tool: The Mupfure river basin case' MSc thesis DEW 045, IHE Delft, the Netherlands. Postel, S.L., Daily, G.C., and Ehrlich, P.R. (1996) `Human appropriation of renewable fresh water' Science 271:785-788. Rockstrцm, J. and L. Gordon (2001) `Assessment of green water flows to sustain major biomes of the world: implications for future ecohydrological landscape management' Phys. Chem. Earth (B) 26: 843-851. Shiklomanov, I.A. (ed.) (1997) Assessment of water resources and water availability in the world, Comprehensive assessment of the freshwater resources of the world, World Meteorological Organisation, Geneva. Smith, M., R.G. Allen, J.L. Monteith, A. Perrier, L.S. Pereira, and A. Segeren (1992) `Report on the Expert Consultation on revision of FAO methodologies for crop water requirements', FAO, Rome, Italy, 28-31 May 1990. 65
Wackernagel, M., Onisto, L., Linares, A.C., Falfan, I.S.L., Garcia, J.M., Guerrero, I.S., and Guerrero, M.G.S. (1997) Ecological footprints of nations: How much nature do they use? - How much nature do they have? Centre for Sustainability Studies, Universidad Anahuac de Xalapa, Mexico. Wackernagel, M. and Rees, W. (1996) Our ecological footprint: Reducing human impact on the earth New Society Publishers, Gabriola Island, B.C., Canada. Wichelns, D. (2001) 'The role of 'virtual water' in efforts to achieve food security and other national goals, with an example from Egypt' Agricultural Water Management 49:131-151. Yegnes-Botzer, A. (2001) 'Virtual water export from Israel: Quantities, driving forces and consequences' MSc thesis DEW 166, IHE Delft, the Netherlands. 66
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia bosnia and herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Banana 6800 6610 13690 9400 5840 11380 9760 6570 7120 8970 7120 7120 8130
Barley 3770 5420 3420
Bean dry Bean green
3850
3540
3970
4250
8040
4260
3400 5520 4510 3640 3560 4030 3560 3560 3790
2390 5920 5010 4140 2700 5290 2700 2700 4420
2500 4200 3390 2120 2200 2670 2200 2200 2760
Grapes Groundnut
6470
3890
12640
3790
14360
7370
6780 12510 10200 6530 3970 9030 3970 3542 7790
3550 7290 6060 3540 3180 5930 3180 3180 5240
Maize 3340 2160 6860
Mango 12680 21660
3290 6780 5640 3250 3170 4380 3170 3170 4890
11400 21190 17430 11450 17370 13820
Millet 4580 2160 5530 3360 4800 3820 2500 3690 4210 3690 3690 2580
Palm 11910 19630 10560 19600 16130 10550 15920 5140 12740
7050 9250 7120 3520 7010 16700 7260
3520 4180 3560 2780 3270 3420 3490
3450 4620 2700 2700 3450 3500 4200
3260 3190 2200 2120 2500 2740 2460
7640 10110 3970 2690 7410 9400 6290
4600 5570 3180 3400 4280 4450 4940
3350 5180 3170 3120 3980 4110 4620
13060 17000 12540 11530 11650
3370 3910 3690 2720 2810 3680 1850
12190 15770 5140 11600 14100 10670
5940 3520 18840 12510 7730
2960 2780 4310 2870 4220
2350 2700 2950 7180 3970
2470 2120 3570 3510 2250
7260 3110 11120 13010 7640
3430 3400 4200 6140 4830
3170 3120 3850 5700 3480
11350 16950 19570 13810
2380 2720 3050 4580 2940
10520 15700 17700 12780
7120 13690 16810 7070 7410 13330 18060 7120 19640 9860 7930 22850 5580 5180 6560 18380 14340
3560 3420 4440 3620 3580 2870 5140 3560 4600 4520 4110 5210 2540 4100 3120 4290 3220
2700 8040 4110 3050 3660 2860 5600 2700 4830 5050 4000 5740 2620 4330 3040 3450 2910
2200 4260 3480 3470 2740 2290 3760 2200 3540 3400 3200 4120 2270 4120 2460 3580 2630
3970 14360 9130 8570 7690 7470 9170 3970 10680 10360 8340 15070 8270 5200 7390 10550 8110
3180 7370 5440 5690 4650 3660 7150 3180 6150 6080 5110 7150 3740 4960 3940 4690 3830
3170 6860 5060 4470 4330 3390 6690 3170 5720 5660 4760 6610 2510 3500 3660 4330 3540
21660 15300 14130 13030 12080 16590 17880 17680 13970 21320 12250 10760 12110 16600 12980
3690 5530 4190 3010 2990 2980 5680 3690 4990 3860 4090 6070 2140 2930 3130 3560 3030
19630 14080 13190 12020 11230 15220 5140 16560 16360 13000 22720 11480 9980 11210 15370 12050
6300 16280 5530 9430 8670 7120 7120 22760 9480 9481 6290 9680 8720 14100 7120 19170 2050 7120 7120 8380 11930 21520 7120 7120 16280 6610 8520 6300 15280 17740
3880 3480 4350 4270 5050 3560 3560 6250 4330 4270 3050 5620 3930 3040 3560 4080 1030 3560 3560 4300 2630 4130 3560 3560 3480 5420 3940 3880 3000 3450
4000 3310 3330 4900 5200 2700 2700 6230 4840 2680 4520 4080 3100 2700 4470 1230 2700 2700 3730 2570 5220 2700 2700 3310 3970 4320 4000 3200 3950
3000 2830 3530 3190 4180 2200 2200 4660 3260 3260 2480 4200 3090 2400 2200 3170 1040 2200 2200 3430 2100 3110 2200 2200 2830 4250 2980 3000 2390 2690
7000 9220 5770 9790 7650 3970 3970 12020 10020 7440 10250 11080 7890 3970 10550 3600 3970 3970 8870 6680 11750 3970 3970 9220 12640 8910 7000 8600 9880
4080 4280 5370 5820 6530 3180 3180 8060 5820 3680 6930 5060 3960 3180 5600 1880 3180 3180 5220 3320 6230 3180 3180 4280 3790 5260 4080 4020 4880
2970 3960 2460 5410 6060 3170 3170 7520 5410 3410 4490 4690 3670 3170 5190 1410 3170 3170 4860 3070 5860 3170 3170 3960 2160 4890 2970 3710 4520
10940 14730 16830 20810 17080 11880 20110 16630 12780 17430 6630 14620 10810 19580 14730 15200 10940 13840 16100
2000 3460 3050 3530 5100 3690 3690 6340 3720 3390 4210 4250 3230 3690 4670 2210 3690 3690 3810 2680 5510 3690 3690 3460 2160 3330 2000 3380 4170
12250 13700 15580 19130 15830 11000 18570 14570 11890 16210 4590 7080 13450 10040 18310 7080 13700 14060 12250 12920 15040
Appendix I - p.1
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 7960 8230 6300 7120 7120 8510 8640 13070 14920 7120 13070 5530 9500 5400 8740 7720 8600 16780
Barley 4120 3900 3880 3560 3560 3780 4180 8800 1880 3560 8800 4350 4400 3650 1910 3700 3200 3370
Bean dry 3590 4270 4000 2700 2700 5510 3920 4160 8530 2700 4160 3330 4880 3070 5120 3510 3090
Bean green 3270 2930 3000 2200 2200 5190 3020 3280 2200 3530 3310 2980 2470 3380 2672 2800
Grapes Groundnut
8180
5020
8470
5220
7000
4080
3970
3180
3970
3180
11320
6930
9680
5010
13240
5980
14990
6180
3970
3180
13240
5980
5770
5370
9800
5910
5100
4620
9060
4340
8890
5340
3970
9680
4020
Maize 4680 4860 2970 3170 3170 4720 4850 6350 5710 3170 6350 2460 5500 3160 4030 4470 6420 3710
Mango 13620 14590 10940 19720 15710 24940 21620 24940 16820 10540 13550 14730 15140
Millet 3420 3110 2000 3690 3690 5180 4160 3960 4400 3690 3960 3050 3610 2910 3220 3530 3180 3260
Palm 12510 13460 12250 5140 18460 14500 22610 19300 7080 22610 9740 15550 9500 12240 13710 14120
6500
2460
3870
2980
5290
3370
2190
9880
3560
9230
17850 6840 7120 7560 13510 14220 10520 7120 7120 7010 20580 12380 14430 7810 8440 23300 8530 12530 15160 5820 7120 11160 7560 15170 7410 19090 8340 7120 6570 9130 23300 23110 2200 11130 11900 7320 7000 7880 8170 7840 7120 9000 12520 8530 15310 7120 7120 15610 12420
3000 3040 3560 1710 2960 3120 2550 3560 3560 3020 5130 3430 3520 3560 4250 4270 3820 6630 3120 3170 3560 5120 2400 3460 3580 4350 3330 3560 3640 3900 4270 4440 3970 4490 4520 4460 3530 4000 4170 3380 3560 3590 2870 4020 3560 3560 3560 4050
8170 3170 2700 4300 2400 3100 6140 2700 2700 3820 4340 3880 2600 3640 3770 4900 4210 6310 2370 3880 2700 5710 4150 2520 3660 3000 4380 2700 4140 4420 4900 4620 3180 5960 7100 3380 3150 2460 3450 3860 2700 3650 7180 4330 8430 2700 2700 3900
4510 2960 2200 2040 2690 2470 3200 2200 2200 2560 4170 2490 2980 3180 3560 3380 3000 5830 2710 2920 2200 3860 2570 2970 2740 3780 4040 2200 2120 3020 3380 3660 3170 4300 4760 2820 2630 3560 3400 3320 2200 2960 3510 3040 4420 2200 2200 3180
18220 7650 3970 7840 8250 7940 11000 3970 3970 6420 11550 6270 8230 8720 9880 13140 9270 14400 8970 6330 3970 11720 8080 8880 7690 11290 8170 3970 6530 10710 13140 14500 3600 12450 9900 9340 8040 11140 9200 8250 3970 4280 13010 8740 15980 3970 3970 9070
8210 4520 3180 3590 2500 3980 5540 3180 3180 3660 5850 4900 3670 4950 5850 6010 5160 9240 3250 4580 3180 6880 4300 3510 4650 4260 4970 3180 3540 5200 6010 5780 3690 7040 4540 4670 4390 4180 4940 4630 3180 4340 6140 5340 7750 3180 3180 5070
7620 3670 3170 3330 2280 3690 5150 3170 3170 2270 4530 4590 3350 4250 5100 5560 4790 8620 2980 3430 3170 4200 6400 4010 3230 4330 3910 2960 3170 3250 4820 5560 5310 4010 6560 2430 4520 4140 3850 4590 3630 3170 4270 5700 4970 7200 3170 3170 4710
24720 12770 11780 12080 12900 16580 11140 18650 11380 13030 14460 16200 21100 15560 23750 13620 12060 20000 12510 13660 13030 17160 14580 11450 17660 21100 22660 8340 19810 18370 15160 13070 16420 14800 14020 19570 14980 24010 15010
5980 3170 3690 2670 2300 3230 4150 3690 3690 3770 4450 3950 2670 3690 3860 5190 3600 7350 2490 3190 3690 4380 3300 2610 2990 3090 4060 3690 2500 4230 5190 4950 3290 5490 6490 3470 3290 3650 3390 3800 3690 3610 4580 3250 5770 3690 3690 3990
23960 11880 10650 11200 11980 15020 10290 17200 10460 12030 13430 15050 19750 14420 22090 12670 11130 18510 11420 12660 12020 15900 13670 7080 10550 16470 19750 21240 3520 18230 17150 13460 12090 15290 13650 13040 17700 13840 21730 7080 13860
Appendix I - p.2
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Banana Barley Bean dry Bean green Grapes Groundnut Maize Mango
Millet
Palm
9540 14220 19050 14220 7810 7580 7352 23110 8970 6230 8970 7520 15800 8740 7120 7120 9540 15340 16780 12440 8390 15440 9430 8110 7880 6700 16780 18360 9540 7120 7120 6570 5600 6560 7410 7050 9840 9900 9310 5570 14220 18070 18470
5640 3120 4560 3120 3560 3570 4030 3450 5590 3080 5750 4400 3560 3560 5640 1740 3370 2440 4700 3160 4270 3710 1260 5150 3370 3730 5640 3560 3560 3640 2760 3120 3580 3390 4570 3110 3590 4100 3150 4900 4060
4080 3100 4450 3100 3640 3470 5290 4200 5640 3620 8280 3950 2700 2700 4080 8790 3090 2180 4370 3130 4900 3950 4790 3820 3090 3600 4080 2700 2700 4140 2430 3040 3660 3180 5060 5410 4810 4190 2960 3710 2750
3600 2470 3580 2470 3180 3000
10060 7940 10490 7940 8720 8550
2670 2450 4570 3030 5620 3490 2200 2200 3600 3270 2800 2050 4260 2550 3190 2860 1900 3500 2800 3040 3600 2200 2200 2120 2580 2460 2740 3160 3440 3230 3340 3400 2550 4050 3570
9030 7430 8280 8060 17110 9260 3970 3970 10060 15350 9680 7260 8780 8760 9790 8890 8030 7330 9680 9070 10060 3970 3970 6530 8840 7390 7690 8170 10180 10570 10160 4390 8010 10150 10990
6390 3980 5780 3980 4950 4800 5930 4090 6870 4480 9250 5400 3180 3180 6390 6240 4020 2850 5740 4000 5820 4860 3500 4390 4020 5070 6390 3180 3180 3540 2690 3940 4650 5020 6140 5450 5490 4930 3850 5180 3910
4120 3690 5370 3690 4250 4240 4240
18500 12900 17310 12900 14460 14070
4380 3800 6640 3690 8620 5030 3170 3170 4120 5760 3710 2620 4460 3700 5410 4520 3240 1540 3710 4270 4120 3170 3170 3250 2450 3660 4330 4110 5720 5060 5100 4890 3570 4800 3580
17370 12130 13540 25900 15340 18500 22000 15140 11210 16870 13970 16830 14880 11730 12980 15140 16590 18500 11450 12590 12110 13030 13550 17440 16380 16130 12880 16380 16590
3940 3230 4580 3230 3690 3570 4210 3380 5620 3630 7180 3880 3690 3690 3940 4410 3260 2290 3950 3290 3530 3470 2530 2400 3260 3770 3940 3690 3690 2500 2890 3130 2990 3190 3800 4170 4270 4130 3080 3760 2860
16850 11980 16010 11980 13430 13040 12000 15920 11350 12580 24750 14130 16850 19600 14120 10460 15450 13020 15580 13800 10520 11760 14120 15460 16850 5140 6340 10550 11780 11210 12020 12620 16120 14950 14810 11960 15050 15400
Appendix I - p.3
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Pepper 4200 3240 3520
Potato 2960 6640 6920
Sorghum 4450 5230 7550
Soybean Sugarbeet
5300
6960
6870
8190
5520
5710
Sugarcane Sunflower
12740
6300
11640
6040
23310
9100
Tobacco 5790 5730 5280
Tomato Vegetable
7640
4040
7700
4900
8350
4230
3690 5740 4570 4050 3130 5790 3130 3130 3120
4130 6880 5630 5290 3290 4680 3290 3290 4740
3260 5030 4070 4210 2600 4880 2600 2600 3830
4230 6660 5400 6020 3400 5810 3400 3400 3780
4850 8960 7530 6700 3990 5780 3990 3990 6550
11620 21000 17970 12850 12830 18520 12830 12830 14160
3710 6800 5770 3770 2990 5550 2990 2990 5050
3550 5710 4660 4090 2830 5350 2830 2830 3420
4610 8600 7280 4490 3740 6330 3740 3740 6320
3160 5480 4600 2430 2450 4490 2450 2450 3760
3420 4680 3130 3110 3370 4940 2250
3520 4070 3290 2610 5230 4230 4360
3270 3000 2600 2670 4280 3880 2890
5210 3970 3400 3450 5660 5730 2570
5270 5360 3990 3970 6930 6640 6180
13450 12930 12830 6670 17490 15540 11950
4030 3980 2990 2990 5370 4210 4730
4280 3440 2830 2840 4860 4620 4030
4830 5050 3740 3740 6810 6330 5860
3360 4560 2450 2440 3280 3550 3110
3520 3110 6570 3300 4400
4000 2610 4260 5750 4980
3150 2670 3010 6530 3920
4330 3450 6290 4570 5330
4980 3970 7770 5640 6170
12070 6670 17270 21130 14250
3280 2990 3360 8100 4120
3520 2840 5380 4340 4210
4080 3740 5940 6990 5120
2480 2440 5230 3460 3160
3130 3520 4360 3790 3830 3880 3410 3130 5090 4630 4820 7850 4610 4070 3790 5830 4310
3290 6920 5400 4650 3780 3570 7000 3290 6000 5650 5050 6880 5410 4320 3940 4690 3780
2600 7550 3830 2920 2950 3060 5140 2600 4900 4180 3980 6540 4290 4450 3090 3490 3050
3400 5520 4430 5460 3780 4400 4340 3400 5830 5550 5190 9500 5740 5580 4020 5840 4650
3990 5710 5340 4710 4580 5140 4530 3990 6770 7570 6040 10880 6640 6530 4790 7100 5510
12830 23310 16240 14300 13320 12470 18070 12830 18780 18190 14500 22930 13830 9870 12690 17120 13400
2990 9100 4560 3490 3590 3380 6200 2990 5580 5830 4550 7010 4330 4730 3550 3940 3390
2830 5280 3610 4470 3360 3560 3000 2830 4640 4810 4280 7590 3740 4650 3240 4900 3810
3740 8350 5030 4350 4620 4860 5450 3740 6830 7370 5690 10680 5250 6220 4510 5930 4970
2450 4230 3620 2890 3080 2850 2950 2450 3860 4720 3770 5440 3120 3710 2920 4600 3270
2380 4920 2590 4240 6000 3130 3130 5200 4470 3730 4570 5060 4110 3130 5170 1730 3130 3130 3970 3470 5680 3130 3130 4920 3240 4400 3990 2380 4510 5020
3580 4200 5500 5350 6300 3290 3290 7280 5410 4060 4730 4910 3860 3290 5410 2400 3290 3290 4210 3250 6010 3290 3290 4200 6640 4920 3580 3880 4690
2980 3560 4340 3950 4950 2600 2600 5810 4100 3190 4790 4550 3280 2600 4840 2470 2600 2600 3290 2710 5940 2600 2600 3560 5230 3570 2980 3640 4490
2790 5460 5600 5250 6150 3400 3400 5620 5440 4280 7790 5980 4630 3400 6250 2780 3400 3400 4500 3860 7500 3400 3400 5460 6870 4730 4730 2790 5420 6240
3320 6430 6720 7290 7790 3990 3990 6620 7250 5000 7580 6230 5420 3990 7150 3060 3990 3990 5250 4530 8340 3990 3990 6430 8190 6500 3320 6220 7080
8600 15150 10920 17240 14790 12830 12830 22320 17540 12570 21420 17210 13230 12830 18090 5660 12830 12830 14890 11200 20220 12830 12830 15150 11640 12000 15650 8600 14160 16540
3530 3910 4940 5670 5700 2990 2990 6930 5600 3490 7380 4770 3640 2990 5320 2420 2990 2990 3710 3050 6390 2990 2990 3910 6040 4980 3530 3900 4820
3000 4460 4730 4630 5390 2830 2830 4430 4730 3440 6110 4990 3760 2830 4940 1910 2830 2830 4390 3130 5830 2830 2830 4460 5730 4110 3000 4350 4950
4280 5890 6300 7160 7330 3740 3740 6940 7080 4380 5890 6110 5100 3740 7280 3550 3740 3740 4740 4240 9000 3740 3740 5890 7700 6290 4280 6030 7140
2620 3640 4070 4630 4630 2450 2450 4350 4610 2760 5170 4320 3000 2450 3720 960 2450 2450 3060 2680 3670 2450 2450 3640 4900 4020 2620 3130 3420
Appendix I - p.4
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Pepper 3600 3730 2380 3130 3130 4720 5150 6170 2310 3130 6170 2590 4330 2790 2100 4140 2600 5430
Potato 3740 4870 3580 3290 3290 4920 5170 4780 5590 3290 4780 5500 5500 2410 4050 4680 2610 3940
Sorghum 2920 3260 2980 2600 2600 5030 4030 3450 7840 2600 3450 4340 3860 2500 4670 3420 3470
Soybean Sugarbeet
3980
4670
4340
6440
2790
3320
3400
3990
3400
3990
6910
8250
4890
6180
5820
6380
3690
5460
3400
3990
5820
6380
5600
6720
5130
7330
4580
5260
3140
3680
5400
5450
3400
3990
6000
7070
Sugarcane Sunflower
13740
3370
15040
4890
8600
3530
12830
2990
12830
2990
20300
6490
16480
4440
24710
9270
23840 10210
12830
2990
24710
9270
10920
4940
17320
5610
10100
4130
14640
5770
15170
4080
2990
15400
3890
Tobacco 4080 3780 3000 2830 2830 6870 3980 7000 3900 2830 7000 4730 4470 3940 3030 4420 4120 4950
Tomato Vegetable
4320
2830
6160
3810
4280
2620
3740
2450
3740
2450
7470
5460
5830
3620
8700
4400
7130
2880
3740
2450
8700
4400
6300
4070
7080
4450
5270
2810
4940
2400
5040
3380
6200
6250
3920
2360
2300
3460
4270
5610
10600
4480
3550
5060
3790
3350 3580 3130 2010 5230 4100 2700 3130 3130 3410 6040 3300 4630 4220 4720 6950 4310 6920 5400 4250
7550 3860 3290 3360 2600 3900 5200 3290 3290 2480 5850 4790 3670 4480 5350 5750 4200 4890 9070 3250 4260
8070 3080 2600 3860 2680 3280 5720 2600 2600 3660 4170 3630 2540 3580 3740 5730 3870 6890 2600 3620
5400 4740 3400 2680 4810 4600 4130 3400 3400 3830 5950 4180 4430 5110 5700 8610 5110 8940 5440 4550
6760 4900 3990 3470 6080 5390 4470 3990 3990 5720 7270 4370 5470 5640 5900 9790 6370 7980 6620 4700
27860 13180 12830 12750 12130 13360 17810 12830 12830 12010 19500 12380 13460 15020 16470 21490 15672 16050 24430 13760 12300
12150 3680 2990 4840 3480 3650 6940 2990 2990 4350 4860 4340 3200 4190 4350 6050 5670 4870 7290 2960 3980
7000 5460 3890 2830 2530 4250 3730 3950 2830 2830 3150 4950 3360 3740 4180 4680 6880 4370 7580 4620 3840
9410 4530 3740 4090 4110 5100 6280 3740 3740 5290 6270 3900 4390 5240 5490 9630 6180 10290 5210 5270
4170 3050 2450 2020 4190 3050 3160 2450 2450 3620 4960 2560 3800 3460 3590 4630 4090 6590 4060 3510
3130 5350 2570 5150 3830 6770
3290 3200 6400 4110 3550 3780 4330
2600 4730 4000 2590 2950 3000
3400 6270 3560 5030 3780 6370
3990 8550 3570 6170 4580 7930
12830 20580 13270 13960 13320 17490
2990 6580 4720 3020 3590 3380
2830 5440 3240 4270 3360 5500
3740 8320 4850 4870 4620 6090
2450 5330 2680 4070 3080 5360
3320 3130
3100 3290
3930 2600
6490 3400
6490 3990
15050 12830
5160 2990
5370 2830
5850 3740
4350 2450
4050 5080 6950 8130
5290 4900 5750 5560
4210 5000 5730 5620
6020 6590 8610 9130
6700 6580 9790 11160
12850 18050 21490 22830
3770 5250 6050 5810
4090 5660 6880 7870
4490 6740 9630 10360
2430 4990 4630 5490
3400 4880 4360 5940
3990 6810 2640 6130
7000 5990 6300 4830
2990 6300 8140 5870
2830 6440 10230 7200
4580 20790 19660 16670
2450 6810 8180 5620
2990 5520 6540 3540
3740 7900 9330 6960
4680 6920 4500
4110 5400 4210 3780 3130 4220 3300 3900 3940 3130 3130 4490
4380 6720 4640 3840 3290 4440 5750 5010 7240 3290 3290 5000
3190 5330 3640 3680 2600 3500 6530 3380 8210 2600 2600 3790
4240 7550 4690 5290 3400 4590 4570 4490 5720 3400 3400 4760
4950 8480 5810 5870 3990 5400 5640 6560 6640 3990 3990 5670
13630 18060 15340 14600 12830 8680 21130 15470 29090 12830 12830 15770
3590 5020 3940 4460 2990 4030 8100 4960 10090 2990 2990 5810 4400
3450 5620 4570 4340 2830 3820 4340 3890 5460 2830 2830 3880
4650 6110 4970 5400 3740 5060 6990 6250 8810 3740 3740 5330
2950 3460 3130 3720 2450 3300 3460 3870 4350 2450 2450 3530
Appendix I - p.5
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Pepper Potato Sorghum Soybean Sugarbeet Sugarcane Sunflower Tobacco Tomato Vegetable
5420 4100 5230 4100 4220 4230
4820 3900 5680 3900 4480 4480 4480
4680 3280 4410 3280 3580 3460
6910 4600 5610 4600 5110 4820
6900 5390 6660 5390 5640 5420
5790 3960 6600 3890 6370 4350 3130 3130 5420 2130 5430 4210 5200 4700 4240 4160 1470 4210 5430 5800 5420 3130 3130 4050 4500 3790 3830 3760 4550 3460 4020 4810 4220 5240 6630
4680 4140 6930 3900 8910 4510 3290 3290 4820 5630 3940 3000 5310 3900 5350 4630 3200 4390 3940 4520 4820 3290 3290 5290 5730 3940 3780 4300 5710 5200 5300 5070 3790 5250 3970
4880 3280 5460 3520 8110 3520 2600 2600 4680 8100 3470 2450 4120 3460 3950 3760 4200 5160 3470 3950 4680 2600 2600 4210 4550 3090 2950 3090 4000 5130 4720 4010 3120 3380 2890
5810 4230 5100 4900 8150 5030 3400 3400 6910 3590 6000 4550 6330 5330 5250 4870 2260 5210 6000 6430 6910 3400 3400 6020 6430 4020 3780 5040 5300 4550 4960 5240 4620 4840 6420
5780 4660 8450 5560 8820 5550 3990 3990 6900 5380 7070 5410 6990 6230 7290 6000 3030 5330 7070 7570 6900 3990 3990 6700 7210 4790 4580 4950 7600 5090 5430 6160 5450 6030 7910
18270 13360 18150 13360 15020 14620 13564
6360 3650 5080 3650 4190 3980
6120 3730 4560 3730 4180 3940
7020 5100 6290 5100 5240 5060
4630 3050 4200 3050 3460 3280
18520 12170 15790 14110 27190 15700 12830 12830 18270 24320 15400 11350 17390 14320 17240 15340 12850 12030 15400 16960 18270 12830 12830 12850 14260 12690 13320 13910 17990 17430 16990 9200 13310 17220 16800
5550 3700 6270 4170 9430 4080 2990 2990 6360 10610 3890 2640 5540 3760 5670 4590 5370 5450 3890 4290 6360 2990 2990 3770 4190 3550 3590 3700 5810 6130 5480 4610 3460 4040 3170
5350 3680 5920 4010 7190 4440 2830 2830 6120 3870 4950 3800 5150 4340 4630 4250 2290 5650 4950 5290 6120 2830 2830 4090 4410 3240 3360 4120 4590 4100 4300 4370 3770 4050 5510
6330 4540 7910 5150 10400 5190 3740 3740 7020 7210 6250 4600 5950 5770 7160 5840 4020 5970 6250 6790 7020 3740 3740 4490 5030 4510 4620 4570 7320 6150 6170 5770 5000 5010 6470
4490 3390 5140 3450 6060 3390 2450 2450 4630 2810 3920 3020 4600 3400 4630 3930 1740 3950 3920 4180 4630 2450 2450 2430 2780 2920 3080 3060 4570 3400 3660 3770 3180 4580 5150
Appendix I - p.6
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melon 5600 6130 6250
Wheat Cotton seed
4350
7410
8010
5900
6060
Cabbage 2700 2930
Carrots
Cauliflower Cucumber Lettuce 3000
Oats Onion green
3660 6630 5600 4670 2990 5750 2990 2990 4910
3540 5480 4440 3030 3740 4730 3740 3740 3120
5470 8960 7180 5110 8710 3880 4970
3240 1180 3740 3020 3200 1600 1800 2780
6730 6730 3760
6100 6100 3410
4360 5010 3000 4600 4860
4150 4150 2300 3120
5740 5740 3220
5330 5330 2980 3200
3980 3880 2990 3000 5150 4960 4660
4260 4660 3740 3540 3270 4560 2470
6360 7380 5290 6840 4330
3660 1960 1800 2790 3500 2550
3760 3760
3410
3000 3000
2300
2220 3220
2980 2980 4440
3770 3000 5440 5190 4530
2920 3540 3830 4890 3320
6090 5940 5680 6660
3200 1800 5150 2540 4000
6120
3670 3000
3190
3220
5400
4410
3850
5040
4840
2990 6250 3830 3470 3450 3810 3420 2990 5040 5640 4490 8230 4240 4990 3430 5060 4030
3740 5900 3800 4260 3440 3520 4620 3740 5180 4570 4250 7770 3720 4040 3310 4070 3520
6060 7400 6290 5480 5500 9710 4872 8920 7300 6590 11280 7660 6780 5670 6670 5620
1960 2930 3960 3200 2860 3660 1642 4080 3760 3870 5270 3440 2250 2940 4640 3320
4220 3180 4560 4660
3000
2300
4720
5280
4110
5790
5090 4640 4910
3980 4410 3390
3730 3440 2860
5450 5470 3760
2980 4450 4860 4610 3600
3280 4730 5020 5450 5780 2990 2990 4850 5400 3680 6740 4580 4000 2990 5410 2170 2990 2990 4490 3340 6500 2990 2990 4730 6130 4830 3280 4690 5400
2300 4180 6540 4340 8400 3740 3740 5530 4480 3170 6380 4910 3690 3740 5450 1240 3740 3740 3470 3060 6810 3740 3740 4180 8010 3900 2300 4350 5250
4280 6440 6770 11020 7080 6000 11430 7900 5900 3880 8520 3730 6680 4910 10070 5600 3880 6440 10168 6280 4280 6310 7710
2470 3620 2790 3460 3960 2020 1720 4980 3610 3130 4580 3790 2970 3800 1760 1800 1960 3970 2610 3670 1960 1940 3620 3100 3290 3800 2300 3060 3360
3410 3410 3760 3760 3860 3760 3600 3600 5510 5080
2670 3410 3410 3410
3540 3000 5620 3000 3000
2160 2300 4430 2300 2300
2590 3220 3220 3220
4250
3600 3600 5790 3000
3100 4200
6240 5290 3220
4540 4540
3790 3790
3110 3110
3510 3510
4540 6150
3790 5670
3110 3550
3510 3510 6500
5460
4200
3830
4020
2590 2980 5040 2980 2980 3890 5570 3450 3450 3450 5010 5760
Appendix I - p.7
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
W.melon 4120 4780 3280 2990 2990 6390 4410 6860 5110 2990 6860 5020 5450 4170 3660 4040 5190
Wheat Cotton seed
3180
6000
3570
5840
2300
4280
3740
3740
6910
9190
3950
7080
6100
13080
4780
4590
3740
6100
11920
6540
8752
4220
6810
3760
6510
3450
3690
4330
6930
6440
3880
4310
6210
Cabbage 3690 3150 1960 3660 4080 3210 1560 1960 4200 2800 3600 2700 1650 1800 3770
Carrots Cauliflower Cucumber
3600 6160 4220 4680 6380 5450 4470 5820 4220
4540 5090 5600 6260 4720 5770 4860 5990
4570 3790 6120 4390 8000 3790 6250 4720 5480 3990 5350 5200
Lettuce 3570 3110 6010 3530 3920 3110 2540 3870 4630 3310 4450
Oats Onion green
3510 6570 4910 3510 5010 5720 5600
4620 3450 4400 4980 5780 4330 3450 4210 4300 5670 4230 5580 3450 5100
4400
3820
7020
3672
4590
4230
3580
4910
4590
6860 3640 2990 3030 4160 3980 4700 2990 2990 4390 5150 3410 3840 4150 4320 7450 4710 8080 4700 3930
6440 3840 3740 2850 3490 3710 4430 3740 3740 3380 4490 3320 2970 4150 4550 6950 4200 7650 3370 4030
6250 6210 3470 3490 5920 4660 6620 8080 6760 5020 6930 7350 9730 6770 10440 4860 6270
2530 1800 1720 1520 3950 3060 2200 1960 1960 5150 2400 3890 3878 4390 3430 6030 3830 3280
4220 6110 3600 5480 4220
4960
4600
3670
3220
4720
3000 3000 5230
3940
3510
5240
4200
3700
4790
2590
5200
6780
2440 4110
5790
3450 3450 4760 6630 3450 3450 6030 4460 3190 5550
2990 6360 3690 4350 3450 5510
3740 6460 5160 3480 3200 3440 3750
8270 4210 5020 5480 5970
1960 4270 4020 3200 5210
4720
3000
4350 4030
3800
3450 4450 3780
5080 2990
5440 3740
8730 5600
1960
3600
3410
3000
2300
3220
2980
4670 4910 7450 8300
3030 5450 6950 7220
5110 8180 9730 9540
2600 3020 5080
6730
6100
4360
4150
5740 5120
5330 4480 8940 5130
6090 7240 3950
3672 5760 7040 5160
7660 10500 7290
1960 4070 4320
6130
5570 5460
6200
2300
4840
3780 6550 8650
3570 6220 4770 4410 2990 4040 5190 4850 6550 2990 2990 4110
3410 4200 3600 4370 3740 5200 4890 3690 6170 3740 3740 3960
5860 9910 7300 7410 6790 5680 6090 6790 7130
5150 4140 1960 2230 3300 3110 1960 1960 3730
3760 4710
4720 4650
3000 3830
3760 3150
3790 3220 3510 3980
3000 3600
2300
3510 3510
3570 4410 4630 2980 3850 2980 3570
Appendix I - p.8
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
W.melon Wheat Cotton seed Cabbage Carrots Cauliflower Cucumber Lettuce
6450 3980 4850 3980 4150 3950
5650 3710 4660 3710 4150 3890
5750 3650 6270 4130 7980 4540 2990 2990 6450 5140 5190 3940 5280 4610 5450 4430 2910 5880 5190 5560 6450 2990 2990 4670 5000 3430 3450 3670 5650 4670 4740 4620 4000 4190 5560
4730 3450 8730 4020 7540 3830 3740 3740 5650 4810 4310 3100 5140 4110 4340 4090 2730 4270 4310 4740 5650 3740 3740 3030 3430 3310 3440 4020 4360 4400 4480 5730 3580 3560 3800
8830 5920 8210 5920 6930 6560 8710 5090 6830 10140 6920 8830 4390 6210 4400 8010 6140 6770 6540 2750 8720 6210 7070 8830 6210 5110 8640 5670 5480 6350 7110 5630 6310 5690 6860 5640
3650 4240 3060 4026 1960 1960 4560 3440 3950 5210 4010 1960 3650 1960 2840 3690 3320 3460 2260 2150 2080 4010 2660 3650 1960 2100 4050 2430 3030 3200 3760 2800 3270 2390 3210 4950 4990
5400 5320 3670 3760 5960 4390 3670 4150 3670 6020 4140 3670 5400 3670 4220 3670 5410 5080 5060 5570
5120
6200
5290 5840
4850 4720
3000
3410
3040 4120
5990 4210
3860 4960 3570
4720 4410
3000 4150
2300 4030
5080 5940 6200 4720 5390
5110 4900 5490 4200 5280 5490 3000 5280 4600
4580 3430 2640 3110 4110
5240
4030
3620
3920
Oats Onion green
4570
4410 3510
4200 2980
5100 6770 3510 5570 5610 6260 3510 3510 6370 6110 4400
4460 6350 4350 6240 2980 4620 2980 3950 4550 4870 5220 5380 2980 5340 2980 5600 3450 4450 3450 2980 4280 3780
4160
5410 4200 4000
Appendix I - p.9
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium-Luxembourg Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bahrain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Onion dry
Peas
Safflower Spinach Sweet potato Artichoke
Citrus 8660 14490
Rice 5900
6620 6620 3970
4490 4490 2730
5970 5970 3370
3700 2330
3970
3670 2730 2730 3600
3370
2330
6430 6430 3500
10850 4680
7780 3000 11180 7680 7680 9400
5480 3500
4680
11630 4910 8550 10380 7870
8600 6200 8600 5900 5900 6700 8200 8950 5900 5900 6780 7200 6570
2730
6530
4100
5760
7670 4910 11420 13020 9400
6800 7600
3970
2730
5900
10300
5920
3000 3400
6120
3280
6670 5580
4020 4170 4020 3430
5490 5680
3900
4960
11370 9370 10940
8260 11190 12190 2570 9570 16780 8390 7360 8230 11220 8840
8200 6200 7340 6800 7200
3350 3970 3970 3970 5260 6720 6800
3000 2730 5180 2730 3780 3780 4210 5420 4020 3780 4020
3370 3370 3370 6800
2330 4400 2330 2330
5590 5590
3780 3780
4680 4680
3610 3610
5590 8190
4020 3780 5550
4680 6820
3610 4710
3370
5680
3500 3500 3500 6940 6810 4370 4370 4370 5090
4680 4680 4680 10710 13800 7490 7490 7490 11040
8770 11500 9740 14040 11660 8050 13650 11390 8740 11960 3320 4250 9820 7380 13580 4250 10060 8370 10230 11940 9530 11120
7340 8450 5900 5900 5900 6870 9600 8200 5900 5900 5900 6250 9600 5900 5900 9200 7820 9120 7650
Appendix I - p.10
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Onion dry 5590
Peas Safflower Spinach Sweet potato Artichoke
4130 3780
4680
3610
4370
7490
Citrus 9130 9920 8260
Rice 8820 7920 6200
6400
6020 3680 8210
8080 4850
3190
7100 5670
18410
13600 12400 16300
9880 9300 10210
5590 5170 6760 5710
3780 8120 4190 3560 5420
9200 5640
3870 4260 3210
5620 4030 6820 5050
9550
14800 7360 11460 7060 9010
5900 12000 6400 7600 8210
3970
4570
3760
3570
13920 10370
6200 9230
6190
3860
3520
6880
6570
3970
3960
3970
4020 3780 3780
17640 7600
5860
10290
7820 8120 8810 11080
6200 8720 5900 5900 5900 5900
7030 6220
4170 4570 3900
3320
5450
12560 7710 8760 10100
11200 8900
6000
4020 4800
6200
3260
10700
14610 10620 16330 9250 10230
7450 6410 7980
3790
5140
4200 5670 3670
3370 4810
3000
13640 8450 9230 11560
12000 7620 8720
3970
2730
3370
2930
3500
4680
3910
9800 5900
6620 8920
4490 5500 5490
5970
6430 6300
7680 12170 15680
10420 12300 12600
2730 6040
13440 9530
5900 11670 10970 7620
5490 4970 3970 5450
4180 3790 4300
7580 4550
3120
3970 3970
2730 3790
3370
6180 5860 3500 4860
11110 9960 5870 10180 16000 10160
7840 8230 8720 5900 6800 5900 5900
Appendix I - p.11
Appendix I. Crop water requirements (m3/ha). Source: CropWat model (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Onion dry 5740 3970 6570 8710 3970 7120 3970 7140 7100 7910 7120 3790 4630 3970 5140 5220
Peas Safflower Spinach Sweet potato Artichoke Citrus
5640 6140
4600 3790
4520
4010 5330 6200
5210 4200 6690
4830
3790 8410 3270 4640
3370 5080
3840
3850 4800 4860
6640
4500 3780 6200 3790 4750 4770
6070 6800
2680 3620
3770 3670
4810
3490 4370 4490
16480
12400 11740
9570
5630 4600 5320
11060 13790
11750 8330 10520 18220 10340
5860 5300 6130
18830 10170
14410 7670 11400 9570 10170 7740 8610
11360
6860
4910 7260 8560
8830 9270 11870
11000 10900 10520 8780 10940 11210
Rice 11600 10600 8720 5900 5900 7260 8350 7600 12600 8900 5900 12000 6200 6800 9600 7230 9200 7200 7680 9850 6200 9340 5900 8600 7680 6200 7680 8720 8670 8960 9000 10340
Appendix I - p.12
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Banana 3.2 2.5 9.7
Barley 1.2 1.8 0.9
Bean dry 1.1 0.5
Bean green 1.2 3.7
Grapes Groundnut
6.9
13.9
0.6
3.9
1.1
0.4
0.3
Maize 1.5 3.7 2.2 0.6
Mango
Millet
Palm
0.8
0.5
11.4
11.0
2.6
2.3
1.6
1.3
2.5
19.7
1.9
0.9
4.7
1.3
1.0
2.7
2.2
0.9
9.3
14.3
0.6
0.7
5.6
1.5
0.9
24.0
7.4
3.4
18.8
1.0
5.2
0.7
16.5
1.0
1.0
11.2
0.6
1.0
2.6
2.0
3.6
7.0
11.8
7.3
5.1
13.3
12.3
7.6
3.4
3.2
2.6
4.7
4.3
16.6
18.9
7.2
4.0
7.6
4.0
3.6
1.7
5.7
1.5
5.2
9.0
4.0
1.6
5.3
4.4
0.9
9.6
3.6
2.2
1.1
1.0
3.7
2.3
2.5
1.0
2.6
1.0
12.2
2.1
5.9
0.8
1.1
5.2
4.1
1.6
1.1
2.2
9.4
3.9
0.5
0.3
1.5
1.0
11.2
1.6
11.4
0.6
0.7
1.6
14.1
0.7
8.7
0.9
0.2
16.0
2.3
0.7
4.3
2.6
0.8
5.1
1.0
15.8
1.8
2.8
7.4
9.9
3.3
3.3
1.0
3.8
1.4
1.0
1.4
5.0
0.7
0.8
1.1
1.1
11.2
4.6
0.4
0.8
1.6
1.3
14.4
0.9
7.3
9.0
0.6
1.9
6.9
1.1
2.2
12.0
3.2
2.0
3.0
1.3
6.5
0.6
12.0
3.7
1.6
2.8
2.5
1.4
31.2
2.2
1.3
5.9
3.7
0.6
0.5
1.4
0.8
3.3
54.0
0.5
14.7
2.9
3.4
11.7
0.4
43.5
2.1
1.5
3.9
1.3
5.2
1.3
1.0
1.7
12.3
0.8
33.2
0.7
0.5
37.5
2.1
2.6
1.8
0.9
4.5
1.2
2.2
15.9
0.9
0.8
6.2
1.4
1.0
6.3
11.4
11.2
12.4
12.9
6.3
6.3
7.0
7.0
5.8
7.2
7.0
14.0
5.9
5.0
6.4
8.0
6.0
12.0
6.2
12.0
1.5
4.0
12.5
19.2
2.9
11.0
3.3
4.6
4.0
3.0
8.3
0.3
45.0
1.1
1.6
4.8
1.0
0.7
4.9
2.0
8.5
3.0
4.9
12.5
1.4
1.8
12.7
1.0
2.4
0.8
0.8
16.8
1.1
0.7
27.0
1.2
1.9
1.4
1.0
0.8
1.5
1.1
5.6
1.0
2.9
34.3
4.0
4.1
1.1
6.6
1.1
12.0
1.6
1.4
1.0
1.2
1.2
7.8
0.7
1.3
1.5
3.5
8.9
9.8
1.0
2.5
6.7
1.1
12.0
1.3
1.7
1.2
16.7
1.0
8.0
0.4
1.7
14.7
19.2
0.6
5.0
12.5
16.9
0.6
9.6
3.6
2.0 1.6
15.1 1.6 0.9 15.0 1.0 0.8 0.9
7.6
2.6
6.2
2.3
6.2
6.4
0.6
1.8
0.9
6.2
1.3
3.0
2.0
2.5
2.7
4.0
1.0
24.5
29.3
0.9
0.7
3.8
9.5
2.3
7.2
11.2
9.3
11.1
5.2
3.5
1.7
16.4
8.5
8.2
9.3
11.1
2.9
3.0
1.0
2.5
12.0
4.1
1.1
9.0
0.8
3.8
1.0
1.7
1.1
1.5
4.7
0.3
2.2
1.1
6.7
1.3
1.4
8.0
2.9
9.3
1.0
1.0
0.7
0.9
1.8
1.3
1.4
1.8
1.2
1.0
6.4
0.8
11.4
8.0
0.9
1.0
11.4
0.9
8.8
8.8
21.3
0.8
2.7
0.9
8.6
Appendix II - p.1
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 6.8 6.4 38.6
Barley Bean dry Bean green
0.7
2.9
0.5
2.9
3.1
1.3
8.4
Grapes Groundnut
0.9 0.9
6.0
1.0
5.8
0.9
Maize 1.2 0.8 1.2 6.4
Mango 6.3 7.3 6.7
Millet 1.4
Palm 21.4 14.1
31.2
1.9
0.4
12.5
1.7
26.1
1.4
1.6
0.5
1.0
6.7
4.6
51.8
1.5
26.7
3.8
2.0
8.1
1.2
4.4
4.0
1.8
21.6
0.7
2.7
23.5
5.9
7.5
2.3
8.9
2.3
5.9
1.0
7.0
9.0
16.3
8.8
1.7
7.9
7.0
11.8
9.6
2.8
0.8
1.7
12.3
1.8
2.7
5.1
2.3
6.2
8.8
3.8
1.9
12.0
6.9
12.6
11.2
1.1
9.7
1.2
1.2
7.5
2.3
2.4
11.9
0.7
11.4
16.9
0.8
11.4
0.6
11.4
11.4
11.4
1.0
11.4
1.3
0.9
7.1
2.9
1.6
3.2
0.4
5.5
2.4
2.8
6.2
0.6
1.5
5.4
0.6
5.2
4.2
2.0
0.8
9.0
13.3
2.0
2.5
1.0
4.4
1.9
13.3
1.8
3.9
1.0
2.5
15.7
0.6
23.0
2.0
8.1
2.5
1.0
5.3
11.0
0.9
1.3
2.4
8.3
1.6
1.4
4.3
25.7
2.4
2.4
1.6
9.9
2.9
2.3
0.3
0.8
0.9
1.6
0.6
1.7
0.5
3.0
5.0
1.7
2.0
1.2
1.8
1.0
8.0
4.4
1.1
12.0
0.9
2.5
3.0
0.9
8.5
4.4
0.9
5.9
0.9
3.3
5.3
0.7
0.9
11.4
12.2
5.1
0.5
17.6
1.6
0.6
2.5
6.0
0.6
3.4
2.3
28.7
0.9
19.9
24.4
2.2
0.6
5.2
1.7
0.8
0.7
4.5
32.0
0.7
0.6
6.5
1.2
0.7
6.0
7.0
6.0 5.8 1.0
3.5
10.0
6.5
12.4
3.0
3.2
11.9
7.1
6.3
0.9
1.8
5.6
3.6
2.1
4.8
1.0
1.7
5.0
4.4
0.8
0.6
2.1
4.5
1.5
2.6
9.4
1.2
2.8
3.3
1.9
6.7
1.9
0.4
0.6
1.8
7.3
1.1
1.7
0.6
0.5
0.5 19.8 2.5 0.8
0.4
8.8
0.7
8.3
0.5
1.3
0.6
0.7
11.4
0.2
1.0
0.6
6.3
2.9
2.0
5.7
1.3
44.0
0.7
7.0
1.0
0.7
2.0
3.5
0.6
14.0
0.8
0.6
3.6
1.2
0.5
39.5
0.5
0.4
14.3
20.0
1.5
0.7
22.0
1.2
0.9
2.0
0.9
3.7
1.9
29.2
1.3
0.5
21.1
0.6
20.0
3.0
8.3
0.7
23.0
2.5
1.6
23.0
1.4
0.8
0.6
1.0
8.7
6.7
7.6
9.1
3.0
7.0
9.0
7.8
7.0
7.9
8.4
6.0
6.8
6.7
1.8
3.0
17.8
2.8
9.5
2.8
4.4
2.0
4.3
8.4
4.4
3.2
1.4
1.0
4.4
4.4
4.3
1.7
1.1
7.1
4.2
1.1
1.1
3.0
1.2
0.4
1.3
1.5
1.4
6.0
1.1
12.0
1.8
4.0
2.7
0.8
1.5
9.9
1.1
1.6
6.7
0.8
5.4
0.9
2.3
7.5
1.8
2.4
17.6
0.9
1.7
6.2
1.3
5.8
2.5
5.3
4.0
2.9
12.5
0.9
6.8
12.5
3.6
1.1
2.0
0.6
0.8
0.9
7.5
1.1
0.8
11.4
11.4
26.5
0.4
10.5
1.6
2.7
0.5 9.6 14.8 9.6 26.0 12.5
0.8
0.9
11.4
0.8
Appendix II - p.2
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Banana 1.0 4.5 6.9 17.2 4.9 25.0 22.0 21.3 2.9 16.1 15.4 44.7 33.0 33.9 21.4 4.2 22.0 4.1 8.4 12.8 1.7 1.5 5.1 26.9
Barley Bean dry Bean green
4.7
3.0
0.6
7.9
1.7
3.0
3.0
3.0
1.5
3.4
3.2
2.5
0.3
0.9
1.2
5.0
2.4
1.1
12.9
0.5
4.8
1.9
5.0
1.6
1.2
3.8
1.8
5.3
8.7
0.4
1.6
8.2
0.9
7.0
2.3
0.8
7.0
0.7
0.8
4.0
0.3
0.9
0.5
6.8
1.9
1.4
8.3
0.4
Grapes Groundnut 1.0
13.7
4.0
1.7
0.8
7.5
1.6
3.5
1.1
6.6
0.7
13.5
1.7
4.7
2.3
7.9
0.6
11.0
0.7
1.4
1.4
11.2
1.1
11.2
5.5
2.7
1.2
1.1
5.2
0.6
16.5
1.5
0.5
0.5
5.4
1.1
6.3
2.6
5.8
Maize 3.3 2.1 1.6 0.9
Mango 5.7 8.4 6.8
1.2
1.6
8.0
6.0
6.9
0.7
7.2
2.2
11.4
9.5
1.9
3.3
0.6
2.5
2.3
1.8
9.2
9.2
3.2
3.5
1.4
1.2
3.4
1.0
2.0
2.9
6.6
3.7 0.8
Millet 2.0 0.6 1.0 0.9 1.9 1.5 0.6 2.4 0.7 0.3 0.6 1.0 0.9 0.4 1.7
Palm 12.8 1.0 8.3 16.5 16.0 10.5 14.1 10.5 2.8 13.8 17.6 8.8 12.4
4.6
0.4
1.8
2.0
8.0
0.6
5.6
1.3
17.7
3.2
2.0
21.0
2.2
0.6
0.8
11.9
19.4
1.1
0.8
15.6
0.9
0.7
7.0
2.5
13.2
1.7
13.3
1.7
5.6
15.8
2.9
14.0
3.4
3.0
13.3
5.2
6.2
0.7
1.2
1.1
2.5
4.0
16.9
1.1
8.0
3.0
8.4
4.8
0.5
4.9
1.9
2.2
1.0
0.5
1.8
3.0
15.5
1.3
2.6
7.2
1.6
3.5
0.9
1.0
1.0
14.1
1.9
14.1
1.2
3.5
12.1
0.9
11.4
5.5
6.0
5.7
9.3
1.1
1.5
2.6
1.3
5.7
6.9
1.5
4.1
0.6
4.2
3.6
1.3
4.8
0.6
2.9
1.0
4.8
1.6
0.8
7.1
7.0
0.4
1.4
0.7
10.5
7.1
7.1
0.6
1.6
4.7
0.2
Appendix II - p.3
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Pepper
Potato 16.8 14.2 15.4
Sorghum 0.9 2.7
5.5
Soybean Sugarbeet
14.3
1.7
3.7
Sugarcane Sunflower
19.0
1.4
1.7
0.5
1.0
37.8
0.6
Tobacco 1.9 1.0 1.0
Tomato Vegetables
9.5
3.2
8.6
17.3
6.6
7.8
3.7
7.3
1.2
29.5
4.4
12.9
1.2
32.1
3.2
0.6
3.7
9.5
0.2
14.0
1.2
11.4
1.6
0.6
11.2
0.6
45.1
9.2
0.8
0.3
5.5
0.8
23.7
13.6
6.5
2.1
8.5
0.2
2.4
26.0
2.0
2.0
2.7
68.4
1.3
0.5
21.6
1.2
7.3
0.8
0.7
0.8
0.7
1.3
2.2
7.8
5.7
6.7
1.8
1.7
3.2
12.8
1.0
27.7
18.7
95.9
1.2
2.5
46.1
36.5
12.0
2.6
2.4
43.0
26.1
1.2
18.1
16.6
25.0
1.2
17.8
8.8
28.5
3.5
39.9
0.9
6.9
5.4
58.1
7.6
1.0
22.0
1.9
1.8
14.4
14.3
22.0
1.1
3.4
32.9
4.0
48.2
1.0
6.1
34.5
0.8
5.2
6.6
11.5
1.5
31.2
1.5
2.6
46.4
0.9
0.9
12.4
5.1
0.4
1.6
7.8
4.6
1.8
4.5
3.0
16.4
1.6
0.4
1.9
6.0
0.8
2.4
1.2
2.4
28.0
0.6
17.7
1.0
0.8
68.1
0.8
1.8
5.4
11.6
0.8
73.0
1.3
1.3
15.4
4.9
1.0
0.5
11.3
8.5
64.8
1.0
9.1
6.8
1.8
0.3
2.9
1.4
0.6
27.6
0.7
6.3
1.0
1.4
4.5
7.5
0.6
27.3
2.9
2.8
42.8
1.5
2.8
77.9
25.7
16.7
15.6
20.0
12.5
1.0
27.0
9.0
2.6
1.3
7.3
0.8
8.6
6.2
0.7
95.5
1.4
9.5
1.2
16.5
4.0
1.6
61.9
1.5
2.9
65.5
2.0
1.5
13.9
3.3
1.8
29.2
75.0
2.0
1.8
23.9
17.7
1.2
17.0
3.2
2.5
26.0
94.8
1.8
21.7
9.0
14.4
1.2
9.0
7.0
6.3
0.6
0.5
47.2
0.5
7.4
5.4
8.9
2.0
0.4
7.5
7.0
0.7
5.0
1.0
3.8
22.3
1.2
85.9
1.9
25.9
13.6
0.5
0.3
1.2
67.9
0.5
1.0
8.2
0.5
11.5
4.1
2.5
4.3
1.7
1.5
11.5
7.1
24.7
1.0
12.0
34.1
0.7
4.8
5.0
0.8
23.7
73.0
4.2
11.1
7.0
0.5
19.6
1.5
45.6
73.0
2.2
2.0
17.7
1.9
0.5
39.5
1.6
56.3
1.2
1.9
43.0
23.0
5.8
1.0
1.0
2.0
1.1
1.0
1.2
1.9
2.5
43.7
1.3
36.4
12.9
9.4
1.4
1.8
6.3
67.7
1.5
2.2
9.4
6.7
1.2
21.5
5.8
2.6
47.4
118.5
2.3
1.2
36.9
17.4
5.7
1.3
2.4
68.6
1.8
28.8
13.8
13.0
3.2
22.0
1.2
1.1
44.2
6.8
0.7
7.3
1.3
3.6
115.8
0.7
12.6
2.7
0.9
8.0
3.0
0.5
19.8
0.5
39.0
6.2
1.2
1.0
13.7
0.5
38.9
7.0
0.7
11.5
1.7
1.0
18.2
2.0
1.0
0.6
9.4
1.2
0.7
0.9
34.5
2.7
74.2
1.5
0.6
2.6
56.6
2.0
56.7
1.2
2.8
39.5
0.8
9.3
8.0
73.0
0.9
28.2
25.3
36.0
2.3
2.8
28.2
12.1
7.7
28.8
15.0
58.3
6.6
1.2
4.8
0.7
1.2
1.5
16.7
2.5
2.8
41.6
2.0
25.5
0.6
1.2
63.0
1.5
2.8
44.3
23.8
44.0
8.6
1.0
39.9
16.4
11.5
9.8
2.2
28.3
8.6
51.2
0.9
4.0
27.5
5.1
Appendix II - p.4
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Pepper 0.5 0.5 0.4 0.7 0.8 0.5 1.2 0.5 0.8 1.2 0.5
Potato Sorghum
12.2
0.8
1.0
0.9
21.3
2.3
12.9
18.8
0.8
14.7
1.2
21.3
1.2
14.4
0.3
31.9
4.2
38.7
7.7
24.2
6.4
15.8
3.3
25.9
0.7
Soybean Sugarbeet
2.1
32.0
2.4
44.6
1.1
24.0
1.2
1.6
29.8
1.3
22.4
1.2
5.7
1.2
3.5
46.3
1.7
54.3
Sugarcane Sunflower
65.2 58.8
81.8
1.5
1.2
72.1
0.6
68.9
86.2
0.7
21.3
1.3
1.2
70.0
1.3
2.7
63.2
67.5
1.0
Tobacco 0.9 1.4 0.5 2.0 1.5 0.6 1.1 1.0 1.1 1.0 2.8 1.5 2.6 0.2
Tomato Vegetables
4.2
6.8
15.5
5.7
1.5
1.0
28.4
14.2
41.7
15.7
1.0
7.4
7.5
27.2
16.7
11.4
6.1
7.0
1.4
17.4
53.2
15.7
17.9
1.7
56.5
26.3
36.5
14.9
0.8
1.8
0.6
0.7
3.8
0.8
0.8
7.6
1.0
24.5
1.4
22.3
15.0
0.4
6.6
15.9
1.2
19.8
1.7
1.1
7.8
1.2
0.5
14.1
0.7
12.4
1.3
1.3
17.2
1.2
13.0
1.1 1.3
1.2
2.3
0.9
0.9
29.2
47.5
0.4
0.8
28.4
39.4
0.5
1.7
14.3
15.9
86.7
0.6
2.2
12.4
8.9
14.5
62.0
1.4
7.4
11.9
2.6
48.3
31.9
1.5
64.5
56.9
1.2
2.4
15.8
14.7
36.7
5.4
5.7
70.0
1.2
8.4
22.5
24.4
2.3
1.3
29.5
18.4
6.8
1.2
1.0
5.0
2.3
13.2
11.6
12.0
0.8
1.1
7.6
2.4
1.4
1.3
18.4
15.7
0.4
5.9
0.5
1.2
33.3
0.9
9.2
8.3
0.8
11.0
0.7
0.9
1.0
0.5
0.9
8.8
8.3
1.8
15.0
1.0
22.0
68.9
1.0
0.8
17.5
13.6
15.0
1.0
75.0
0.8
37.3
5.3
2.3
24.0
1.0
65.9
12.5
1.2
62.9
0.7
16.5
12.7
5.0
0.4
63.0
0.8
6.4
0.8
18.5
59.7
1.6
9.5
17.3
1.7
22.3
3.2
1.6
18.0
63.9
0.8
1.9
29.3
7.7
2.5
11.7
1.2
5.0
2.6
0.9
16.6
35.0
1.3
1.2
14.2
1.3
7.4
8.2
3.5
6.7
6.5
1.3
18.3
0.6
1.0
62.0
76.5
0.7
1.0
48.7
17.4
12.5
0.8
18.0
0.6
1.7
8.8
6.2
1.4
0.9
0.8
44.2
0.8
1.7
13.4
0.3
0.8
4.5
7.5
9.2
0.8
36.6
0.9
8.9
2.0
44.9
8.0
1.8
46.0
42.0
1.2
1.0
42.6
39.4
13.7
1.4
1.8
1.2
41.7
1.6
1.5
47.0
23.6
1.0
13.3
1.9
2.2
66.2
1.4
1.8
7.6
1.0
0.2
0.8
23.3
0.8
16.3
8.0
1.1
6.4
1.1
0.7
28.4
0.9
0.4
7.0
6.9
6.7
23.7
26.0
1.2
1.1
32.3
22.9
1.7
21.9
3.0
1.2
16.0
20.0
4.5
22.7
14.4
16.6
0.6
1.2
26.5
47.8
1.3
1.9
2.0
13.8
16.0
2.4
0.8
53.2
1.0
1.6
12.3
12.0
21.9
53.3
19.7
4.2
4.0
53.8
1.2
4.3
16.2
6.0
1.4
2.8
47.0
1.4
1.6
37.5
6.2
1.2
11.3
4.6
1.4
118.8
1.2
24.4
15.0
1.5
12.1
1.2
63.4
1.2
8.6
8.6
2.0
15.7
1.5
33.8
63.0
1.1
2.9
15.4
19.6
2.0
15.7
8.0
2.5
6.6
8.0
0.7
2.6
66.6
18.8
3.8
1.0
12.9
9.3
31.9
1.8
18.0
69.3
1.0
12.2
7.6
14.4
1.5
1.8
21.7
1.2
1.3
16.6
1.8
9.7
1.0
0.8
18.6
34.0
0.8
0.9
12.3
15.3
6.0
0.8
0.5
47.6
1.0
1.3
7.4
14.7
52.8
6.7
0.8
7.1
Appendix II - p.5
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Pepper 0.5 1.7 1.2 1.8 2.0 1.2 2.0 0.6 0.8 2.0 1.5 2.8 1.0 1.8 0.7 1.4 1.2 2.0 2.0 1.6 1.2 1.2 1.2
Potato Sorghum
25.9
1.3
17.1
0.6
0.8
14.0
1.2
14.3
2.4
19.7
0.3
26.6
2.3
24.7
5.0
12.5
0.8
7.3
0.6
2.0
0.6
3.2
35.2
23.2
0.6
13.2
1.0
6.9
0.9
7.8
1.6
0.7
22.0
12.8
0.3
25.9
1.6
5.6
7.2
1.5
8.2
1.2
19.5
4.2
1.2
4.2
4.4
16.4
3.6
13.6
2.6
18.4
2.6
11.8
Soybean Sugarbeet Sugarcane Sunflower Tobacco
25.0
1.2
13.0
3.4
23.0
1.3
19.8
1.1
1.2
12.0
1.5
4.8
43.2
1.3
16.0
2.2
6.5
1.0
1.2
0.9
46.0
3.3
68.0
0.8
45.4
1.4
0.4
1.5
16.0
7.0
0.7
22.0
0.9
0.8
1.3
1.5
16.0
1.7
0.9
35.0
0.3
67.2
1.3
2.1
76.8
0.7
2.6
55.2
1.3
7.1
0.8
5.0
1.2
18.8
1.0
2.8
1.6
55.0
1.8
1.5
2.6
96.8
0.4
0.8
56.7
1.1
1.4
28.0
0.5
1.1
42.6
2.1
43.9
48.4
1.2
40.0
0.6
0.8
32.0
1.5
0.9
2.5
1.2
1.2
15.4
1.5
17.4
2.7
57.8
2.5
49.5
1.9
1.1
11.8
13.3
0.6
1.3
1.0
0.8
63.0
12.6
44.0
0.9
2.0
79.7
1.4
2.2
51.6
1.2
3.3
1.7
1.9
0.8
61.5
1.4
1.9
1.1
5.6
1.9
Tomato Vegetables
7.5
6.7
5.8
24.3
21.8
19.5
18.0
6.1
7.8
9.9
6.3
23.0
17.1
19.9
7.7
27.0
16.4
6.4
31.9
14.2
59.5
21.3
7.5
1.0
12.0
7.8
8.4
15.8
12.5
8.2
32.9
21.0
36.7
23.3
38.7
8.9
19.9
18.0
7.9
6.8
9.1
7.4
4.0
5.0
14.7
1.3
12.6
9.0
37.2
12.5
41.7
15.9
11.6
11.0
7.5
6.5
7.4
13.4
8.3
68.2
25.7
36.6
3.1
48.5
31.8
18.2
8.3
34.0
4.6
15.8
2.6
17.5
12.9
2.0
2.4
1.2
12.7
1.7
1.5
8.2
4.7
2.7
35.2
2.1
12.7
8.9
1.5
1.7
8.3
7.6
0.7
10.0
0.7
2.3
0.9
15.8
0.6
2.1
13.1
0.6
1.9
1.0
6.4
18.3
0.7
2.2
6.7
6.9
Appendix II - p.6
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melon 11.5 15.3
Wheat Cotton seed
1.2
1.1
2.5
1.0
0.8
0.6
Cabbage 9.0
Carrots Cauliflower Cucumber
12
13.7
11.2 13.1783
Lettuce
1.3
1.0
13.9
2.5
21.7
1.9
15.9
2.3
5.4
9.2
1.9
6.5 2.3
1.7 8.3
0.1
5.0
4.0
1.0
15.0
26.3
2.0
22.6
17.1
3.6
30.9
37.3
2.0
46.5
31.4
1.3
13.1
8.3
14.0
20.4
15.2
1.3
10.3
7.5
6.0
17.1
16.5
19.1
45.1
7.6923
11
18.0
50.0 13.3333
9.2 15.60005
22.6
18.0 72.242
27.9
8.40215
23.0
12
10.8 10.0091
19.8
7.6 4.1111
4.9
7.6471
10.3
12.9354
18.1
65
64.6
1.5
1.5
9.6
0.9
15.0
3.1
1.7
0.9
1.2
10.3
9.2
7.4
6.6
2.5
7.2 6.9091
9.6
30
7.6
1.9
2.2
26.0
15.0
11
19.0
12.8
2.7
0.8
1.1
16.9
12.9
1.7
0.9
10.8 15.82375
8.1
27.1
1.3
1.4
1.9
12.9
18.3
2.6
15.0
1.2
21.7
36.6
24.0
24.0
16.3 32.1399
27.5
12.0 15.3333
16.0
2.1
16.4
3.5
26.3
3.9
12.0
2.2
0.5
0.8
27.0
27.0
3.8
20.3
17.8
3.0
4.6
31.9
21.0 23.1579
13.8
22.9 15.83625
21.7
12.9 17.8759
13.8
1.3
0.4
20.8
2.8
4.07145
31.3
6.0
18.5
3.3
56.3
2.6
4.6
7.2
1.0
7.4
10.0
1.1
14.0
9.0
15.6
10.0
36.7
38.0
34.9
20.6
27.7
42.7
10.3
4.5
16.8 6.6323
7.4
2.883
23.4 90.78945
10.0
16.5 11.2232
7.6
9.6 328.5714
25.0
9.8
0.7
29.3
6.3
18.6
2.3
10.0
10.0
14.5
10.0
0.7
9.1
8.0
2.4
29.2
26.2
1.8
8.0
6.1901
10.0
31.25
14.7
5.7 12.7875
7.1
23.4 13.81505
25.9
10
1.3
2.0
11.8
12.8
3.5 32.2937
1.1
1.6
14.6
1.0
2.0
32.8
7.2
19.0
31.6
22.7
42.2
15.1
14.2857
9.2 75.2621
24.0
12.1 116.9438
27.5
21.7353
14.1
2.3
7.5
1.8
42.8
2.3
19.0
25.0
2.0
0.3
7.6
8.3
2.0
51.6
44.4
0.8
2.8
23.5
31.4
0.3
10.0
5.3
9.0
9.0
2.0
11.5
10.0
1.3
1.2
8.54165
26.7 40.76265
24.0
10
19.4 82.1579
18.7
10
7.0
34.49035
19.9
11.5
4.5
16.7
Oats Onion green 1.6 0.8 1.0
2.1
22.0
1.4
2.0
22.0
4.1
20.0
0.8
22.0
1.7
23.0
3.4
9.6
22.0
0.9 2.4
1.1
22.0
1.4
9.1
17.0
2.5
22.0
3.3
22.0
1.9
23.7
1.4
22.0
1.8
22.0
2.6
20.0
1.2
6.2
3.1
20.0
5.1
20.0
0.7
5.1
0.7
12.0
1.2
1.6
1.0
10.0
2.5
20.0
4.4
19.1
0.6
4.8
19.1
0.7
1.9
24.2
1.2
22.0
Appendix II - p.7
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
W.melon 9.7 17.3 13.2 21.3 1.5 22.6 33.8 19.9 33.6 38.1
Wheat Cotton seed
0.4
0.7
2.0
3.6
2.6
0.7
0.8
1.3
1.8
2.0
0.5
1.5
8.8
1.5
3.6
3.2
0.9
3.5 0.2
Cabbage 5.7 6.0 30.8 27.4 34.6 18.3 24.0 18.0 16.2 34.0 29.3 19.4 15.8 39.2 25.7
Carrots Cauliflower Cucumber
11.7
8.0 22.7273
25.9
18.2 23.7472
32.0
12.0 120.40475
14.5
17.3 6.6434
15.9
16.0 8.31485
11.0 19.33925
10.0
11.3
7.55
24.4
9.8 166.6667
73.2
26.0 65.625
48.1
20.9 27.2059
13.9
12.6 14.2105
28.9
10.5 49.5831
36.7
17.2 81.94265
Lettuce 2.8 14.4 23.5 6.6 17.0 11.7 24.0 36.6 19.3 12.4 23.5 29.2
9.7
1.3
1.4
1.8
11.5
11.5
0.4
22.0
0.0
0.0 8.0847
0.0
0.0
10.0
19.9
3.0
27.2
3.7
24.3
1.5
15.9
2.4
2.4
26.0
2.4
1.2
16.2
1.2
2.7
14.5
3.3
1.8
15.6
25.9
58.3
25.9
44.3
38.4
2.5
16.1
15.9
2.9
0.0
0.0
14.8
9.1
26.0
21.3
0.0
0.0
0.0
0.0
16.9
3.9
22.6
14.1
18.4
8.6
0.0 11.9811
0.0 53.08535
42.6 42.03475
0.0 14.97915
0.0
0
0.0 11.7219
23.9 31.3329
21.2 21.2 50.2 0.0 0.0 0.0 123.7
9.8 15.1923
15.4
16
20
2.5
1.6
18.5
3.7
12.4 4.3409
2.6
0.8
21.7
0.8
2.3 5.0
1.0
1.0
22.7
4.9
0.8
10.0
0.0
38.5
16.0
0.0
0.0
1.7
0.0
0.0
44.0
0.0
15.0
5.0
0.0
0.0
17.6
14.6
2.9
34.1
23.0
0.0
16.0 24.88095
17.0
0.0
0.0
16.2
0.0 21.1111
31.2
0.0
18.8 15.33025
13.9
12.3 26.5625
19.0
4.4
2.3
0.6
21.1
0.8
1.1
1.1
5.6
13.3
10.9
0.0
0.0
0.9
0.0
6.1
2.0
20.6
22.4
0.5
0.0
0.0
0.7
0.0
0.0
1.4
0.0
0.0
10.0
7.833
0.0 7.32145
0.0
0.0
1
0.0
19.2 28.09645
0.0
0.0
0.0
0.0
16
0.0
0.0
0.0
1.7
8.3
1.8
1.0
7.1
2.0 2.1
0.0
0.0
0.9
33.4
33.4
37.5
73.3
2.8
1.5
0.0
1.3
0.0
0.0
0.7
0.0
8.7
0.0
0.0
10.6 664.2857
28.7
45.0
36.0
0.0
0.0
0.0
0.0
0.0
0.0
4.5
2.0
2.3
22.2
2.2
12.8
1.9
1.0
0.7
35.4
29.3
22.0
20.0
1.9
15.2
18.4
13.6
7.5
14.2 127.3375
22.8
16.0
12
0.0
18.5
12.5
1.4
0.0 3.8016
13.2
5.2
1.8
2.3
1.3
15.5
3.5
6.7
1.6
9.5
2.4
2.3
2.8
4.8
1.6
0.8
1.2
0.0
12.1
1.7
13.2
16.4
0.9
11.6
0.0
39.6
29.7
1.8
17.5
32.2
5.6
0.0
15.5
12.0
14.7
20.0
0.9
22.5
0.0
18.6
16.5
0.4
0.0
0.0
12.0 11.27695
13.5
0.0 4.0357
0.0
20.1 13.48725
0.0
18.7 23.3333
21.1
0.0
0.0
12.0 15.0265
12.9
20.0
17.0
0.0 17.47915
6.1 10.0344
23.0
Oats Onion green
16.0
2.6
15.0
1.5
18.0
1.2
18.0
12.0
0.8
12.1
6.1
20.0
0.4
31.8
2.5
20.0
1.8
11.5
1.4
21.2
12.3
0.4
12.0
1.1
12.0
1.4
13.1
25.2
2.2
12.0
1.7
20.0
1.3
12.0
1.3
0.0
17.1
2.0
20.0
1.3
20.0
2.9
12.0
1.9
20.0
1.4
22.9
1.6
20.0
0.7
14.4
12.0
5.0
20.0
4.0
45.2
1.2
22.0
6.8
20.0
4.1
31.3
0.8
20.0
12.5
1.2
7.2
1.0
22.0
5.0
2.6
20.0
0.6
18.7
16.0
1.6
20.0
1.2
20.0
Appendix II - p.8
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
W.melon Wheat Cotton seed Cabbage Carrots Cauliflower Cucumber Lettuce 10.0
11.9
4.3
12.9
22.0
13.8
1.0
18.0 22.65995 23.0
1.2
2.0
4.1
3.8
22.9
11.9
0.3
14.5
2.4
37.8
3.0
28.6
1.2
12.5
1.5
6.2
5.4
22.3
1.7
4.8
1.1
1.4
14.5
0.6
1.2
8.4
12.5
4.6
13.0
1.5
29.2
2.0
12.8
3.2
1.8
4.4
2.3
2.3
0.4
8.6
26.3
2.9
14.0
1.9
11.7
2.7
15.4
0.4
11.5
21.0
12.0
26.4
16.1
32.8
21.6
0.4
1.3
33.1
24.5
3.8
28.8
51.3
13.4
11.5
0.9
22.7
0.7
0.0
43.0
53.7
22.9
40.4
3.8
22.1
13.8
1.0
7.1
11.0
0.4
0.0
1.5
11.9
12.0
1.0
22.0
20.5
1.5
11.4
7.3
2.9
22.3
21.1
1.9
6.2
18.3
0.3
14.4
11.5
36.2
13.4
28.4
56.1
1.7
23.0
38.7
8.4
11.1
2.4
53.2
36.3
0.8
30.0
28.9
1.0
23.0
12.0
10.0
17.0
10.5 11.24215
8.2
24.6 13.18185
14.2
20.9 63.4612
27.9
9.3333
10.6771
21.9
54
24.0
17.0 88.2353
24.9
21.9 11.41915
20.9
3.58335
6.9 8.33945
16.7
17.0
6.6 11.579
5.2
20.0
22
0.0
18.3 28.67225
17.4
4.75
18.5
10.0 10.3859
13.0
35.0 55.00105
19.7
13.3
410
27.4
17.5 16.4046
33.4
10
16.4 14.03265
24.3
17.2
16
22.7
13.5
1.6
13.6
3.3
7.5 5.6
1.4
9.2
8.7
13.4
7.5
1.3
7.0
1.0
17.11075
4.5
7.36665
Oats Onion green
12.0
12.0
2.5
20.0
2.6
1.0
12.5
1.8
21.0
20.0
12.0
3.6
61.6
5.7
61.6
1.2
15.8
0.5
12.0
12.5
1.5
12.0
22.0
0.1
21.2
1.9
10.5
12.0
12.0
1.4
20.0
16.5
6.0
13.0
2.2
20.0
1.0
22.0
20.0
1.2
22.0
12.5
12.0
1.9
20.0
1.6
12.0
Appendix II - p.9
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Bahrain Brazil Brunei Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, D Congo, R Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Onion dry 14.5
Peas Safflower 7.1875 2.5263 6.78635
Spinach
Sweet potato Artichoke 8.1
Citrus
Rice 2.25 2.3 1.5
8.5
0.8375
7.9
27.4 24.26765
0.776
18.0 7.1699
38.9 20.4492 0.77925
15.2
51.9 41.07015
11.6
10.6 4.4309
5.5
29.9
4.0
8
4.8
13.3
7.5
2.125
26.7 30.12615
1.2
19.1
0.0
4.5
9.9
7.5 5.8239 7.5 5.1704 14.5
12.4 8.9022
7.8 21.9422
7.2
5.8
18.0
18.7
5.4 5.2566
3.2
17.1
14.4
12 9.5518
11.0
6.2
5 4.62185
4.2
3
9.4
3.076
8.5
3.2
2.3
14.0
9.7
15.5
6.2
2.0167
5.0
2.08705
11.3
3.2
1.6667
4.3
1.79305
15.5
4
10.2
5.4 2.7941
5.2
1.6519
3.0691
5.5
1.9259
6.2
3.12495
5.7
6
3.4
1.86585
7.2
3.25195
33.5 11.11915
1.5
5.8
27.5
20.0
36.5 25.81115
20.6 7.97325 2.16665
14.0
16.7
14
6.8
5.9
6
23.5
4.5
7.9 5.82635
6.6
37.5
6.25
15.5
4.523
30.4 14.69855
9.3
1.2
11.5
10.0
5.7
5.3
3.5
1.46155
2.5
1.48545
7.0
7.5
6.8 4.02985
20.3
4.0
12.4 6.34365
14.0
6.8 4.89515
2.6
1.2143
3.7
0.755
7.5
0.8571
28.0
11.0
4.30975
3.0
11.2 1.57235
5.2
4.2
5.1 2.77285
19.0
8.8
5.3
14.0
9.7
5.2
14
7.7
9.0 5.0724
23.8 9.3316
8.2
14
0.6
18.9
4.4
14
10.0
5 0.52145
4.0
4.1
4.43805
3.7
13.5
5.3 3.36425
24.0
18.0
17.5 8.75905
6.5
6.07815
2.5
5.2
8.1
17.2
9.5
40.2 19.56075
6
18.0 12.074
38.4 15.3646
7.7
0
19.1 7.40965
8.0
6.3
5.2
0.0
1.2
17.2
15.9 13.4 1.2
9.5
14.2
6.2
1.8
14.0
9.7
1.4
20.0
10.0
2.7
10.5
6.1
1.37705
5.2
5.4 5.95475
2.6919
2
1.68265
3.2
5.4
5.2
1.5491
12 7.63025
7.8
3.2
2.41405 5.1 1.50935 1.51415
Appendix II - p.10
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Onion dry Peas Safflower Spinach Sweet potato Artichoke
4.7
5.7
6.5
24.4 5.36845
11.4 7.38065
7.3
8.5
25.2 9.9121
8.8 4.91935
31.0
9.5
30.3 16.6805
28.2 20.11925
8.7
50.7 22.13145
15.1 4.0192
13.3
1.2
17.5
0.6
0.8
2.0
6.1
0.8
56.3
13.2
7.6
12.5
20.2
3.0
3.3
11.0
9.7
8.5
7.8
9.5
7.5
9.7
33.4
10.0
12.6
10.0
16.1
23.8
Citrus 3.2 16 12.4 8.5 7.4 11.5 6.8 20
Rice 4.1243 1.99 2.4201 3.00945 5.2 2.94915 4.22555 4.25235 1.8642 5.2 5.5 6.214 1.49105 6.31655 2.3
13.6 2.5966 0.4347
5.6 5.7143
20.0
9.5
11.0
3.0116 6.1 2.6238
11.9 9.6154 58.9 10.3224 25.9 16.5 8.6 18.8 19.29555
14.7
12.9
12.4 4.00865
14.7
21.2
6.50645
41.5
12 2.4424
5.6
2.81975
3.2
14.9
4.5
16.0
2.8
19.0 8.10715
8.6
6.3
8.0 13.2863
10.0
1.2916
5.2 5.03615
8.5 1.83335
5.5
2.0916
7.2
5.2
8.2
8.5
12.0
0.5
29.0
12.6
0.0
0.0
22.1
6
12.4 6.2204 1.48765
11.7
7.9 4.3423
0.0
3.0
21.5 10.6394
5.7
6
8.2
10
0.8
11.1 0.2 4.6
8.9
1.0
11.7
19.0
12.0
5.9
2.0
15.9
12.0
6.9
4.6
7.3 1.85515 5.5 2.9122
2.24415
7.1
3.2
9
0
4.54265
3.3
7.1 4.6435
1.125
3.3 9 5.2059 1.07465 3.1844
36.0 22.3658
1.2
20.5
20.0
42.5
6.7
2.2
24.5
6
6
0.0 5.2108
15.1
7.4
13.2 12.94155
0.75
10.9
19.7
6.7 6.93335
22.0 6.2485
11.6
6.8
21.5 4.07495
25.3 8.8916
16.5
25.9
9.8
0.0
10.1 9.58715
10.6 2.92515 1.04165
25.0
14.0
9.7
4.3
15.2
6.1 5.0 17.9
11.0
4.7
7.8
14.8
18.0
4.2
14.0
7.3
5.9
2.6
4.9 4.6 10.9
2.4335
5.4
5.2
10
6.8 3.30695
2.71135
4.4
1.549
5.2 3.9 2.9837 2.75565
1.7857 3.9396 3.2 6.0153 2.8226 5.2 6.0007
4.5 2 2.8352 2.88645 1.864
Appendix II - p.11
Appendix II. Actual crop yields (ton/ha) in 1999. Source: FAOSTAT database (www.fao.org).
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Onion dry
Peas Safflower Spinach Sweet potato Artichoke
4.0865
1.5
12.3
7.5
20.3
5
12.0
7.4
0.8
11.0
16.8
4.5
20.2 4.9055
20.6 21.62995
42.3 16.1121 1.49405
17.1
7.8
8
7.1
29.4 12.9167
38.36145
19.0 9.0304
7.7
3.0
6
14.7
12
1.2 12.0
0.9
12.0
4.5
16.1
4.156
21.6
9.828
6.5
4.0
5.2
7.9 3.2409
12.0
8
36.0 10.1948
44.0 33.6443
8.1 9.6311
27.0
2.928
25.6
5.3
3.0
8
1.0286 1.676 0.9272
15.2 9.6 109.6 12.0 16.3
12.0 4.6 2.7
14.5
10.0
3.9
12.0
16.2
14.0
5.5
13.4
11.7
1.8
11.0
1.7
15.4
7.2
12.2
6.7
8.2
16.0
11.5
4.2
14.0
9.7
16.5
12.5
10.0
9.1 6.3
14.0 2.7895
10.0
5.5 5.57055
15.2
6
14.8
14.4 1.9986
2.1
Citrus 6.2 12.5 5.6 12 24 5.1 3.8 4.5 8.2 11.6 14.2 15.5 24.8 6.8 7 15.5 3.7 15 5
Rice 3.3 2.6106 1.15665 3.3 5.2 5.2 3.9679 1.6667 2.26925 7.30225 3.264 0.8598 3.7621 6.83335 5.2 4.28635 2.53045 1.53665 2.372 1.92265 2.9244 2.3 4.75415 0.8975 1.40165 2.96635 3.3 5.2 6.46125 5.80615 2.44815 4.8423 4.03165 2.1 2.3 0.80885 2
Appendix II - p.12
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Banana 2066 3760 604
Barley 3142 2990 3910
Bean dry Bean green
3470 14897
3542 1151
Grapes Groundnut
941
908 3717
6317 6611
6710
11845
Maize 2227 577 3066 5172
Mango
Millet
Palm
5621
6328
929
887 2538 454 3726 0 492 1665 147 374 3212 440 529
1599 2789 2069 753 3622 4211 5982 2445 377 3490 0 5148 1089
2656 1069 5640 2077 1012 4759 3087 796 3588 5251 2368 1372
939
3375
3084
303
555
2405
627
1272
1710
543
799
520
680
3801
829
3952
4346
1421
178
522
3533
330
2306
451
1057
888
6458
2434
2258
0
700
4140
3350
3533
4730
2476
2072
923
3180
1205
128
142
3400
256
1700
365
1029
1885
2132
5484
3692
2210
4916
1627
615
1127
0
0
952
2998
1459
1211
530
861
803
8400 15400
16424
483 0 3281
1823 1392
5846 3557 4157
660 3043
485 1220
2701 3209 7729 7139
1261 839 4900 4521
1878 4332
7681 3732
1286 1257
1613 929
8366 3329
6110
2706 10069
314
830
6353
1750
1745
2607
5122
593 6547 7754 1215 465 1839 211 3115 3837 0 0 117 1110 804 199 9480 768 190 258 4929 3102 1207
1098
1377
679 1640 1437 5367 1524 2375 904 680 2547 4382 2619 2920 4417
9912 1646 3145 2417 5379 0 8433 983 12994 3575 2023 2077 0 5028 1772 4621 1241 5647
353 3540 362 366 476 612 299 440 275 526 1671 336 1066 689
2763 726 418 572 1287 1000 1317 796 1399 1294 623 662 835 0 1866 533 1007 1191 2638
1060 4645 7405 1870 1676 2769 4690 4923 0 3468 4309 4882 5820 1633 2891 2891 0 5605 1953 5060 2891 4345
381 17162 3059 9228 295 708 2088 1840 4431 0 1528 4855 443 1840 1478 478 264 4628 3929 0 2627 506 1893 264 3015
397 2941 4331 864 951 773 0 7718 9820 491 17080 0 8141 2046 2494
3075 4090 13683 1680 5303 5421 847 1845 2306 4678 4613 5468
308 1625 681 584 2415 0 724 1432 0 6965 14230 971 11890
0 1353 1867 5427 3305 0 347 215 4075 1863
1352 572 1984 577 2178 4565
1158 8700 2907 2077 1492 0 5797
943 196 308 598 1308 333 516 268 1034
551 426 1134 243 1363
0 2891 3320 5495 11357 2891 3370 1327
2333
4372 3136 4109
0 773 354 6287 1783 4030 1444 476 2733 232 0 1678 2734 4520
0 3814 4137 1841 0 20326 7504 2504
4613 5849 3790
621 1255 18310 621 1564 0
4092 4527
576 4826 1755
Appendix III - p.1
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Banana 1177 1277 163
Barley Bean dry Bean green
1140
6134 8359 2117
1010 1034 263
Grapes Groundnut
5622
1167 686
5952 4080 3533
Maize 3925 5832 2425 494
Mango 2171 1995 1641
Millet 2553
Palm 573 365
272 690 500 252 207 1169 1229 404
2008 6176 3775 535 5867 1160 924 2796
13775 2346 2609 8626 588 1697 4094 1740
1899 511 0 1399 2200 0 402 428 256
482 1291 1488 2533 567 811 3447 1241 430 3285
8318 2806 2563 1640 873 4882 4747 1977
2852 1821 1019 3008 264 502 252 4497 1317 338
1600 3065 2839 2227 2254
7177 4752 7968 2910
1619 857 1983 621 1983 854 833
3051 0 1548 622 294 9141
2403 1415 1230 0 0 1520 2254 702 11341 5270 2015 1438
0 4561 0 3631 1929 1792 3012 2055 2700 907
376 991 331 0 557 1284 275 2405
1392 1561 398 0 0 7303 923 792 2200 902 469
0 6395 1685 0 8210 3450 1228 6633 3190 2891
2027 2473 880 0 0 1428 1555 1452 2423 2622 264 722
2807 1532
7146 5335 3560 0 3568 4100 4341
7090
3495
4684
1270
2179
8087
5056
1630
1407
2810 444 3376 3883 297 763 239 0 2455 236 2327
2225 0 7514 1453 2099 0 3370 2983
4895 6067 8167 0 6084 3204 6413 5330
530 563 3000 785 451 733 216
1246 0 897 510 1259 1134 1410
4003 1386 6225 11550 1525 3121 2209 6359 4060 6816
1891 2013 3304 13431 667 1338 0 1121 1273 3413 9733 1779 2523 8389
2338 3044 4220 3554 1277 3000 1859
5207 1544 6262 17719 4785 7410 2593 4108 4454 17934
678 1440 1336 1054
0 208 3329 0 795 3294 185 490 394 371 4007 309 592 427 1837 310 310 12420
3335 566 635 4270
6826 933 3185 6774 7000
1123 5613 3930 0 2667 3492 959 2784 1340 1448 2492
5300 9933 14727 7310 3287 3903 4371 1388 6657 12207 11802 1646 3240 0
254 279 1007 483 409 603 470 1461 1187 1233 1172 1100 351 3069 505
595 715 1611 514 1172 1374 0 627 966 1856 923 971 2760 15980 892 931
2891 3218 1749 13819 3973 3355 3911 6034 4245 5488 4564 2762 4881 2446 1736 8396 2891 0 5704
1764 445 0 2861 4176 4170 3845 334 1640 1608 2906 764 1680 1922 2092 551 809 1425 399 1059 874 1608 0
3565 4613
3792
12393 3024
7429 1853 2248
13056
2189 841 2272
6826 1921 0
4428 3941 0
621 925 622 1881 7965 1402 819 1599 525 1046 621
Appendix III - p.2
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Banana 0 0 0 827 3908 312 345 345 0 1433 581 139 272 222 739 2098 324 2309 2009 969 4840 10406 1839 293
Barley Bean dry Bean green
1212
5167
2094 1191 0 4514 1442 926 674 14462 2042 1438 3718
1213 2379 0 0 4511 3753 11011 1887 3191 1519 2572 3946 2798 15885
4064 658 13205
7315 3340
1200 314 1060 886 537 189 957 606 3434 252 437 467 400 515 424 228
Grapes Groundnut 0
734 1163 2455 0 670 1594 1048 733 354 354 1816 13276 1862 439 1653 1275 1264
1598 2383 4871 3094 4364 0 3434 1804 10768 6482 6607 3900 2891 2388 5673 6302 1884 10548 7750 4418 1361
Maize 0 0 2501 3931
Mango 0 0 1886
2983 531 707 611
7970
0 1966 401 3500 6325 3775 2760 345 346 1299 1646 2663 776 2266
0 1519 0 5320 12449 11210
1839
2544
878 1878
Millet 2019 5667 3383 4100 1909 0 7655 1394 7566 12347 6964 3284 2544 9037 1476
Palm 0 11980 1448 814 750 1516 805 1198 8736 1025 594 1747 848
3636 1193 402 313 0 338 476
2018 638 1118 1670 3266 2836 3978
6891 1800 6800 2077 1367 6727 3985 5413
400
5751
3222
2023
4034
3699
4609
1693
4113
272
6016
1030
1096
3940
166
2382
2891
396
3690
365
391
251
1064
377
0
1985
450
742
466
7080
664
2083
2621
1388
1089
826
0
0
820
556
2167
1220
781
925
527
1240
3621
1695
1805
3322
1054
1800
2907 0
1003
3159 1599
3131 3136
589
1462
3451
3892
6700
816
1237
3944
1009
6883
6325 3829
4945 2538
3587
570
1450 13214
3338
5159
1433
503
1548
6517
2238
3530 14300
Appendix III - p.3
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Pepper
Potato 176 467 451
Sorghum 5627 2796
753
Soybean Sugarbeet
487
4007
2218
Sugarcane Sunflower
671
4528
3579
18200
0
308
5771
Tobacco 3022 5349 3668
Tomato Vegetables
426
2415
568
483
638
0
1257
431
3375 4825 5217 2850 7800 5183 4213 19760
179
960
254
146
1515
879
345 15205
0
308
2012
293
58
290
769
4706
184
0
611
1488
309
16209
2458 1700 2933 1261 2720 2875 7075 8206 3213 0 3450 1601
258 58 7586 184 545
1910 193 1069 566 337 222 583 303 363 450 0 260
2137 4531 1133 4208 1574 2718 3489 7645 1833
2460 2979 2125 1194 2358 4659 1617 826 4860 6035 0 3830 1746
929 1389 135 137 87 206 356 0 698 660 260 114 1209 510 329 478
805 191 131 123 94 148 430 0 625 4560 171 617 536 542 2073 0 484 526 1151
1470
305
2467
2244
220
209
5351
2295
954
273
0
0
1746
6120
226
176
2231
2197
243
501
1153
9609
5520
23310
10560
742
498
2214
3192
5696
251
3610
396
566 14413
1239
2235
2048 7774
483 12470
5040
491
2575
1076
382
5217 3842 2678 3158 619 9840 5180 7500 6260 6260 4470 3808
121 360 1978 1118 329 311 232 325 605 0 160 478 217 266 168 83 5410 0 433 220 855
897 3096 9997 1073 1339 973 4697 10304 1055 3950 0 2355 824 3509
1227 3588 3119 1616 9627 2325 4550 2213 2220 2125 2361 2954 2492
93 107 224 184 1556 608 88 71 788 160
1202 1989 240 132 134 284 0 100 223 505 203 176 8770 0 186 181 251
1935 2887 2385 2866 1345 2492 2379 3218
1006 4810 5632 5241 1279 2585 1779 4083 8150 0 0 1622 8920 3054 6936 1295 1415 1489 4300 0 1550 5092 2722
48 342 273 80 260 208 662 674 0 0 165 5890 547 1486 660 212 87 7080 0 464 159 212
95 309 524 441 571 1560 210 324 657 610 0 0 193 446 570 926 661 1302 107 757 3756 0 414 297 314
253
1063
181
7821
745
3756
1750
2492
2573
156
7101
85
359
580
1366
0
411
0
0
0
0
0
6260
166
116
176
3144
133
97
6260
108
419
1277
54
356
1279
1013
133
202
1942
164
204
2615
192
404
4733
6114
4858
757
240
5832
4428
2387
2493
147
6260
84
371
1303
71
1173
999
90
1225
7443
365
2132
595
7493
4757
3240
364
2615
3435
144
185
4166
2032
174
206
4400
3942
273
0
0
392
383
348
3867
379
2569
985
875
1356
151
306
4959
277
4833
783
4835
601
668
Appendix III - p.4
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Pepper 4760 6260 13371 7894 7713 6260 5142 5180 5413 2325 4200
Potato Sorghum
398 3580 155 256 262 351 224 389 103 123 227 348 724 156
4238 3466 1134 6087 3358 2875 23086 619 449 677 6839
Soybean Sugarbeet
1302
104
1395
89
6077
344
4031
3741
214
2795
244
2833
705
4850
1586
145
2646
97
Sugarcane Sunflower
211
256 105 1966 2492 281 10449
239
287 1122 353
13484 7735 2492 6931 1843
274
150
4130
Tobacco 4533 2749 6048 1450 4535 6303 6146 4070 2573 7000 1693 2918 1507 15667
Tomato Vegetables
1037
416
397
667
2788
2620
132
172
90
476
5460
785
486
320
264
624
470
534
6378
253
118
259
396
2596
93
107
135
161
3250 8145 2950 1675 6260 4471
1416 1047 304 0 0 505 585 207 169 663 233 264
0 4101 3460 0 18050 2316 2405 4767 2000
2615 5000 3768 0 4500 5492 3778 11500 4250
232 544 2899 137 73 140 101
6115
178
6224
171
359 183 523 10766 1069
10125 2492 2119 3738 2136
2369 2235 2462 0 4667 2229 716 1953 1685 2573 2211
434 504 686 0 0 594 447 138 5100 474 495 204
0 439 0 319 0 0 284 531 109 110 617 610 272 1032 156
13591
985
8340
4958
585
5351
682
595
5788 2411 3592 6750 2550 2608 1977 1565 3375 5080 7391 2922 3508 2520 1565 2110 0
334 299 1792 1814 176 191 664 435 1829 224 285 2628 335 73 0 127 368 5750 875 169 311 159 383 0 1051 1121 412 317 209 283 537 402 228 339 0 341
3810 5779 15659 1146 0 1010 6436 3355 3278 10949 325 0 2694 24989 4991 1997 10216 1989 799 3767 799 438 1700 2690 0
4922 5110 2780 3977 3560 4517 8394 1889 3763 3008 10763 13990 5250 6593 7631 2664 3238 4342 2267 1836 1848 4112 0
13460
5942
4068
500
456
256
218
4190
5225
299
255
240
287
8791
258
868
653
5670
0
0
255
6243
374
321
388
9475
1036
230
2863
551
235
261
192
4776
1973
180
456
0
241
367
2269
2279
264
1838
0
1248
820
58
173
7225
3240
100
154
777
5096
2491
553
656
301
4265
1988
230
4507
1179
0
411
6072
487
87
305
2492
2830
88
62
0
2727
96
103
272
3945
3769
654
921
8220
593
579
803
6456 18819
1485
794
0
109
2042
2718
116
0
403
1040
1239
349
325
386
411
6063
3444
4748
503
313
5620
2213
564
375
0
0
254
2875
1085
182
385
3591
3555
163
556
129
3691
204
209
230
3652
624
435
118
204
2718
965
242
125
818
1085
5841
1450
76
176
5603
4340
544
196
2116
420
5460
725
573
184
2405
2098
226
1336
215
377
3586
2997
304
160
0
5810
0
0
298
529
0
Appendix III - p.5
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Pepper 0 3188 3417 2344 2115 4825 1980 10319 7963 1565 3613 1504 4240 817 7602 4143 4517 1565 1565 2531 3750 3158 3227
Potato Sorghum
186 227 320 313 227 176 167 553 538 2296 1030 93 208 426 572 386 243 362 123 781 551 549 248 792 778 323 422 214 321
3565 5085 4271 2983 1461 0 2157 656 7020 6241 5867 8255 8100 4073 1557 5962 11281 2625 2286 3185 2167 595 1178 1776 1188
Soybean Sugarbeet Sugarcane Sunflower Tobacco
0
0
0
0
794
4708
676
3391
4258 3308
470 1136 0
4337
361
1927
714
5228
4083
9056
87
1023
59
8692
152
2564
16438
3048
338
1909 683 848 0 276 158 286 1981 5448 837 332 159 200 621
4656 3028 0 4144 5428 5213 1070 3497 8683 2400
5595 5225 2552 0 0 2498 1390 4709 5992 4440 1786 4005 1491 5940 2653 10300
4773
141
1055
69
357
3858
384
7344
5196
402
3625
2554
2260
4902
5415
490
4607
397
1259
69
1380
81
3225
5845
609
1155 290 292 161 249
6483 4337 3322 2115 3151 2444
3714 6496 487 1415 1264 1258 2327
4738 3322
206 2373
2470
1722 1805
Tomato Vegetables
0
0
0
288
212
262
169
1026
540
514
484
228
202
255
426
0
0
0
198
317
76
160
1057
5140
429
444
1236
384
415
412
114
117
102
105
181
519
363
156
795
574
504
410
1488
920
393
2720
570
514
157
314
96
110
515
359
0
962
533
507
504
103
180
102
784
77
77
247
295
148
607
0
1716
167
239
8995
1919
3350
418
2711
3207
621
861
1925
175
7336 7367
526
4630
2124
251
4817
3057
2021
487
413
3107
2646
697
496
1312
7319
2158
5010
720
918
4529
2505
966
746
Appendix III - p.6
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
W.melons 485 408
Wheat Cotton seed
3528
6736
3210 7222
0 9774
Cabbage 325
Carrots Cauliflower Cucumber Lettuce
250
0
0
0
Oats Onion green 0 0
2655
5470
0
49347
748
0
0
336
1218
5292
201
256
396
231
2690
242
138
1954
0
0
0
0
0
0
362
2082
2402
104
181
661
321
184
2902
242
688
1940
34
120
189
42
82
794
149
324
1928
0
138
0
547
136
0
145
199
405
0
0
0
0
0
0
1890
4947
0
0
0
0
488
0
0
0
2159
115
228
232
1297
130
424
94
83
189
46
36
957
310
7339
1647
0
394
3338
5083
311
0
200
1130
243
0
2298
2351
202
0
531
332
0
100
1363
596
1706
3095
235
360
401
203
4592
220
234
1370
0
116
0
3536
4841
8605
0
190
0
1607
328
0
140
2640
4005
2919
222
164
1441
4060
76
115
290
164
149
2328
202
336
170
0
0
0
0
13874
3634
14879
258
1053
127
118
242
172
271
1632
221
189
1024
1769
111
256
202
278
158
2887
195
287
1525
1893
644
146
381
190
207
2686
164
2739
15637
159
0
0
0
0
4280
334
341
259
787
1439
118
5724
271
1983
199
0
203
452
313
1244
149
222
341
0
103
3246
108
0
0
62
443
0
817
805
58
183
206
267
301
1034
149
518
62
88
356
9
92
630
149
361
0
0
0
0
0
115
0
374
4465
8075
343
0
745
282
437
0
764
230
1005
4811
157
147
0
419
162
8914
464
246
2135
4514
474
0
4408
2796
1940
0
0
4881
5389
261
0
93
1953
0
0
0
1884
91
516
0
95
119
493
50
130
1391
173
86
85
374
32
113
798
181
263
0
30213
211
1609
257
0
0
5565
498
1940
38
81
170
93
129
725
181
2322
7854
0
0
143
3440
3641
132
175
317
69
190
3411
207
0
329
0
0
0
254
423
0
0
0
131
1150
2140
200
508
474
933
230
3350
262
5048
6361
Appendix III - p.7
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
W.melons 339 173 486 323 3348 304 148 273 124 96
Wheat Cotton seed
3450 1040 2675 4938 3330 9560 427 4067 2016
13626 2140 13402 5507 6540 3115 3332 9724
1088 15245
Cabbage 647 525 0 72 0 200 170 178 97 58 143 145 228 69 64
Carrots Cauliflower Cucumber
0
0
201
139
250
160
0
0
0
0
294
921
388
350
528
569
414
0
0
0
173
483
23
64
0
95
133
276
173
391
0
386
154
464
80
159
348
65
Lettuce 0 247 132 913 208 0 130 69 201 374 141 152
Oats Onion green
289
1371
230
4380
244
4092
277
482
0
358
572
173
0
132
2019
215
3178
493
0
200
455
0
5005
2198
157
368
3193
17060
171
643
13264
288
0
0
425
221
1273
3981
235
177
353
169
3437
351
0
0
0
0
0
0
0
0
0
57
0
0
0
0
433
2652
2485
112
265
307
0
288
2148
1550
117
0
0
1856
173
117
1169
58
287
207
0
30
0
397
2819
0
290
3748
1386
207
1143
130
0
87
255
107
0
0
0
306
188
150
387
1791
173
0
173
1796
4918
278
0
0
1205
1539
2097
3713
6077
389
192
5188
101
343
328
169
218
372
2998
5837
0
0
0
1363
229
0
0
0
8080
7650
218
0
0
0
175
160
173
824
2143
96
183
423
255
216
4233
243
680
1597
148
10540
9021
174
4143
2105
0
2880
10482
3092
8083
675
4148
0
472
383
0
0
0
0
0
155
252
0
173
0
308
315
3208
449
6222
59
108
321
0
4670
426
69
92
136
2975
1963
3475
7784
3406
12871
0
5
80
644
115
1428
4267
149 118 204 1315 257
810
55
0
391
0
101
0
121
3045
2469
185
307
341
517
6050
328
327
3245
5461
0
0
0
0
0
692
310
2716
318
0
0
0
0
0
1187
2319
8142
0
3158
498
2049
2782
4263
313
0
0
0
278
3220
200
284
8246
0
0
926
1056
49
127
235
222
1349
149
606
3154
3772
127
146
248
164
149
6682
206
584
508
1566
201
0
0
0
0
2807
0
0
0
0
0
1338
0
87
172
2211
149
628
2384
105
0
0
359
100
2980
179
0
19609
Appendix III - p.8
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
W.melons 544 309 1975 0 0 396 96 145 638 289 1071 271 550 436 342 100 458 1259 2759 114 334 426 222 299 0 352 340
Wheat Cotton seed Cabbage Carrots Cauliflower Cucumber Lettuce 0
1329
166
391
6187
284
274
254
3458 941 0
192
443
74
228
60
174
0
0
1951
6875
104
243
1155
1342
137
86
0
0
3295
7962
177
2553
10563
600
46
68
696
0
0
3365
2325
165
301
4314
4399
274
334
3002
14800
4960
2933
310
502
4283
8158
151
943 2678 1382 1347
169
4360
198
0
933
97
196
4639
335
0
2351
23523
2067
184
319
13697
101
404
435
69
65
1302
3551
91
109
1578
483
0
1250
3642
46
101
8323
6675
101
187
5580
139
423
485
201
449
267
0
123
0
271
197
94
178
451
0
215
56
96
0
0
0
201
363
193
0
735
613
275
202
0
423
0
0
0
0
191
151
884
321
0
508
0
177
100
0
355
7
114
308
322
123
460
0
0
0
305
252
2812 1743 476 679
4576
355
585
178
0
5142
796
5726
0
866
491
Oats Onion green
381
350
1394
149
0
5100
357
3855
302
218
520
962
48
0
0
0
293
0
248
316
3713
379
221
50495
247
3211
512
248
445
2482
149
339
588
265
2948
223
6110
157
149
3667
195
302
451
2188
210
0
333
Appendix III - p.9
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Afghanistan Albania Algeria American Samoa Angola Antille Antigua Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Botswana Brahain Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Burma Cambodia Cameroon Canary Islands Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo, Dem Republic Congo, Republic of Cook Islands Costa Rica Cфte d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Estonia Ethiopia Falkland Fiji Islands Finland France French Guiana Gabon Gambia Georgia Germany Ghana Greece Grenada Guadeloupe Guatemala Guinea Guinea-Bissau
Onion dry 0
Peas Safflower 0 0 0
Spinach
Sweet potato Artichoke 0
Citrus
Rice 0 2565 0
0
0
0
241
185
7693
0
0
170
220
7661
244
76
66
202
0
0
0
0
0
459
0
0
0
1285
149
91
2808
122
800
0
0
0
0
528
0
528
461
512
124
0
0
356
0
1422
1636
1938
375
753
640
900
318
952
0
1277
0
2233
0
2666
645
2797
2565
250
482
317
952
3362
0
3450
0
2053
0
0
3792
317
0
565
1741
2720
0
0
1922
0
0
0
0
0
500
0
4395
0
0
177
306
4080
569
0
0
183
156
271
523
2622
278
0
287
0
0
572
143
667
505
469
0
0
829
471
257
604
2808
203
131
257
233
1088
0
0
0
0
0
0
1516
1234
1821
244
2343
594
1072
781
1210
1471
0
0
0
0
0
0
0
0
1703
0
0
5374
1135
0
2255
0
0
1107
1113
250
482
1135
270
1735
0
0
0
584
830
0
793
1519
2042
282
581 11333
0
283
767
780
1096
827
287
0
1349
0
0
270
1135
0
804
0
0
326
398
139
193
3900
210
670
0
0
146
246
227
0
428
749
353
0
0
648
4733
0 308 0 312 3707 0 0 0 0
1208 772 1104
787 787 698 1312 1869
0 1135 991 0 3125 5705 1844 1135 5939 1025 2850 3169 0 0
Appendix III - p.10
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kampuchia Kazakhstan Kenya Kiribati Korea Korea, Republic of Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libyan Lithuania Macedonia Macao Madagascar Maderia Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mexico Micronesia Moldova Mongolia Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norway Oman Pakistan Panama Palestine Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Rйunion Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia
Onion dry 0 0 229 562 0 0 0 180 171 240 0 113 0
Peas Safflower Spinach Sweet potato Artichoke Citrus
635 704 816 433 828 0 398 487 208 161 1349
3900 13467 6063 11500
0 207 1600 0 0 293 563 257 0
0
0
2581
397
0
838
2360
850
595
0
1000
1918
0
168
0
2000
320
955
640
424
1685
212
353
Rice 2139 0 3273 2060 0 3350 2201 2401 0 1135 2182 1030 0 1203 3570
293
0
0
800
0 179
2059
0
1265
1700
3518
518
401
0
0
0
241
0
0
205
239
0
555
1639
0
0
0
0
633
2538
0
3092
1844
0
1302
643
2107
0
496
0
600
494
285
0
0
1135 1172
824
2275
0
5355
0
879
759
459
277
0
0
0
0
670
485
772
4168
278
0
873
1200
0
491
1836
3056
0
0
0
0
2328
0
1180
0
0
0
1942
0
892
1441
1719
0
0
0
0
395
0
945
629
367
6013
0
3636
0
250
939
0
0
7091
0
2738
110
122
2808
143
331
106
0
0
365
917
915
524
0
816
0
0
0
0
0
0
0
249
669
730
185
930
216
484
0
393
285
373
1296
0
189 0
0
135
250 0 424 0 1270 0 0 0 793 0 1384 250 663 0 0 0 0 0
4027
482
724
1135
768 1790 3564
3151 4536 8134
1135 2992 3677 2765
0
1990
0
3113
1368
3089
1135
1133
3556
0 2081 2044 0
Appendix III - p.11
Appendix III. Specific water demands (m3/ton) in 1999. Source: calculated on the basis of Appendices I and II.
Saint Vincent/Grenadines Samoa Sao Tome and Principe Saudi Arabia Senegal Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States of America Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Virgins Wallis and Futuna Is West Bank Western Sahara Yemen Yugoslavia Zaire Zambia Zimbabwe
Onion dry 0 0 478 361 0 0 155 0 1227 135 374 516 0 487 442 366 0 0 0 593 105 105 0 147 0 1732 0 946 0 0
Peas Safflower Spinach Sweet potato Artichoke
0
0
Citrus
752 1228
622
5650
226
0
0
185
331
2811
283
775
293
2808
0
0
931
545
387
5644
320
856
1155
0
495
6455
0
1373
2000
0
0 766
0 0 1448 285 0 0 456 0
922
1488
985
877
1712
600
0
1504
381
3000
0
2127
435
0
1240
1240
383
0
742
865
1166
775
0
372
223
141
4057
222
495
0
0
711 459
0
0
0
0
317
415
0
293
0
1259
0
1261
0
598
0 627 728 2247
0
2946
701
0
0
2242
Rice 3515 4060 0 2642 1135 1135 0 0 3199 1143 2328 14655 2366 0 1135 2800 2450 4425 4047 3760 3146 3130 1615 0 7027 2090 2830 1135 1331 1323 2533 1586 2163 4129 3896 11127 5170
Appendix III - p.12
Appendix IV: FAO guidelines on crop water requirements in mm [=10 m3/ha]
Crop Bananas Beans Corn (Maize) Cotton Dates Grains Grapefruit Groundnut Onions Potato Rice Sorghum Soybean Sugar beet Sugarcane Sweet potato Tobacco Tomato Wheat Source: Gleick (1993, p.282-283)
FAO guidelines
Min
Max
700
250
400
550
900
300
650
500
350
350
590
300
450
450
1000
400
300
300
450
1700 500 750 950 1300 450 1000 700 600 625 950 650 825 850 1500 675 500 600 650
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3)
Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAPE VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR.GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995 59.9 105.7 9523.3 2.8 223.9 2.3 7.0 328.0 307.9 2.8 1433.0 863.1 158.1 51.2 144.2 12427.3 86.1 186.0 13948.1 22.1 717.7 235.2 9.8 346.8 88.4 0.0 24.6 16261.0 177.7 102.7 29.6 1.9 266.3 161.2 3982.1 39.8 48.6 0.1 3.2 2735.6 47926.2 0.0 6352.3 13.0 22.8 645.6 4.1 1510.8 754.3 458.5 1052.0 965.6 1136.4 1181.8 102.2 3.1 642.9 1171.1 15892.2 1006.4 0.0 26.8 233.6 512.7 1.0 0.0 68.4 667.4 1.9 8.7 8721.1 63.7 275.8
1996 76.9 665.9 5683.6 1.9 230.5 3.5 9.1 297.1 220.6 6.5 949.1 1413.6 117.3 16.9 114.6 7349.0 81.6 95.1 14172.0 22.0 304.7 69.6 46.5 575.1 154.3 0.1 80.7 26101.0 217.5 657.0 41.8 1.5 85.9 90.0 4565.6 40.6 137.3 2.1 0.0 3316.0 36450.2 1.8 8178.9 43.7 25.3 628.1 0.0 2956.3 322.7 448.6 1248.9 1208.5 1267.0 1234.5 95.4 1.2 578.6 1176.5 16736.0 942.0 0.5 87.5 146.9 257.4 0.5 0.0 125.4 888.4 0.0 17.2 10242.3 113.6 511.5
1997 107.0 240.2 11328.1 3.0 92.4 0.2 15.4 3598.7 510.8 8.2 905.2 1325.0 132.5 23.8 47.3 4940.4 168.8 244.4 15308.7 21.8 269.6 437.4 43.0 668.1 284.6 0.0 187.4 22776.5 287.6 353.7 81.9 0.0 74.8 241.6 5310.6 34.3 188.3 0.0 2.9 2933.7 21541.0 7.5 7905.1 32.7 95.9 140.8 0.0 1688.5 400.8 886.6 869.8 1360.8 1380.4 1270.9 56.5 3.5 791.6 1524.6 17371.4 1308.7 0.1 69.9 1376.6 160.3 1.3 3.1 270.6 1021.0 0.0 16.1 9369.8 83.9 380.3
1998 5.3 256.3 10687.4 2.0 164.6 0.2 0.5 1735.4 182.2 14.0 777.2 1452.3 2112.6 12.0 294.1 15034.2 126.7 2208.3 14878.1 25.4 562.5 28.7 33.0 738.9 409.6 17.2 58.8 25724.2 569.8 155.6 154.9 5.4 132.1 194.0 4882.8 37.9 1.3 6.6 0.1 2983.3 23307.6 0.0 8485.7 46.7 160.1 110.9 0.0 1707.5 1271.6 623.3 1304.4 1192.5 1372.7 1681.0 111.2 0.8 695.7 2460.3 17799.3 923.5 5.4 177.6 823.0 387.9 1.5 0.1 248.4 1047.6 0.0 13.7 9523.1 93.1 367.7
1999 43.4 120.3 11504.2 1.3 157.9 0.1 11.9 1475.5 359.3 3.0 990.4 1352.4 2501.4 18.1 86.6 1772.2 135.2 3545.7 13755.1 21.2 508.4 24.4 0.0 1045.3 242.0 0.0 1.3 24945.1 366.5 167.0 35.0 9.5 91.4 189.8 5331.0 69.3 106.6 0.0 0.7 4344.2 23529.5 0.9 6755.1 60.5 162.9 73.8 0.0 1875.2 1118.3 415.3 937.2 1164.6 1072.1 1544.9 182.2 5.2 950.1 1638.7 16886.5 1530.9 0.3 12.3 574.9 427.4 1.8 0.0 160.5 970.3 0.0 12.2 9025.3 149.3 61.4
Total 292.4 1388.3 49053.2 11.0 869.4 6.4 43.9 7434.7 1580.8 34.6 5055.0 6404.9 5022.0 122.0 686.9 41523.0 598.4 6279.5 72061.9 112.5 2362.8 795.3 132.3 3374.2 1190.0 17.3 352.9 115807.8 1619.1 1441.8 343.2 18.3 650.4 876.6 24072.1 221.8 482.0 8.9 6.8 16312.8 152752.2 10.3 37677.0 196.6 467.0 1599.3 4.2 9738.3 3867.7 2849.3 5412.3 6318.3 6228.6 6913.1 547.5 13.8 3658.8 7971.2 84685.3 5711.5 6.4 374.1 3154.9 1745.7 6.2 3.3 873.0 4594.7 1.9 68.0 46881.6 503.6 1596.6
Appendix Va - p.1
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3)
Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS Hong Kong HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F.ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995 206.8 20653.3 320.2 0.5 2740.6 1.0 29.7 49.4 851.9 93.4 14.7 81.2 363.9 528.8 3182.6 452.6 57.0 595.7 25841.8 5904.1 50.8 813.1 2314.5 19087.4 414.6 55326.2 7731.2 16.4 1998.6 0.1 563.0 19013.1 472.4 270.1 89.0 235.8 767.5 66.9 647.1 588.3 122.7 21.3 547.2 42.4 10337.4 25.4 77.3 306.9 2.9 10.3 160.8 489.5 16237.9 8.8 202.8 16.9 0.0 6838.3 445.8 9.2 14.7 16.1 1.0 128.6 48.3 33476.2 931.3 478.7 206.4 1010.8 0.0 2551.2 1263.4
1996 501.8 23907.8 617.4 0.4 3193.6 0.4 49.7 0.0 1209.5 53.5 14.0 59.1 321.6 625.1 3344.2 539.1 59.7 1517.0 24063.7 5393.2 172.7 877.6 5270.7 19275.5 423.9 60193.5 1196.9 74.6 635.5 0.2 440.1 22870.1 356.0 494.6 127.0 470.8 824.2 168.0 669.6 757.7 124.0 149.6 163.5 13.4 11549.1 14.0 29.7 325.6 2.0 0.0 442.6 658.4 25277.9 14.0 86.7 6.1 0.0 6391.8 219.0 4.9 13.5 0.4 0.0 64.1 94.4 35300.6 971.8 684.4 242.4 4410.2 1.8 2085.8 1097.1
1997 259.3 21815.3 657.0 0.8 3093.2 1.3 30.7 0.0 1120.2 33.4 3.1 71.9 305.2 846.7 3119.5 987.2 66.1 4084.9 18687.4 8339.0 1669.0 886.6 5798.8 20528.5 375.3 63662.0 7585.9 40.6 612.4 0.4 1084.1 23638.2 621.4 84.5 169.4 319.4 635.3 60.5 1273.8 578.1 118.1 294.8 228.6 12.3 12024.4 12.0 35.3 306.9 2.4 0.0 517.3 469.1 22053.6 10.7 21.1 27.7 0.0 6433.2 247.5 31.2 42.6 1.9 0.0 26.6 42.7 37646.8 1144.2 446.7 422.7 7711.9 1.7 1872.5 1198.2
1998 392.1 24692.0 727.2 12.1 3584.7 1.7 32.7 0.0 1186.3 63.0 0.4 47.0 376.3 996.6 3046.2 599.2 68.9 4449.0 28330.4 5144.5 1985.9 1090.5 4895.4 20113.9 368.1 60148.1 3695.0 51.2 922.9 0.4 674.0 23933.4 379.6 54.2 61.5 290.1 560.5 20.9 822.5 394.6 4.3 211.3 265.1 2.8 12571.0 2.0 196.3 294.5 1.9 0.0 676.4 566.9 27729.9 8.0 50.3 41.3 0.2 3743.7 499.9 33.4 14.0 2.8 0.0 18.3 32.2 32509.4 770.4 621.6 658.9 9038.5 0.0 1832.7 1138.5
1999 181.9 25206.0 1034.5 40.6 2977.2 1.8 52.4 0.0 1607.5 167.2 9.4 80.4 578.2 998.4 2864.2 599.8 72.3 1418.6 9907.7 7997.4 1618.1 1061.1 7424.9 19123.8 382.3 58830.0 1425.3 29.2 681.5 0.1 453.6 23458.2 570.2 59.0 23.9 191.1 758.0 21.0 532.5 183.8 115.8 67.7 395.6 58.5 11059.7 4.7 60.6 353.2 1.4 0.0 81.6 639.4 30507.5 5.6 53.1 31.2 0.0 3632.1 272.6 26.8 13.9 4.1 0.0 0.5 42.3 35994.6 1188.8 686.9 17.2 6810.9 0.0 2731.3 1407.1
Total 1541.9 116301.9 3356.2 54.4 15607.0 6.2 195.1 49.4 5975.4 410.5 41.5 339.6 1945.2 3995.5 15556.7 3177.9 324.1 12065.2 106831.0 33115.7 5503.3 4728.9 25940.3 98129.1 1964.2 298159.8 22680.1 209.1 4850.8 1.3 3214.9 112913.0 2488.8 962.3 470.9 1507.0 3880.8 337.3 3945.6 2502.1 484.9 744.8 1600.0 129.4 57541.6 58.1 399.2 1587.2 10.6 10.3 1878.6 2823.4 121806.7 47.1 413.9 123.2 0.2 28089.0 1684.8 105.5 98.7 25.3 1.1 238.1 259.8 175011.7 5003.2 2918.2 1547.6 28982.2 3.5 11073.4 6140.4
Appendix Va - p.2
Appendix Va: Gross virtual water import per country for the years 1995-1999 (106 m3)
Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.IS YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995 2517.0 6.4 422.9 47.1 224.9 4912.5 3712.4 0.0 4579.4 6469.1 48.9 380.5 798.4 2422.6 112.4 8609.4 58.4 0.3 2.6 12240.6 1304.3 17.3 325.9 3889.2 245.2 1266.1 0.6 170.0 21848.7 1404.4 0.0 3.2 1.3 0.0 258.6 30.2 514.7 2224.7 1011.0 7331.2 50.8 719.4 2718.4 599.4 0.0 1.0 805.0 6082.4 6494.9 139.0 0.1 171.8 349.8 2658.5 11994.1 618.7 57.4 23579.1 435.7 0.0 5158.6 173.6 0.0 1421.4 43.9 29.0 121.2 558839.1
1996 2335.3 3.4 520.9 65.0 388.5 5723.8 9576.3 0.0 6740.0 6700.8 36.2 0.0 1086.5 15072.4 119.8 7072.8 54.7 0.9 7.9 14016.2 2721.0 11.5 18.7 3910.3 401.3 1132.8 0.3 334.9 18177.9 206708.4 0.0 5.3 0.9 0.3 561.3 32.4 738.1 2088.1 715.9 7553.6 52.6 924.0 3215.1 388.8 0.0 0.2 842.4 2885.5 11644.9 121.3 0.1 134.0 359.6 1380.1 14326.6 809.4 12.7 26513.8 981.3 0.1 5315.8 100.2 0.0 1947.1 647.3 68.8 49.2 812513.7
1997 4091.0 8.0 595.6 68.9 265.4 5788.4 10949.5 0.2 3099.2 6365.3 55.5 0.0 757.1 17122.9 28.3 6058.6 67.6 0.5 4.2 6480.1 2244.3 20.0 29.7 3785.8 709.7 909.4 0.1 285.4 20299.2 173081.4 0.0 4.1 1.5 0.1 752.0 21.5 729.1 2057.0 672.8 7431.2 60.3 1905.0 4232.1 856.8 0.0 0.0 823.5 3725.7 11974.8 20.5 0.1 69.6 375.3 1710.8 15143.9 670.7 5.6 36844.1 586.7 0.0 5786.9 113.1 0.0 1138.5 715.0 5.9 124.7 792869.1
1998 2125.6 1.2 671.3 48.7 284.4 6215.4 12125.7 0.0 3834.9 7373.0 123.6 0.0 966.1 15768.6 116.1 7186.8 57.2 1.1 0.6 14225.7 3327.1 74.6 23.5 3316.5 325.4 956.5 0.6 557.4 24763.4 52171.3 3.5 17.0 1.6 0.2 1014.1 23.3 851.1 2034.5 648.0 7155.4 59.0 1385.2 4564.2 1223.6 0.0 12.2 593.4 3401.1 12108.4 4.8 0.2 325.0 904.5 2184.9 15099.5 1022.0 1.7 27793.3 607.5 0.1 8063.7 176.6 0.0 1374.4 269.9 12.3 52.6 699989.7
1999 1666.5 1.1 488.5 14.9 551.6 5191.5 4562.2 0.0 2797.6 6882.0 32.2 0.0 740.6 22286.2 88.4 5710.5 43.4 0.6 1.9 5063.8 3805.2 15.5 18.3 4294.7 251.6 1049.7 1.3 151.1 25533.8 3269.8 4.0 6.7 0.7 0.0 220.4 30.4 853.4 2090.4 1375.0 6524.2 10.7 1124.2 5760.1 1189.2 0.0 5.3 333.8 2932.1 9264.8 1.5 0.3 343.6 355.1 2241.9 14454.6 988.2 14.5 31591.3 52.7 0.1 6928.9 205.1 0.0 1363.0 87.6 57.9 231.1 600677.0
Total 12735.3 20.1 2699.2 244.5 1714.9 27831.6 41033.6 0.2 21050.6 33790.2 296.4 380.5 4388.4 72672.6 465.0 34638.1 281.3 3.4 17.1 56566.6 13401.9 138.9 416.2 19196.2 1933.2 5314.4 3.0 1498.7 110623.1 436635.3 7.5 36.4 6.1 0.6 2806.3 137.7 3686.4 10494.6 4422.7 35995.5 233.4 6057.7 20489.8 4257.8 0.0 18.7 3398.1 19625.6 51487.8 287.1 0.9 1043.9 2344.3 10546.8 71020.6 4109.0 91.9 146321.5 2663.7 0.3 31253.9 768.8 0.0 7244.5 1763.6 173.9 578.9 3474587.7
Appendix Va - p.3
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3)
Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN.IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAP VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR. GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995 31.4 6.2 0.2 0.0 0.0 0.0 0.0 37070.2 0.0 0.0 14702.5 918.1 0.0 38.8 0.0 36.7 8.3 43.6 2218.1 50.4 620.9 36.8 0.0 1755.6 5.8 0.0 0.0 18204.4 0.0 1230.6 39.2 0.4 65.5 176.3 59311.3 0.0 1.2 1.0 0.0 1227.0 5703.9 0.0 752.3 0.1 5.1 9.8 0.0 560.2 173.0 624.7 849.4 262.6 1746.2 2211.0 0.0 662.6 1833.0 1684.2 590.3 88.4 0.0 0.0 39.7 26.0 0.0 0.0 0.0 1098.7 0.0 0.0 27178.3 0.0 125.6
1996 122.1 11.4 25.2 0.0 0.0 0.0 0.0 45187.6 0.1 0.0 43171.3 649.6 34.7 57.8 0.0 5162.7 15.0 6.0 1978.1 55.2 1031.0 4.5 0.0 1977.2 283.9 0.0 0.0 20261.8 0.0 413.2 8.6 0.5 23.7 190.2 58122.6 0.0 0.0 0.4 0.0 1266.4 4456.6 0.0 794.0 0.0 2.7 9.0 0.0 1007.0 47.1 621.0 1322.9 278.3 418.5 1707.3 0.0 801.1 2823.0 2285.9 1457.3 78.4 0.0 0.0 16.1 39.3 0.0 0.0 0.0 972.2 0.0 0.0 24851.6 0.0 165.0
1997 979.7 37.1 0.4 0.0 0.0 0.0 0.0 40267.0 2.1 0.0 35407.8 978.2 21.9 135.9 0.0 1017.0 30.7 6.9 2836.2 107.3 1160.3 0.4 0.0 1781.7 14.0 0.0 0.0 38566.1 0.0 226.1 46.2 0.0 31.2 157.5 71206.1 0.0 18.1 0.5 0.0 1188.1 12851.5 0.0 900.2 0.0 10.5 3.6 0.0 573.2 33.7 115.4 1770.5 131.9 173.0 1923.1 0.9 738.0 4581.4 2872.0 648.8 106.9 0.0 1.2 96.7 24.7 0.0 0.0 0.0 1343.6 0.0 0.0 26509.0 0.3 88.3
1998 154.3 12.6 5.5 0.0 0.0 0.0 0.0 59010.8 23.4 0.0 31600.0 1189.0 26.7 104.6 0.0 6592.4 23.9 64.7 2671.9 60.5 1753.0 55.1 0.0 1481.9 13.7 0.0 0.0 40859.8 0.0 815.9 2628.3 0.3 2.5 163.3 56989.1 0.0 0.0 0.8 0.0 1189.6 15344.9 0.0 883.0 0.0 5.7 1.6 0.0 637.3 112.7 227.6 1170.5 143.0 338.7 1840.1 0.0 334.7 2700.5 1835.9 1099.5 77.0 0.0 0.0 276.5 9.5 0.0 0.0 0.0 1221.9 0.0 0.0 26532.0 3.1 440.6
1999 150.1 4.9 3.3 0.0 27.5 0.0 0.0 52241.1 2.2 0.0 25782.5 1145.4 66.8 36.3 1.2 4.1 9.5 54.0 2780.8 265.4 823.9 25.4 0.0 1664.2 1.4 0.0 0.0 42916.8 0.1 1113.0 2144.5 0.0 15.4 252.5 50913.0 0.0 0.0 11.8 0.0 1184.7 12217.5 0.0 996.4 0.0 10.1 0.7 0.0 672.2 51.3 141.2 1406.8 178.6 1129.7 1536.7 0.0 568.5 1381.5 2244.1 711.9 122.4 0.0 0.0 73.1 14.0 0.0 0.0 0.0 822.5 0.0 0.0 30186.4 0.0 1.6
Total 1437.6 72.2 34.6 0.0 27.5 0.0 0.0 233776.8 27.7 0.0 150651.5 4880.3 150.1 373.3 1.2 12813.0 87.3 175.2 12485.1 538.9 5389.1 122.2 0.0 8660.5 318.8 0.0 0.0 160808.8 0.1 3798.7 4866.8 1.3 138.4 939.7 296542.0 0.0 19.3 14.5 0.0 6055.8 50574.4 0.0 4325.8 0.1 34.1 24.7 0.0 3450.0 417.7 1729.8 6520.0 994.4 3806.1 9218.2 0.9 3104.9 13319.5 10922.1 4507.8 473.1 0.0 1.3 502.1 113.4 0.0 0.0 0.0 5459.0 0.0 0.0 135257.2 3.5 821.1
Appendix Vb - p.1
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3)
Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS HONG KONG HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F. ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995 0.0 8425.5 91.4 0.0 5728.8 0.0 32.0 31.3 1735.4 21.5 6.4 95.3 0.0 209.9 241.7 5988.5 0.9 25203.5 730.8 409.7 0.0 137.6 271.5 6380.9 143.3 128.7 102.3 674.0 331.6 0.0 1.7 48.8 0.2 126.7 2.7 11.5 40.5 0.0 36.7 145.7 0.9 53.1 97.7 429.7 350.7 0.0 9.9 20.9 0.0 59.5 0.0 242.1 3804.7 0.0 412.5 44.0 55.8 128.4 69.4 1486.4 0.0 0.0 0.0 0.0 0.0 4164.9 86.1 310.4 100.1 190.6 0.0 13.5 105.0
1996 1.7 10269.3 95.6 0.0 5235.5 0.0 0.5 0.0 1658.0 19.5 6.2 101.2 0.0 343.0 840.8 2501.5 0.2 85625.4 738.8 1221.6 0.1 154.1 644.3 7035.1 163.1 40.2 7.1 8164.1 320.4 0.0 1.7 38.9 0.1 245.2 0.8 18.7 39.2 0.0 25.6 130.7 0.6 146.4 176.2 926.6 2579.4 0.0 7.5 114.5 0.0 0.0 0.2 317.7 11384.8 0.0 205.0 0.0 104.6 88.7 103.0 1141.4 0.0 0.0 0.0 1.7 0.0 4204.1 92.2 330.8 137.8 777.6 0.0 20.6 93.2
1997 82.7 8246.2 172.9 0.0 5486.3 0.0 0.9 0.0 69278.5 27.5 8.8 250.3 0.0 438.4 16.2 3897.5 6.8 28994.7 772.4 504.7 0.1 298.6 651.9 6948.7 143.4 79.7 122.6 10937.1 52.7 0.0 7.3 35.3 0.0 93.9 0.6 101.1 14.2 0.0 31.3 329.5 0.9 122.0 245.4 883.0 1313.1 0.0 16.8 39.0 0.0 0.0 2.9 271.5 32768.8 0.0 213.1 0.0 32.8 95.8 67.6 12430.4 0.0 0.0 0.0 2.7 0.0 5069.3 131.2 462.6 137.4 127.4 0.0 7.9 122.9
1998 239.1 13410.9 364.6 0.0 3571.3 0.0 0.2 0.0 2527.4 52.7 5.5 351.8 0.2 328.7 38.6 6388.1 0.0 29101.4 2538.3 1259.0 16.2 287.3 682.3 6751.3 126.1 498.0 31.3 8188.2 69.0 0.0 0.4 80.5 0.0 133.2 0.9 37.9 44.9 8.7 66.4 513.7 0.0 121.8 72.3 849.2 621.3 0.0 39.2 27.2 0.0 0.0 0.0 291.6 24973.8 0.0 323.6 0.0 7.3 51.1 130.9 2044.7 0.0 0.0 0.0 90.5 0.0 6546.6 153.0 251.0 163.6 194.2 0.0 8.2 141.6
1999 191.3 8004.7 362.8 0.0 5418.0 0.0 2.1 0.0 2483.5 83.1 0.0 334.4 0.0 338.7 77.8 4104.6 0.1 4136.6 915.6 622.1 0.0 131.8 699.3 6694.4 110.5 195.5 11.6 11416.4 74.6 0.0 0.0 141.5 0.0 127.0 3.5 97.5 8.3 0.0 67.0 800.1 0.1 46.1 67.1 844.7 1415.3 0.0 0.9 26.8 0.0 0.0 0.0 251.7 3941.3 0.0 1123.3 9.0 0.0 72.8 54.5 403.7 0.0 0.0 0.0 0.0 0.0 7328.3 103.1 310.8 0.7 3382.4 0.0 5.2 135.2
Total 514.8 48356.6 1087.3 0.0 25439.8 0.0 42.7 31.3 77682.8 204.4 26.9 1132.9 0.2 1658.7 1215.1 22948.1 7.9 173061.6 5695.9 4017.1 16.4 1009.3 2949.3 33810.3 686.5 942.0 275.0 39379.8 848.3 0.0 11.1 345.1 0.3 726.1 8.6 266.8 147.0 8.7 227.0 1919.7 2.5 489.3 658.6 3933.2 6279.7 0.0 74.3 228.5 0.0 59.5 3.1 1374.6 76873.4 0.0 2277.5 50.7 200.5 436.8 425.3 17506.6 0.0 0.0 0.0 95.0 0.0 27313.0 565.6 1665.5 539.7 4672.1 0.0 55.4 597.9
Appendix Vb - p.2
Appendix Vb. Gross virtual water export per country in the years 1995-1999 (106 m3)
Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.I YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995 2945.8 0.0 357.8 17.1 7138.7 123.2 4366.0 0.0 281.6 315.8 0.1 68.7 1538.0 6422.8 0.7 2275.5 0.0 1.7 0.0 1999.5 21.8 0.0 2.1 291.4 1394.0 11.1 1.3 32.3 4459.8 71.3 0.0 5.8 1254.2 0.0 5417.3 60.9 735.7 186.2 9486.6 259.8 1.5 109.9 41728.1 0.9 0.0 0.0 98.3 34.4 5217.1 0.0 0.0 510.0 2128.8 376.8 5614.5 1617.1 0.0 191579.1 1.6 0.0 1125.8 2770.0 1.4 5.5 45.4 67.0 461.6 558839.1
1996 2756.1 0.0 314.3 22.2 8439.5 111.7 9633.0 0.0 218.4 272.3 0.0 0.0 3647.7 16476.2 0.0 3487.6 0.0 1.4 0.0 123.9 65.4 0.0 0.2 301.4 449.3 9.3 0.3 36.0 6038.5 3052.5 0.0 4.8 1335.7 0.0 511.8 130.1 1352.5 124.5 2610.1 208.0 69.0 141.8 90840.7 208.9 0.0 0.0 167.2 61.4 4154.0 0.2 0.0 647.8 6624.3 246.4 6313.7 5672.3 0.0 195159.6 103.7 0.0 2831.3 62568.1 0.0 11.4 1312.3 79.2 708.7 812513.7
1997 1862.2 0.0 392.7 21.2 11766.6 129.9 8821.6 0.0 357.9 718.0 0.0 0.0 1744.5 12951.4 0.0 2537.4 0.0 1.1 0.0 14.8 57.8 0.0 0.2 712.4 515.3 16.4 3.1 31.0 5945.0 2613.8 0.0 9.1 884.0 0.0 381.4 147.5 1922.6 133.4 10175.2 102.1 124.5 358.4 37361.8 1.7 0.0 0.1 116.1 86.8 4430.0 1.5 0.0 35.5 6344.1 409.7 52929.6 3413.9 0.0 172422.8 296.5 0.0 969.2 3048.8 0.0 0.0 223.1 199.0 806.4 792869.1
1998 3585.7 0.0 292.1 21.5 5593.9 263.9 8950.6 0.0 444.7 489.8 0.0 0.0 2620.5 17448.4 0.0 1597.9 0.0 0.6 0.0 32.8 42.2 0.0 0.2 695.8 1160.7 45.7 3.7 14.0 5661.1 2411.4 0.0 6.8 899.5 0.0 946.0 135.5 2091.1 176.2 3949.5 151.5 143.4 391.2 44381.4 428.0 0.0 0.0 44.9 98.4 9058.6 0.8 0.0 190.1 9397.9 507.1 6408.6 2668.7 0.0 165017.7 118.5 0.0 1228.9 21001.7 0.0 40.5 707.5 212.6 663.2 699989.7
1999 1634.3 0.0 298.7 20.0 10901.7 89.0 4438.9 0.0 959.4 853.6 0.0 0.0 3955.3 7104.9 0.0 2893.3 0.0 0.9 0.0 4.8 30.6 0.0 0.5 174.9 1367.6 26.4 1.3 0.0 6000.8 19.5 0.0 5.1 837.5 0.0 1305.2 98.5 1783.9 192.0 94.5 112.3 80.2 415.9 39504.7 434.3 0.0 0.0 26.5 7.8 8717.4 0.4 0.0 90.5 9668.0 550.5 4606.1 2744.5 0.0 180442.5 98.2 0.0 470.7 1539.9 0.0 0.0 153.2 106.9 526.4 600677.0
Total 12784.2 0.0 1655.6 102.1 43840.4 717.7 36210.1 0.0 2262.1 2649.5 0.1 68.7 13506.1 60397.9 0.8 12791.7 0.0 5.7 0.0 2175.9 217.9 0.0 3.2 2175.8 4887.0 109.0 9.7 113.4 28105.2 8168.6 0.0 31.7 5210.9 0.0 8561.7 572.5 7885.8 812.3 26315.8 833.7 418.6 1417.3 253816.7 1073.9 0.0 0.1 453.0 288.8 41222.2 2.8 0.0 1473.8 34163.1 2090.5 75872.5 16116.4 0.0 904621.7 618.5 0.0 6625.9 90928.5 1.4 57.3 2441.5 664.6 3166.4 3474587.7
Appendix Vb - p.3
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3)
Country AFGHANISTAN ALBANIA ALGERIA ANDORRA ANGOLA ANGUILLA ANTIGUA BARB ARGENTINA ARMENIA ARUBA AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS BAHRAIN BANGLADESH BARBADOS BELARUS BELGIUM-LUX BELIZE BENIN BERMUDA BHUTAN BOLIVIA BOSNIA HERZG BRITISH INDIAN OCEAN TER BR.VIRGIN.IS BRAZIL BRUNEI DAR. BULGARIA BURKINA FASO BURUNDI CAMBODIA CAMEROON CANADA CAP VERDE CAYMAN ISLDS CENT.AF.REP CHAD CHILE CHINA COCOS ISLNDS COLOMBIA COMOROS CONGO CONGO, D.R. COOK ISLANDS COSTA RICA COTE DIVOIRE CROATIA CUBA CYPRUS CZECH REP DENMARK DJIBOUTI DOMINICA DOMINICAN RP ECUADOR EGYPT EL SALVADOR EQ.GUINEA ERITREA ESTONIA ETHIOPIA FAEROE ISLDS FALKLAND ISL FIJI FINLAND FR. GUIANA FR.POLYNESIA FRANCE GABON GAMBIA
1995 28.5 99.5 9523.2 2.8 223.9 2.3 7.0 -36742.2 307.9 2.8 -13269.4 -55.0 158.1 12.5 144.2 12390.5 77.9 142.4 11730.1 -28.3 96.8 198.4 9.8 -1408.7 82.5 0.0 24.6 -1943.3 177.7 -1127.9 -9.6 1.5 200.8 -15.1 -55329.2 39.8 47.3 -0.9 3.2 1508.6 42222.3 0.0 5600.0 12.9 17.7 635.9 4.1 950.6 581.3 -166.2 202.6 703.0 -609.8 -1029.3 102.2 -659.5 -1190.1 -513.1 15301.9 918.0 0.0 26.8 193.9 486.7 1.0 0.0 68.4 -431.4 1.9 8.7 -18457.2 63.7 150.2
1996 -45.2 654.4 5658.4 1.9 230.5 3.5 9.1 -44890.5 220.5 6.5 -42222.2 764.0 82.6 -40.9 114.6 2186.3 66.7 89.1 12193.9 -33.2 -726.3 65.1 46.5 -1402.1 -129.6 0.1 80.7 5839.2 217.5 243.8 33.2 1.0 62.1 -100.1 -53557.0 40.6 137.3 1.7 0.0 2049.6 31993.6 1.8 7384.9 43.7 22.6 619.1 0.0 1949.4 275.7 -172.4 -73.9 930.2 848.5 -472.8 95.4 -799.9 -2244.4 -1109.4 15278.7 863.6 0.5 87.5 130.8 218.1 0.5 0.0 125.4 -83.7 0.0 17.2 -14609.3 113.6 346.5
1997 -872.8 203.2 11327.7 3.0 92.4 0.2 15.4 -36668.3 508.8 8.2 -34502.6 346.9 110.6 -112.1 47.3 3923.4 138.0 237.5 12472.4 -85.5 -890.7 437.1 43.0 -1113.6 270.6 0.0 187.4 -15789.6 287.6 127.6 35.7 0.0 43.6 84.2 -65895.5 34.3 170.2 -0.5 2.9 1745.5 8689.5 7.5 7004.9 32.7 85.5 137.2 0.0 1115.3 367.1 771.2 -900.6 1228.9 1207.5 -652.2 55.6 -734.5 -3789.8 -1347.4 16722.6 1201.9 0.1 68.7 1279.9 135.6 1.3 3.1 270.6 -322.6 0.0 16.1 -17139.2 83.6 292.0
1998 -149.0 243.7 10681.9 2.0 164.6 0.2 0.5 -57275.4 158.8 14.0 -30822.8 263.3 2085.9 -92.6 294.1 8441.8 102.8 2143.6 12206.2 -35.1 -1190.6 -26.4 33.0 -742.9 395.9 17.2 58.8 -15135.6 569.8 -660.3 -2473.4 5.1 129.6 30.7 -52106.3 37.9 1.3 5.9 0.1 1793.7 7962.6 0.0 7602.7 46.7 154.4 109.3 0.0 1070.2 1159.0 395.7 133.9 1049.5 1034.0 -159.0 111.2 -333.9 -2004.8 624.4 16699.8 846.5 5.4 177.6 546.5 378.5 1.5 0.1 248.4 -174.3 0.0 13.7 -17008.9 89.9 -72.9
1999 -106.7 115.4 11500.9 1.3 130.3 0.1 11.9 -50765.7 357.0 3.0 -24792.1 206.9 2434.6 -18.2 85.3 1768.0 125.7 3491.7 10974.3 -244.2 -315.5 -1.0 0.0 -618.9 240.6 0.0 1.3 -17971.8 366.3 -946.0 -2109.5 9.5 76.0 -62.7 -45582.0 69.3 106.6 -11.8 0.7 3159.5 11312.0 0.9 5758.7 60.5 152.8 73.1 0.0 1203.0 1067.0 274.2 -469.6 986.0 -57.6 8.2 182.2 -563.3 -431.5 -605.5 16174.5 1408.5 0.3 12.3 501.8 413.3 1.8 0.0 160.5 147.8 0.0 12.2 -21161.0 149.3 59.8
Total -1145.2 1316.2 49018.6 11.0 841.8 6.4 43.9 -226342.0 1553.0 34.6 -145596.6 1524.6 4871.8 -251.3 685.6 28710.0 511.0 6104.3 59576.8 -426.3 -3026.3 673.1 132.3 -5286.3 871.2 17.3 352.9 -45001.1 1619.0 -2357.0 -4523.6 17.1 512.0 -63.0 -272470.0 221.8 462.7 -5.6 6.8 10256.9 102177.8 10.3 33351.2 196.5 433.0 1574.6 4.2 6288.4 3450.0 1119.5 -1107.6 5323.9 2422.5 -2305.1 546.6 -3091.1 -9660.7 -2950.9 80177.5 5238.4 6.4 372.9 2652.9 1632.2 6.2 3.3 873.0 -864.3 1.9 68.0 -88375.7 500.1 775.5
Appendix Vc - p.1
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3)
Country GEORGIA GERMANY GHANA GIBRALTAR GREECE GREENLAND GRENADA GUADELOUPE GUATEMALA GUINEA GUINEABISSAU GUYANA HAITI HONDURAS HONG KONG HUNGARY ICELAND INDIA INDONESIA IRAN (ISLM.R) IRAQ IRELAND ISRAEL ITALY JAMAICA JAPAN JORDAN KAZAKHSTAN KENYA KIRIBATI KOREA D P RP KOREA REP. KUWAIT KYRGYZSTAN LAO P.DEM.R LATVIA LEBANON LIBERIA LIBYA LITHUANIA MACAU MACEDONIA, TFYR MADAGASCAR MALAWI MALAYSIA MALDIVES MALI MALTA MARSHALL IS. MARTINIQUE MAURITANIA MAURITIUS MEXICO MICRON, F. ST MOLDOVA REP. MONGOLIA MONTSERRAT MOROCCO MOZAMBIQUE MYANMAR N.CALEDONIA N.MARIANA NAURU NEPAL NETH.ANTILES NETHERLANDS NEW ZEALAND NICARAGUA NIGER NIGERIA NORFOLK ISLD NORWAY OMAN
1995 206.8 12227.8 228.8 0.5 -2988.3 1.0 -2.4 18.1 -883.5 71.9 8.2 -14.1 363.9 319.0 2940.9 -5535.9 56.0 -24607.8 25111.0 5494.4 50.8 675.5 2043.0 12706.5 271.3 55197.5 7628.9 -657.7 1667.0 0.1 561.3 18964.3 472.2 143.4 86.3 224.3 727.0 66.9 610.3 442.6 121.9 -31.8 449.6 -387.4 9986.7 25.4 67.5 285.9 2.9 -49.3 160.8 247.4 12433.2 8.8 -209.7 -27.1 -55.8 6709.9 376.4 -1477.2 14.7 16.1 1.0 128.5 48.3 29311.3 845.2 168.3 106.3 820.2 0.0 2537.7 1158.5
1996 500.1 13638.5 521.8 0.4 -2041.9 0.4 49.2 0.0 -448.6 34.0 7.8 -42.1 321.6 282.1 2503.4 -1962.4 59.6 -84108.3 23324.8 4171.6 172.6 723.5 4626.4 12240.5 260.7 60153.3 1189.8 -8089.5 315.0 0.2 438.5 22831.2 355.8 249.4 126.2 452.1 785.1 168.0 644.0 627.0 123.4 3.3 -12.7 -913.1 8969.7 14.0 22.3 211.2 2.0 0.0 442.4 340.8 13893.1 14.0 -118.4 6.1 -104.6 6303.1 116.0 -1136.5 13.5 0.4 0.0 62.4 94.4 31096.6 879.6 353.6 104.5 3632.5 1.8 2065.3 1003.9
1997 176.7 13569.1 484.1 0.8 -2393.1 1.3 29.9 0.0 -68158.3 5.9 -5.7 -178.3 305.2 408.2 3103.4 -2910.3 59.3 -24909.9 17915.1 7834.3 1669.0 588.0 5146.9 13579.9 231.9 63582.2 7463.3 -10896.5 559.6 0.4 1076.8 23602.8 621.4 -9.4 168.8 218.3 621.1 60.5 1242.5 248.6 117.2 172.8 -16.8 -870.7 10711.3 12.0 18.4 267.8 2.4 0.0 514.4 197.6 -10715.2 10.7 -192.0 27.7 -32.8 6337.4 179.9 -12399.3 42.6 1.9 0.0 24.0 42.7 32577.5 1013.0 -15.9 285.3 7584.5 1.7 1864.6 1075.4
1998 153.0 11281.1 362.7 12.1 13.4 1.7 32.4 0.0 -1341.1 10.2 -5.1 -304.8 376.1 667.9 3007.6 -5788.9 68.9 -24652.4 25792.0 3885.5 1969.8 803.2 4213.1 13362.6 242.0 59650.2 3663.7 -8137.0 853.9 0.4 673.6 23852.9 379.6 -79.0 60.6 252.2 515.7 12.2 756.2 -119.1 4.3 89.5 192.8 -846.3 11949.8 2.0 157.1 267.3 1.9 0.0 676.4 275.2 2756.1 8.0 -273.3 41.3 -7.1 3692.6 369.1 -2011.3 14.0 2.8 0.0 -72.2 32.2 25962.8 617.4 370.6 495.3 8844.3 0.0 1824.5 996.9
1999 -9.4 17201.3 671.7 40.6 -2440.8 1.8 50.3 0.0 -876.0 84.0 9.4 -254.0 578.2 659.7 2786.4 -3504.8 72.2 -2718.0 8992.2 7375.3 1618.1 929.4 6725.6 12429.4 271.8 58634.5 1413.7 -11387.2 606.9 0.1 453.6 23316.7 570.2 -68.1 20.5 93.6 749.7 21.0 465.5 -616.3 115.7 21.7 328.5 -786.3 9644.4 4.7 59.6 326.4 1.4 0.0 81.6 387.7 26566.2 5.6 -1070.2 22.2 0.0 3559.3 218.1 -376.9 13.9 4.1 0.0 0.5 42.3 28666.4 1085.7 376.1 16.5 3428.5 0.0 2726.1 1271.9
Total 1027.2 67945.3 2268.9 54.4 -9832.8 6.2 152.5 18.1 -71707.4 206.1 14.5 -793.3 1945.1 2336.8 14341.7 -19770.2 316.2 -160996.4 101135.1 29098.6 5487.0 3719.6 22991.0 64318.7 1277.7 297217.8 22405.1 -39170.8 4002.5 1.3 3203.8 112567.9 2488.5 236.3 462.4 1240.2 3733.8 328.6 3718.6 582.4 482.4 255.5 941.4 -3803.8 51261.8 58.1 325.0 1358.6 10.6 -49.3 1875.6 1448.7 44933.3 47.1 -1863.6 72.5 -200.3 27652.1 1259.5 -17401.1 98.7 25.3 1.1 143.1 259.8 147698.7 4437.6 1252.7 1007.9 24310.1 3.5 11018.1 5542.5
Appendix Vc - p.2
Appendix Vc. Net virtual water import per country in the years 1995-1999 (106 m3)
Country PAKISTAN PALAU PANAMA PAPUA N.GUIN PARAGUAY PERU PHILIPPINES PITCAIRN POLAND PORTUGAL QATAR REUNION ROMANIA RUSSIAN FED RWANDA S.AFR.CUS.UN S.VINCENT-GR SAMOA SAO TOME PRN SAUDI ARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SLOVAKIA SLOVENIA SOLOMON ISLS SOMALIA SPAIN SRI LANKA ST.HELENA ST.KITTS NEV ST.LUCIA ST.PIER.MIQU SUDAN SURINAME SWEDEN SWITZ.LIECHT SYRIA A. R. TAIWAN (POC) TAJIKISTAN TANZANIA, U.R THAILAND TOGO TOKELAU TONGA TRINIDAD TBG TUNISIA TURKEY TURKMENISTAN TURKS CA.ISL UGANDA UKRAINE UNTD ARAB EM UNTD KINGDOM URUGUAY US MSC.PACIFIC USA UZBEKISTAN VANUATU VENEZUELA VIET NAM WALLIS FUT.I YEMEN YUGOSLAVIA ZAMBIA ZIMBABWE Grand Total
1995 -428.9 6.4 65.1 30.0 -6913.9 4789.3 -653.6 0.0 4297.7 6153.3 48.8 311.8 -739.5 -4000.2 111.7 6333.9 58.4 -1.4 2.6 10241.1 1282.5 17.3 323.8 3597.8 -1148.8 1254.9 -0.8 137.7 17388.9 1333.1 0.0 -2.6 -1252.8 0.0 -5158.7 -30.8 -221.1 2038.5 -8475.6 7071.4 49.3 609.5 -39009.7 598.5 0.0 1.0 706.7 6048.0 1277.8 139.0 0.1 -338.3 -1778.9 2281.6 6379.6 -998.4 57.4 -168000.0 434.2 0.0 4032.8 -2596.4 -1.4 1415.9 -1.5 -37.9 -340.4 0.0
1996 -420.9 3.4 206.6 42.8 -8050.9 5612.1 -56.7 0.0 6521.6 6428.5 36.2 0.0 -2561.2 -1403.8 119.8 3585.2 54.7 -0.5 7.9 13892.3 2655.6 11.5 18.6 3608.9 -48.0 1123.5 0.0 298.9 12139.4 203655.9 0.0 0.5 -1334.8 0.3 49.6 -97.7 -614.4 1963.5 -1894.2 7345.6 -16.3 782.2 -87625.6 179.9 0.0 0.2 675.3 2824.1 7491.0 121.1 0.1 -513.8 -6264.7 1133.7 8012.9 -4862.9 12.7 -168645.8 877.6 0.1 2484.4 -62467.8 0.0 1935.7 -665.0 -10.4 -659.5 0.0
1997 2228.8 8.0 202.9 47.6 -11501.1 5658.4 2127.9 0.2 2741.4 5647.3 55.5 0.0 -987.4 4171.4 28.3 3521.2 67.6 -0.6 4.2 6465.3 2186.5 20.0 29.5 3073.4 194.4 892.9 -2.9 254.4 14354.2 170467.6 0.0 -5.0 -882.5 0.1 370.5 -126.0 -1193.5 1923.6 -9502.4 7329.1 -64.3 1546.5 -33129.7 855.1 0.0 0.0 707.4 3639.0 7544.8 18.9 0.1 34.1 -5968.8 1301.1 -37785.8 -2743.2 5.6 -135578.8 290.2 0.0 4817.7 -2935.6 0.0 1138.5 491.9 -193.1 -681.7 0.0
1998 -1460.2 1.2 379.2 27.2 -5309.5 5951.6 3175.1 0.0 3390.2 6883.3 123.6 0.0 -1654.4 -1679.8 116.1 5588.9 57.2 0.4 0.6 14192.9 3285.0 74.6 23.3 2620.7 -835.4 910.8 -3.1 543.3 19102.3 49759.9 3.5 10.2 -897.9 0.2 68.1 -112.2 -1240.0 1858.3 -3301.5 7003.9 -84.5 994.0 -39817.2 795.6 0.0 12.2 548.5 3302.7 3049.8 4.1 0.2 134.9 -8493.4 1677.8 8690.9 -1646.7 1.7 -137224.4 489.0 0.1 6834.8 -20825.0 0.0 1333.9 -437.6 -200.3 -610.6 0.0
1999 32.2 1.1 189.8 -5.2 -10350.0 5102.5 123.3 0.0 1838.2 6028.4 32.2 0.0 -3214.8 15181.3 88.3 2817.2 43.4 -0.3 1.9 5058.9 3774.6 15.5 17.8 4119.8 -1116.0 1023.3 0.0 151.1 19533.0 3250.2 4.0 1.6 -836.8 0.0 -1084.9 -68.1 -930.5 1898.3 1280.5 6411.9 -69.6 708.3 -33744.6 754.9 0.0 5.3 307.2 2924.3 547.4 1.1 0.3 253.1 -9312.9 1691.4 9848.5 -1756.3 14.5 -148851.2 -45.5 0.1 6458.2 -1334.8 0.0 1363.0 -65.6 -49.0 -295.3 0.0
Total -48.9 20.1 1043.6 142.4 -42125.5 27113.9 4823.5 0.2 18788.6 31140.7 296.3 311.8 -9117.7 12274.7 464.3 21846.4 281.3 -2.3 17.1 54390.7 13184.0 138.9 413.0 17020.4 -2953.8 5205.4 -6.7 1385.4 82517.9 428466.7 7.5 4.7 -5204.8 0.6 -5755.3 -434.7 -4199.5 9682.3 -21893.2 35161.9 -185.3 4640.5 -233326.9 3183.9 0.0 18.6 2945.1 19336.8 10265.6 284.3 0.9 -430.0 -31818.9 8456.2 -4852.0 -12007.5 91.9 -758300.2 2045.2 0.3 24628.0 -90159.7 -1.4 7187.1 -677.8 -490.7 -2587.5 0.0
Appendix Vc - p.3
Appendix VI. Classification of countries into thirteen world regions
Central Africa BURUNDI CAMEROON CENT.AF.REP COMOROS CONGO CONGO, D.R. EQ.GUINEA GABON KENYA RWANDA SAO TOME PRN SEYCHELLES TANZANIA, U.R UGANDA Central America ANGUILLA ANTIGUA BARB ARUBA BAHAMAS BARBADOS BELIZE BR.VIRGIN.IS CAYMAN ISLDS COSTA RICA CUBA DOMINICA DOMINICAN RP EL SALVADOR GRENADA GUADELOUPE GUATEMALA HAITI HONDURAS JAMAICA MARTINIQUE MEXICO MONTSERRAT NETH.ANTILES NICARAGUA PANAMA S.VINCENT-GR ST.KITTS NEV ST.LUCIA TRINIDAD TBG TURKS CA.ISL US.MSC.PAC
Central and South Asia AFGHANISTAN BERMUDA BHUTAN CHINA HONG KONG INDIA JAPAN KOREA D P RP KOREA REP. MACAU MALDIVES MONGOLIA NEPAL PAKISTAN SRI LANKA TAIWAN (POC) Eastern Europe ALBANIA BOSNIA HERZG BULGARIA CROATIA CYPRUS CZECH REP ESTONIA GREECE HUNGARY LATVIA LITHUANIA MACEDONIA, TFYR POLAND ROMANIA SLOVAKIA SLOVENIA YUGOSLAVIA Middle East BAHRAIN IRAN (ISLM.R) IRAQ ISRAEL JORDAN KUWAIT LEBANON OMAN QATAR SAUDI ARABIA SYRIA A. R.
TURKEY
NAURU
UNTD ARAB EM
NEW ZEALAND
YEMEN
NORFOLK ISLD
North Africa
PALAU
ALGERIA
PAPUA N.GUIN
BENIN
PITCAIRN
BURKINA FASO
SAMOA
CAP VERDE
SOLOMON ISLS
CHAD
TOKELAU
COTE DIVOIRE
TONGA
DJIBOUTI
VANUATU
EGYPT
WALLIS FUT.I
ERITREA
FSU
ETHIOPIA
ARMENIA
GAMBIA
AZERBAIJAN
GHANA
BELARUS
GUINEA
GEORGIA
GUINEABISSAU
KAZAKSTAN
LIBERIA
KYRGYZSTAN
LIBYA
MOLDOVA REP.
MALI
RUSSIAN FED
MAURITANIA
TAJIKISTAN
MOROCCO
TURKMENISTAN
NIGER
UKRAINE
NIGERIA
UZBEKISTAN
SENEGAL
South Africa
SIERRA LEONE
ANGOLA
SOMALIA
MADAGASCAR
SUDAN
MALAWI
TOGO
MAURITIUS
TUNISIA
MOZAMBIQUE
North America
REUNION
CANADA
S.AFR.CUS.UN
ST.PIERRE & MIQUELON ST.HELENA
USA,PR,USVI
ZAMBIA
Oceania
ZIMBABWE
AUSTRALIA
South America
BR.IND.OC.TR
ARGENTINA
COCOS ISLNDS
BOLIVIA
COOK ISLANDS
BRAZIL
FIJI
CHILE
FR.POLYNESIA
COLOMBIA
KIRIBATI
ECUADOR
MARSHALL IS.
FALKLAND ISL
MICRON, F. ST
FR. GUIANA
N.CALEDONIA
GUYANA
N.MARIANA
PARAGUAY
PERU SURINAME URUGUAY VENEZUELA South east Asia BANGLADESH BRUNEI DAR. CAMBODIA INDONESIA LAO P.DEM.R MALAYSIA MYANMAR PHILIPPINES SINGAPORE THAILAND VIET NAM Western Europe ANDORRA AUSTRIA BELGIUM-LUX DENMARK FAEROE ISLDS FINLAND FRANCE GERMANY GIBRALTAR GREENLAND ICELAND IRELAND ITALY MALTA NETHERLANDS NORWAY PORTUGAL SPAIN SWEDEN SWITZ.LIECHT UNTD KINGDOM
Appendix VII. Gross virtual water trade between and within regions (Gm3)
Year Exporter
Importer Central Africa
1995 Central Africa
0.4976
1996 Central Africa
0.6567
1997 Central Africa
0.0344
1998 Central Africa
0.2755
1999 Central Africa
0.1884
Total
Central Africa
1.6526
1995 Central America
0.0169
1996 Central America
0.0013
1997 Central America
0.0762
1998 Central America
0.1474
1999 Central America
0.0114
Total
Central America
0.2534
1995 Central & South Asia
1.7603
1996 Central & South Asia
0.8645
1997 Central & South Asia
0.1941
1998 Central & South Asia
0.5200
1999 Central & South Asia
0.1939
Total
Central & South Asia
3.5329
1995 Eastern Europe
0.0004
1996 Eastern Europe
0.0071
1997 Eastern Europe
0.0009
1998 Eastern Europe
0.0007
1999 Eastern Europe
0.0079
Total
Eastern Europe
0.0170
1995 Middle East
0.2902
1996 Middle East
0.0604
1997 Middle East
0.1064
1998 Middle East
0.0377
1999 Middle East
0.2996
Total
Middle East
0.7944
1995 North Africa
0.0108
1996 North Africa
0.0066
1997 North Africa
0.0715
1998 North Africa
0.0323
1999 North Africa
0.0083
Total
North Africa
0.1296
1995 North America
0.5246
1996 North America
0.3987
1997 North America
0.6078
1998 North America
0.7213
1999 North America
0.6205
Total
North America
2.8728
1995 Oceania
0.0004
1996 Oceania
0.1183
1997 Oceania
0.1549
1998 Oceania
0.4262
1999 Oceania
0.1086
Total
Oceania
0.8083
1995 FSU
0.0000
1996 FSU
0.0000
1997 FSU
0.0084
1998 FSU
0.0000
1999 FSU
0.0001
Total
FSU
0.0084
1995 Southern Africa
0.0659
1996 Southern Africa
0.0148
1997 Southern Africa
0.0187
1998 Southern Africa
0.1619
1999 Southern Africa
0.4690
Total
Southern Africa
0.7302
1995 South America
0.3406
1996 South America
0.1454
1997 South America
0.2371
1998 South America
0.4825
1999 South America
0.4284
Total
South America
1.6341
1995 South-east Asia
0.2849
1996 South-east Asia
0.3131
1997 South-east Asia
0.3588
1998 South-east Asia
0.4478
1999 South-east Asia
0.4075
Total
South-east Asia
1.8121
1995 Western Europe
0.1380
1996 Western Europe
0.1505
1997 Western Europe
1.3653
1998 Western Europe
0.1932
1999 Western Europe
0.1574
Total
Western Europe
2.0044
Central America 0.0000 0.0002 0.0002 0.0001 0.0000 0.0005 0.7178 1.1950 1.0331 0.5410 1.1329 4.6198 0.0218 0.0327 0.1746 0.1800 0.2623 0.6714 0.0189 0.0995 0.0030 0.0229 0.0064 0.1507 0.0705 0.0119 0.0161 0.0173 0.0189 0.1346 0.0000 0.1341 0.0021 0.0109 0.0000 0.1471 22.4680 31.4015 28.0958 33.2296 38.0402 153.2352 0.0033 0.0684 0.1207 0.1274 0.0829 0.4026 0.0000 0.0605 0.1986 0.0587 0.0081 0.3259 0.0774 0.4304 0.0987 0.0191 0.0507 0.6763 0.5553 1.8655 1.7136 1.9114 1.1105 7.1563 0.4551 0.5623 0.0492 0.9822 0.0892 2.1381 0.4339 0.3463 0.4891 0.4562 0.5373 2.2629
Central & South Asia 0.0147 0.0101 0.0035 0.0559 0.0218 0.1060 0.9242 7.9984 93.3307 21.5666 0.6962 124.5161 3.4605 61.7172 20.8937 8.4108 5.9164 100.3962 0.0750 0.0634 0.4984 1.4679 0.7169 2.8216 0.1083 2.3403 2.8098 4.5177 1.7832 11.5591 0.8781 0.6628 0.2092 0.1301 0.5750 2.4551 97.3939 86.3532 77.3522 65.2549 68.8541 395.2083 7.3305 26.9375 18.0507 15.8428 15.0996 83.2610 0.1686 0.5679 0.5140 4.2047 2.5405 7.9956 1.1837 1.8448 1.2787 0.6378 0.4311 5.3761 4.6692 16.1354 11.0835 16.3524 14.0544 62.2949 19.1315 135.8150 29.3716 32.0168 10.2948 226.6296 3.1199 1.3676 47.1093 6.6849 1.2506 59.5323
Eastern Europe 0.0148 0.0175 0.0218 0.0369 0.0274 0.1185 0.1236 0.2523 0.1892 0.1490 0.0615 0.7756 0.2895 1.2141 0.6079 0.5264 0.4313 3.0692 4.7491 3.6900 3.2317 5.0361 3.6283 20.4032 0.4875 0.3581 0.4086 0.3684 0.4666 2.5394 0.1254 0.2632 0.2079 0.2822 0.2611 1.1398 1.7263 2.8439 1.8298 1.4994 1.6147 9.5140 0.0133 0.0344 0.0074 0.0051 0.0141 0.0743 2.2567 3.7433 3.1474 2.8446 1.0728 13.0635 0.0846 0.1097 0.1043 0.0777 0.1200 0.4963 1.0516 1.6227 2.2029 1.5771 1.3799 7.8342 0.4550 0.3038 0.8805 0.4792 0.4391 2.5578 2.6850 5.2138 4.5064 3.3835 3.1859 18.9746
Middle East 0.0008 0.0000 0.0315 0.0248 0.0122 0.0694 0.0234 0.0938 0.2159 0.0729 0.0242 0.4304 4.6034 7.1493 3.5783 5.6039 0.7064 21.6413 1.9467 2.4611 1.2022 2.0765 2.6796 10.3661 7.2631 1.0893 5.9675 3.0537 1.2827 25.6536 1.6840 0.3597 0.3088 1.0650 0.3208 3.7382 12.1025 13.4897 15.8272 9.8012 12.5528 63.7734 0.5766 1.6820 1.7365 3.0403 2.4344 9.4698 3.6448 6.4979 4.8750 8.8628 5.3805 29.2610 0.0013 0.0181 0.0237 0.2207 0.1049 0.3687 2.5608 2.0701 6.2214 5.9081 3.5032 20.2636 5.0358 4.7795 4.4413 5.8334 5.6713 25.7613 3.0802 4.4753 3.4981 3.1953 5.9554 20.2044
North Africa North America
0.0051 0.0155 0.0051 0.0156 0.0099 0.0512 0.3731 0.1906 0.4837 0.0967 0.3849 1.5290 2.2978 2.3960 2.8211 4.3142 1.9312 13.7603 2.5848 1.5212 0.9695 1.3279 1.1580 7.5614 3.9026 0.5779 2.5509 2.6701 1.5322 13.2090 0.3373 0.7116 0.5386 0.8993 0.2485 2.7353 25.7962 25.4160 24.3203 26.5783 26.4031 128.5138 0.0882 1.7303 4.3002 1.9581 1.2312 9.3081 0.6938 0.5752 0.7675 0.6726 0.3649 3.0740 0.0635 0.0506 0.1691 0.0474 0.0844 0.4150 1.4886 3.0895 6.3842 5.2614 2.4084 18.6321 2.4177 4.8298 7.0455 7.5120 9.7584 31.5634 6.0055 2.9264 4.8419 5.6990 5.9736 25.4465
0.0039 0.0045 0.0112 0.0050 0.0266 0.0512 5.8659 7.7870 13.0115 7.3844 6.3168 40.3656 0.4308 0.9847 1.0028 0.4401 0.4600 3.3184 0.0692 0.0804 0.1540 0.1353 0.1162 0.5551 0.4917 0.5697 0.4971 0.4200 0.3671 2.3456 0.0037 0.1016 0.0035 0.1869 3.8797 4.1754 15.6483 14.5063 19.1281 15.9503 17.5477 82.7806 0.1710 0.4404 0.4029 0.5164 1.1563 2.6870 0.0026 0.4862 0.1581 0.2491 0.0684 0.9644 0.1302 0.5077 0.4175 0.3441 0.3402 1.7397 2.0551 2.6493 3.4523 2.5408 2.6677 13.3652 2.1945 2.5216 2.8520 2.7838 2.6162 12.9680 0.4943 0.4402 1.0670 1.7203 1.3596 5.0814
Appendix VII - p.1
Appendix VII. Gross virtual water trade between and within regions (Gm3)
Year Exporter
Importer
1995 Central Africa
1996 Central Africa
1997 Central Africa
1998 Central Africa
1999 Central Africa
Total
Central Africa
1995 Central America
1996 Central America
1997 Central America
1998 Central America
1999 Central America
Total
Central America
1995 Central & South Asia
1996 Central & South Asia
1997 Central & South Asia
1998 Central & South Asia
1999 Central & South Asia
Total
Central & South Asia
1995 Eastern Europe
1996 Eastern Europe
1997 Eastern Europe
1998 Eastern Europe
1999 Eastern Europe
Total
Eastern Europe
1995 Middle East
1996 Middle East
1997 Middle East
1998 Middle East
1999 Middle East
Total
Middle East
1995 North Africa
1996 North Africa
1997 North Africa
1998 North Africa
1999 North Africa
Total
North Africa
1995 North America
1996 North America
1997 North America
1998 North America
1999 North America
Total
North America
1995 Oceania
1996 Oceania
1997 Oceania
1998 Oceania
1999 Oceania
Total
Oceania
1995 FSU
1996 FSU
1997 FSU
1998 FSU
1999 FSU
Total
FSU
1995 Southern Africa
1996 Southern Africa
1997 Southern Africa
1998 Southern Africa
1999 Southern Africa
Total
Southern Africa
1995 South America
1996 South America
1997 South America
1998 South America
1999 South America
Total
South America
1995 South-east Asia
1996 South-east Asia
1997 South-east Asia
1998 South-east Asia
1999 South-east Asia
Total
South-east Asia
1995 Western Europe
1996 Western Europe
1997 Western Europe
1998 Western Europe
1999 Western Europe
Total
Western Europe
Oceania 0.0016 0.0032 0.0037 0.0039 0.0028 0.0152 0.0021 0.0012 0.0016 0.0012 0.0008 0.0068 0.0828 0.0968 0.0857 0.0671 0.0705 0.4030 0.0128 0.0243 0.0550 0.0384 0.0830 0.2134 0.1463 0.1621 0.1582 0.1627 0.1916 0.8209 0.0001 0.0000 0.0003 0.0000 0.0000 0.0005 1.1661 0.6804 0.9599 0.5791 0.6364 4.0219 0.5475 0.6456 0.4756 0.3933 0.7380 2.7964 0.0000 0.0000 0.0128 0.0000 0.0000 0.0128 0.0273 0.0152 0.0182 0.0157 0.0213 0.0977 0.0711 0.0738 0.0618 0.0662 0.0681 0.3409 0.3702 0.4566 0.6372 0.5804 0.5823 2.6266 0.1166 0.0082 0.0113 0.0099 0.0064 0.1523
FSU 0.0000 0.0000 0.0004 0.0030 0.0095 0.0128 0.0705 0.7957 0.6464 1.4570 1.3183 4.2878 0.6171 2.7256 2.4983 2.7169 1.3252 9.8831 1.2859 1.0543 0.7011 0.7832 1.4087 5.2331 0.0583 0.2322 0.2314 0.3683 0.3229 1.2131 0.0045 0.0852 0.0362 0.0845 0.0078 0.2182 1.1577 1.7920 0.9510 0.5480 5.2041 9.6527 0.0002 0.0233 0.0126 0.0182 0.0025 0.0568 0.5451 9.7397 11.8430 10.6950 15.8625 48.6822 0.0000 0.0297 0.0575 0.0426 0.1274 0.2573 0.2946 0.4403 1.0428 1.2015 1.8700 4.8491 0.1799 0.5666 0.6638 4.0351 0.5305 5.9759 0.5322 0.6934 0.7744 0.4420 1.4464 3.8883
Southern Africa 0.2974 0.2296 0.0689 0.0110 0.0372 0.6440 0.1234 0.0135 0.0038 0.0252 0.0000 0.1660 2.0879 1.7244 1.9615 2.8054 0.8581 9.4374 0.0097 0.0436 0.0047 0.0334 0.0270 0.1184 0.0132 0.0039 0.0028 0.0053 0.0039 0.0291 0.2438 0.0988 0.0079 0.0111 0.0715 0.4330 2.9580 2.2324 1.4799 1.7857 1.3884 9.8444 0.0897 1.1791 0.4342 0.4143 0.7245 2.8418 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.3526 0.4171 0.6457 0.6061 0.7558 2.7772 1.0340 0.3949 0.3870 0.3896 0.5423 2.7477 3.0271 1.7790 1.8766 2.3113 2.8190 11.8129 0.6521 0.3595 0.3661 0.3563 0.2997 2.0337
South America 0.0000 0.0000 0.0000 0.0006 0.0019 0.0024 0.5349 0.4109 0.4511 0.8466 0.2027 2.4461 0.2170 0.4307 0.0725 0.1390 0.0133 0.8725 0.0045 0.0180 0.0184 0.0310 0.0087 0.0807 0.0841 0.0303 0.1068 0.1177 0.1395 0.4784 0.0007 0.0003 0.0013 2.5338 2.0780 4.6141 14.2710 19.8020 19.1690 18.7479 16.6849 88.6748 0.1887 1.3382 1.4269 0.3051 0.4021 3.6611 0.0000 0.0007 0.0592 0.0000 0.0000 0.0599 0.2259 0.4718 0.5718 0.0209 0.0160 1.3063 21.4816 28.2697 29.2891 33.7365 33.9501 146.7270 0.6281 1.0685 0.6033 0.9429 0.2086 3.4514 0.5863 0.1325 0.2419 0.3617 0.2690 1.5914
South-east Asia 0.0135 0.0035 0.0052 0.0203 0.0031 0.0456 0.0227 0.0020 0.0662 0.1215 0.1966 0.4090 16.4929 12.9263 8.6227 22.0534 4.7938 64.8891 0.2588 0.0936 0.0984 0.0356 0.0671 0.5536 1.8071 0.1687 0.0653 0.2319 0.3430 2.7234 0.0003 0.0001 0.0794 0.0752 0.0007 0.1556 15.5146 18.5889 19.2247 16.0199 13.4565 82.8046 5.3400 8.1038 7.5285 7.5973 2.9925 31.5618 0.0000 0.0001 0.1445 0.1935 0.0642 0.4024 0.4280 0.3477 0.1307 0.2332 0.0726 1.2123 3.5136 2.1257 4.5405 3.3530 2.9675 16.5003 15.9496 17.5632 14.3879 26.4621 12.8347 87.1976 0.3013 0.2755 0.4019 0.5186 0.2778 1.7752
Western Europe 0.2956 0.3720 0.4330 0.3726 0.5153 1.9884 3.3923 3.2256 3.0797 2.1573 2.4711 14.3330 2.3568 4.8867 5.0332 3.7352 1.7571 17.7689 8.0978 6.5557 6.6503 6.4511 9.6622 37.4171 3.2920 3.5465 3.5249 3.7930 4.0939 18.3654 4.3878 2.4037 1.7243 3.2199 2.0517 13.7874 40.1633 35.7772 34.6834 31.2913 28.3520 170.2672 0.4606 0.9863 0.9140 1.1343 0.9212 4.4077 2.5000 10.2587 9.3471 8.3268 4.5710 35.0022 1.0714 1.5414 1.4755 1.3904 2.1788 7.6575 31.7385 30.1766 35.6362 42.7230 50.9358 191.2102 1.6990 2.4310 2.3415 2.4427 2.1644 11.0786 45.9353 49.6688 51.1823 52.2922 51.3804 250.4589
Appendix VII - p.2
Value of Water Research Report Series 1. Exploring methods to assess the value of water: A case study on the Zambezi basin. A.K. Chapagain - February 2000 2. Water value flows: A case study on the Zambezi basin. A.Y. Hoekstra, H.H.G. Savenije and A.K. Chapagain - March 2000 3. The water value-flow concept. I.M. Seyam and A.Y. Hoekstra - December 2000 4. The value of irrigation water in Nyanyadzi smallholder irrigation scheme, Zimbabwe. G.T. Pazvakawambwa and P. van der Zaag ­ January 2001 5. The economic valuation of water: Principles and methods J.I. Agudelo ­ August 2001 6. The economic valuation of water for agriculture: A simple method applied to the eight Zambezi basin countries J.I. Agudelo and A.Y. Hoekstra ­ August 2001 7. The value of freshwater wetlands in the Zambezi basin I.M. Seyam, A.Y. Hoekstra, G.S. Ngabirano and H.H.G. Savenije ­ August 2001 8. `Demand management' and `Water as an economic good': Paradigms with pitfalls H.H.G. Savenije and P. van der Zaag ­ October 2001 9. Why water is not an ordinary economic good H.H.G. Savenije ­ October 2001 10. Calculation methods to assess the value of upstream water flows and storage as a function of downstream benefits I.M. Seyam, A.Y. Hoekstra and H.H.G. Savenije ­ October 2001 11. Virtual water trade: A quantification of virtual water flows between nations in relation to international crop trade A.Y. Hoekstra and P.Q. Hung ­ September 2002 Acknowledgement The work underlying this report has been sponsored by the National Institute of Public Health and the Environment (RIVM), Bilthoven, the Netherlands. The research is part of the research programme of Delft Cluster. We would like to thank Ton Bresser (RIVM) and Huub Savenije (IHE) for their valuable inputs.
IHE Delft P.O. Box 3015 2601 DA Delft The Netherlands Website www.ihe.nl Phone +31 15 2151715 National Institute for Public Health and the Environment Delft Cluster

AY Hoekstra, PQ Hung

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