Import and export of atmospheric water vapor between nations

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1 Import and export of atmospheric water vapor between nations Paul A. Dirmeyer Center for Ocean-Land-Atmosphere Studies, Calverton, Maryland Kaye L. Brubaker Dept. of Civil & Environmental Engineering, University of Maryland, College Park Timothy DelSole Dept. of Climate Dynamics, George Mason University, Fairfax, Virginia Corresponding author: Paul A. Dirmeyer COLA Technical Report 256 January 2008

2 Abstract We have applied a methodology for estimating the source regions of evaporation supplying precipitation over specific regions to the areas of most of the nations of the world. The methodology has been used in the past to estimate recycling ratios and the surface sources of moisture supplying rainfall over specific river basins. Extension to nations is straightforward, and we have incorporated other demographic information to gain a new viewpoint on the linkages between nations through the atmospheric branch of the hydrologic cycle. We find that nations with the highest recycling ratio, when scaled to a common area, have a combination of mountainous terrain, humid climate, or are at high latitudes. Nations with the lowest scaled recycling ratio are usually arid or semi-arid and on the coast. Small landlocked nations are most likely to receive most of their precipitation from the evaporation of the territories of other nations. Moisture independence is greatest for large isolated nations. Nations that import a majority of their precipitating moisture from other countries who rank lower in terms per-capita precipitation, i.e., more water poor nations, tend not to be economically rich, but instead poor nations possessing lower population densities than their neighbors. 1

3 1. Introduction Contentious arguments over water resources frequently take the form of quarrels between neighboring nations through which flows a common river. The upstream nation begins to build a dam or otherwise divert a substantial fraction of the water from the river so that the amount of water reaching the downstream nation is critically reduced. The Transboundary Freshwater Dispute Database (Yoffe et al. 2004) lists well over 300 international water dispute events dealing with water quantity between % more than for all other categories of international water disputes combined. Most occur in arid regions. From a practical standpoint, surface rivers and lakes are an obvious source and resource for fresh water. But no nation manufactures water it comes into the ground from the atmosphere above as rain or snow. Our research has been designed to examine how atmospheric moisture sources (evaporation from the surface) and sinks (precipitation) are linked across hydrologic elements of the land surface (e.g., river basins). Our methods are described in Section 2 below. One quantity that can be easily calculated from the resulting data is the recycling ratio (RR). RR is the fraction of precipitation over a defined region that originated as evaporation from that same region. RR is considered a measure of the sensitivity of the water cycle in a region to disturbance or perturbation, with a high value of RR suggesting strong local climate feedbacks (Brubaker and Entekhabi 1996). We can also determine the evaporative sources of moisture from outside of the chosen region. Estimates of RR or external moisture sources can be made for any arbitrary domain. What would we find if we considered individual countries? We could determine, for instance, from which countries the rainfall in a given nation evaporated. Of course, for many locations, much if not nearly all of the water has an oceanic source. Nonetheless, it would be interesting to see, for instance, how much of the rainfall that a 2

4 certain nation relies on for agriculture actually evaporates from a neighboring state. Much as virtual water (Oki and Kanae 2004) describes how nations are linked economically by their water use, an assay at the national level of evaporative sources and sinks could illustrate how climate and the atmosphere links us all hydrologically. In some sense, our calculation is an estimate of actual, rather than virtual, water importation and exportation. Advances in climate research, the production of global atmospheric reanalyses, and the extension of observational data sets for several decades now enable us to look at this part of the global hydrologic system in a new way. Section 2 describes the data sets used, and the method to calculate the evaporative sources of rainfall and snowfall over individual nations. Results are presented in Section 3. Section 4 provides a summary and discussion. 2. Data and methods The global gridded precipitation data of Xie and Arkin (1997) provide the information on total mass of water that is the starting point for estimating evaporative sources. The procedure starts from observed rainfall events and traces the moisture in the air backward in time to estimate its track of origin. The methodology we use to track water in the atmosphere is called the quasi-isentropic back-trajectory scheme (QIBT; Dirmeyer and Brubaker 1999; Brubaker et al. 2001). The approach is similar to that used for tracking air pollution. QIBT treats water vapor as a passive tracer between the time it enters the atmosphere as evaporation and the time it condenses into a cloud and precipitates to the surface. The water vapor in the air is assumed to change thermally in the same manner as the air it is in; clouds that may form and dissipate along the way are considered unimportant in the net. Multiple tracers of atmospheric moisture are chosen, distributed horizontally and vertically in the areas of precipitation in order to sample the 3

5 water vapor contributing to each rainfall or snowfall event. Reanalyzed fields of winds and temperature (Kanamitsu et al. 2002) are used to calculate the path each tracer followed to arrive at the point of precipitation. All calculations are performed on the latitude-longitude grid of the reanalysis data (grid boxes are approximately 1.9 on a side). Reanalysis estimates of precipitation are combined with satellite-based measurements at 3-hourly intervals (Joyce et al., 2004) to downscale the observed precipitation in time. Along each tracer path, reanalyses of surface evaporation rate and humidity are used to estimate how much of the tracer came from evaporation at each time interval prior to the precipitation. For each grid box, we calculate the evaporative source (ES) that supplied the water for precipitation over that grid box during a particular time interval (e.g. one month). The ES appears as a pattern of various intensities when plotted on a map. Figure 1 illustrates this for a specific grid box over the central United States for precipitation during the month of July By definition, the total integral of the ES over the globe equals the total mass of water that fell over the grid box during the specified interval. This information is accumulated for each month during the period of Please see Dirmeyer and Brubaker (2006) for a more complete description. The ES for larger areas is simply the sum of the ES from all grid boxes within that aggregate target area. The fraction of precipitation over the target area originating as evaporation over any arbitrary region is easily calculated. Thus, this approach also straightforwardly provides estimates of the recycling ratio (RR), which is easily calculated as the fraction of the total ES that lies within the target area (Dirmeyer and Brubaker, 2006). It should be noted that the area of many countries are on the same scale of, or smaller than, a single grid box. Thus, we have disaggregated the data from individual grid boxes that fall across national boundaries by the fraction of each nation s area within each box. Another problem with the global meteorological reanalyses used for these 4

6 calculations is that the reanalysis model does not resolve many islands and treats those areas as ocean. This affects not only small islands but also many larger ones, such as all of the Greater Antilles. As a result, the list of nations for which we have performed water transport calculations is not complete. In addition, although our method uses observed precipitation analyses and global reanalyses of atmospheric state variables, it also uses the reanalysis estimates of evaporation, which contain no actual observations of evaporation. Evaporation is considered a class D variable (Kalnay et al. 1996) meaning it is entirely the product of the analysis model with little constraint by assimilated observations of other variables. There exist other multi-year global evaporation estimates from the integration of offline land surface models, such as from the Global Soil Wetness Project (GSWP; Dirmeyer et al. 2006) or the Global Land Data Assimilation System (GLDAS, Rodell et al. 2004). These are theoretically superior to less constrained reanalyses estimates, but they are likewise purely a model product void of real observations of evaporation and generally cover shorter periods of time on different grids than the atmospheric reanalysis. Except for a few localized research sites, there are no routine measurements of surface fluxes such as evaporation. Heterogeneity of the land surface on scales much smaller than the reanalysis grid prevents local flux measurements from being easily scaled up to the resolution considered here. Measurements of evaporation would need to be at the same (or greater) density of that for rain gauges to be useful in this context. Unfortunately, evaporation is the least measurable component of the surface energy or water balance from remote sensing, so satellites do not offer strong promise for addressing this data gap. These caveats connote that our estimates should not be taken as a definitive or absolute measurement of ES magnitudes, although we do have more faith in the relative differences and trends found by this method. RR itself also varies with errors in 5

7 evaporation a general overestimation of evaporation rates will lead to larger values of RR, and vice versa. Again, relative comparisons between regions or different time periods within a region are less prone to such systematic errors. Brubaker et al. (2001) showed that random errors in evaporation estimates have almost no impact on calculation of ES or RR. 3. Results Table 1 presents the complete assay of hydrologic quantities derived from the QIBT calculations. Data on population come from USCIA (2005). Mean annual precipitation for each country is presented as the estimated total mass of water that falls within the boundaries of that nation, based on the gridded fields of observed precipitation (Xie and Arkin 1997). This mass is equal to the total ES supplying precipitation to each nation. The ES that is determined to originate from land areas is termed the terrestrial evaporative source (TES), and is expressed as a percentage of ES. The oceanic contribution to ES would be 100% minus TES. There are two columns of Table 1 showing recycling ratio. The first is RR for each nation. Table 2 lists the ten nations with the largest values of RR. These are also ten of the largest nations. Values of RR increase with the size of the target area. One can envision that as the target area grows to encompass the entire surface of the earth, RR must approach 100%. Likewise, as the area shrinks to any single point on the surface of the earth, RR approaches 0%. Sudradjat (2002) found that, over the Mississippi basin, there was a robust scaling between the total area under consideration and the recycling ratio for that area. Dirmeyer and Brubaker (2006) found that this property held across the globe, and that there appears to be a constant value of the slope of the regression curve between log(rr) and log(area) that applies over all land areas, at least down to the scale 6

8 of a single grid box. This allows us to scale the RR for any region of arbitrary surface area to a standard reference area, allowing us to directly compare RR between regions of differing sizes. Figure 2 shows as black diamonds the area and calculated recycling ratio for all nations in this study. There is a clear dependence on size. The diagonal line represents the scaling parameter found by Dirmeyer and Brubaker (2006), and the open circles show the scaled recycling ratio for a common reference area of 10 5 km 2, represented by the thin vertical line. Graphically, the transformation for any point in Fig 2 is accomplished by selecting one of the diamonds, tracing down parallel to the diagonal scaling line until the vertical line is reached, and reading the new recycling ratio on the ordinate. The shaded area denotes the range of possible areas for a single grid box in the reanalysis data set. The possible areas vary because the reanalysis data are on a latitudelongitude grid, so the convergence on meridians toward the poles causes the area of grid boxes to decrease with latitude. There is some indication that the scaling found by Dirmeyer and Brubaker (2006) may not hold below this range. Scaled recycling ratios for nations smaller than one grid box appear to be skewed toward low values. Table 1 also shows the scaled RR for each nation. Figure 3a shows a global map of scaled RR calculated for the entire 25-year period over the land grid boxes of the reanalysis grid (excluding Antarctica). As discussed by Dirmeyer and Brubaker (2006), there are clear spatial deviations that appear to reflect variations in altitude, mean precipitation and latitude. Figure 3b also shows RR scaled to the same reference area, but tallied by nation. Much of the apparent discrepancy between the two maps results from the differences in accounting on a uniform grid versus regions (nations) with highly variable areas. This is particularly evident in the vicinity of sharp gradients in precipitation and recycling ratio. Table 3 ranks the 10 nations with the highest and lowest scaled RR. Low scaled RR occurs in both very dry and very wet nations. The dry areas lack evaporation to provide a local 7

9 supply of ES moisture must come from remote sources. Wet nations in the tropics are largely supplied by bountiful oceanic ES. The shape and orientation of a country can also result in low values of scaled RR. If a country is elongated in shape in a direction perpendicular to the direction of the predominant transport of moisture, such as the case for nations like Chile or Togo, there is insufficient fetch for evaporation from the country to recondense and precipitate before being advected across the border. Nations with high values of scaled RR are found predominantly at high altitude, high latitude and interestingly, Eastern Europe and to a lesser extend southern Africa. Orientation can increase scaled RR if the major axis of an elongated nation is parallel to the prevailing flow (e.g., Mongolia or Papua New Guinea). Returning to Table 1, the second column shows the total terrestrial evaporative source (TES) for each nation expressed as a percentage of ES. Table 4 lists the 10 nations with the greatest and least percentage of their total rainfall that originates as evaporation from land surfaces. Small island nations would have much smaller TES than any of the values shown here. High values are mainly confined to nations that are well inland (e.g., Mongolia) or have a long overland fetch due to the prevailing winds (e.g., Namibia). We next look at the quantity (TES RR), the percentage of total precipitation that starts out as evaporation from nations other than the target nation. This quantity is, in some sense, a measure of moisture dependence. Table 5 lists the ten nations that rate as the most and least dependent on evaporation from other nations. As with TES, nations with high percentages tend to be inland or have long upwind fetches over land. However, the list is skewed towards smaller nations that have low rates of moisture recycling. Nations with low values of (TES RR) are coastal or island nations with predominantly onshore flow. 8

10 Table 6 shows for each nation the three largest contributors to that nation s ES. These could be considered the equivalent of the nation s major trading partners in terms of the atmospheric branch of the hydrologic cycle. The ten top contributions to one nation from another, in terms of percentage of the receiving nation s overall precipitation, are listed in Table 7. For the nations investigated, none are dependent on evaporation from another single country for more than half of their total precipitation, and only seven cases are found where more than 30% comes from one country. The maximum value found was 42.5% of Nepal s precipitation, which we estimate to come from evaporation from the land over India. Each of the top ten suppliers of moisture and the majority of main contributors in Table 1 are immediate neighbors to the receiving nation. The next quantity listed is (RR/TES). This ratio, expressed as a percentage, corresponds to the portion of all terrestrial evaporative sources that are domestic in origin and a sort of independence measure. Top and bottom nations in this category are listed in Table 8. Nations that do not have a strong dependence on imported moisture, so to speak, are generally large and/or isolated, with Australia topping the list. Nations that show a small fraction of domestic ES are all small themselves. Seven of the ten nations scoring lowest in (RR/TES) are located in Africa. Many of the water statistics shown so far exhibit a significant dependence on the physical size of the target nation. In economic terms, it might be more useful to consider statistics that are weighted by population rather than area. Thus, we introduce the concept of precipitation per capita (PPC) a means of defining rich and poor countries in terms of water availability. An important caveat for this metric is that it obviously neglects potentially important sources of surface water such as rivers (the classic example is Egypt s dependence on the Nile). There may also be dependencies on less renewable water sources such as unreplenished groundwater. Table 1 also lists this quantity, which is shown in map form in Fig 4a. The richest and poorest nations measured by this metric 9

11 are listed in Table 9. There is a general tendency for tropical nations to have high values of PPC, and subtropical nations to have rather low values. It is immediately clear that water wealth does not correspond well to standard economic measures of wealth. Some nations seem at first glance to confound intuition. For instance, the largely arid nation of Australia ranks as the ninth richest water nation in terms of per capita precipitation. This results from a combination of high rainfall rates over a large area in the tropical northern part of the nation, and a very low population density. The fact this water largely falls far from the nation s major population centers is not accounted for in this metric. Greenland may also have a surprisingly high PPC, as it does not receive a great deal of precipitation. However, Greenland s population is listed as only On the low side, Bangladesh is not an obviously water-poor nation. News of catastrophic floods in Bangladesh is common, and the nation yearly receives torrential rains. However, the combination of high population and small area (i.e., very high population density) results in a low value of PPC. Egypt indeed comes in as the poorest nation in terms of PPC the Nile is crucial for supporting Egypt s population. Israel ranks as the second poorest, and it indeed struggles to maximize water efficiency. We combine the estimates of water sources and sinks from the QIBT calculations with the water wealth metric PPC to estimate the percentage of precipitation each nation imports from poorer nations. Figure 4b provides a global map of these percentages, and the ten nations with the largest proportion of their precipitation from evaporative sources in nations with lower PPC are listed in Table 10. There is a strong but not perfect anticorrelation between PPC and the fraction of ES imported from more water-poor nations. We can put these results in the same context as that used for virtual water import and export. We can see from Table 8, for instance, that it makes little sense from a water resource point of view to ship Israeli citrus to Iceland. The import of precipitation 10

12 from nations with lower PPC constitutes an up-gradient transfer of water. This transfer of moisture from poorer to richer nations in terms of PPC is by no means a form of exploitation these nations are at the mercy of the circulation of the atmosphere. Nevertheless, it is interesting to see that this list is dominated by nations that are relatively sparsely populated, largely inland, and adjacent to more densely populated nations. Most of the nations shown in red in Fig 4b are by no means rich in the traditional sense. Because economically rich (or poor) nations are largely in proximity to one another, it is rare, for example, for industrialized nations to import moisture from more water poor developing nations. On the other hand, the nations in Fig 4b with low values (not importing much moisture from nations with lower PPC) range from wet to dry and rich to poor. 4. Discussion and Summary We have applied the QIBT methodology of calculating the spatial distribution of sources of evaporative moisture supplying precipitation to the areas of the world s nations. This exercise is motivated by the realization that surface water, over which international disputes are common, comes from rain and snow that is carried by the atmosphere which is unregulatable. A new perspective arises regarding the interconnectedness and relationships among the water resources of nations. Because of the definition of the water vapor recycling ratio (RR), nations with the largest areas are most likely to derive the greatest fraction of their total precipitation from moisture evaporated within their own borders. However, when scaled to a common reference area, we find that the nations with the highest RR for a unit area are some combination of mountainous, humid, or at high latitudes. Those with the lowest scaled RR are coastal nations and nearly always arid or semi-arid. As might be expected, 11

13 landlocked nations are most likely to derive the bulk of their moisture from terrestrial evaporation, and coastal humid nations derive the greatest amount of precipitated moisture from oceanic evaporation. Small landlocked nations are most apt to be dependent on evaporation from the territories of other nations to supply the moisture for their precipitation. Island nations and some humid coastal countries derive the smallest fraction of their total moisture source from the evaporation of other nations. We cataloged the main external suppliers of evaporative moisture for each nation. Nations that are upwind of major low-level atmospheric circulation features are chief suppliers. For example, Brazil, which has a large area, humid climate, and lies under the western edge of the South Atlantic subtropical anticyclone between the Atlantic Ocean and much of the rest of South America, is a major source to nearly every other nation on the continent. The largest single dependencies, where one nation derives a large fraction of its total precipitation from evaporation arising from within another country, usually consist of a small inland nation supplied by a much larger adjacent nation. When we examine the fraction of all terrestrial evaporative sources that is domestic (arising from within that nation s boundaries), large isolated nations exhibit what could be called the greatest moisture independence. Small countries surrounded by neighbors have the least independence. In fact, for this study we did not consider many of the smallest nations in area. Accuracy of the estimates of recycling ratio tend to break down when the area under consideration becomes smaller than the resolution of the meteorological data sets used in the calculation. Finally, when we consider population as well, we find the disparity in terms of the amount of precipitation per capita (PPC) spans nearly five orders of magnitude. Generally, highly populated arid nations have the lowest PPC, but Bangladesh ranks as seventh poorest among the nations considered despite its high rainfall because its population density is so high. When we combine this information with our calculations 12

14 of the sources and sinks of atmospheric moisture, we find that the list of nations that import a majority of their precipitated moisture from nations who rank lower in terms PPC tend to be those with lower population densities than their neighbors a nontraditional list of water exploiters (Table 10). The relationships between nations found in this study reveal new perspectives. We find that it is common for a nation downstream along an important river to be a significant evaporative source for the precipitation over the upstream nations the precipitation whose runoff supplies the river. Often the list of disadvantaged nations, based on the metrics we present, are filled with the names of developing countries. However, many of the most water-rich nations are otherwise economically poor. If a way could be found to take advantage of these natural resources, their lots could improve. At the very least, this study may promote a fresh look at water resources, and an appreciation of how the global hydrologic cycle binds all nations together. Additional data, including maps of the evaporative source regions for each country, the mean annual cycle of the source regions, and their interannual variability are available online at Acknowledgements: This work was supported by NSF awards EAR and EAR Thanks to Barry Klinger for discussion and questions that stimulated some of the investigations. References Brubaker, K. L., and D. Entekhabi, 1996: Analysis of feedback mechanisms in landatmosphere interaction. Water Resour. Res., 32, Brubaker, K. L., P. A. Dirmeyer, A. Sudradjat, B. S. Levy, and F. Bernal, 2001: A 36- year climatology of the evaporative sources of warm-season precipitation in the Mississippi river basin. J. Hydrometeor., 2,

15 Dirmeyer, P. A., and K. L. Brubaker, 1999: Contrasting evaporative moisture sources during the drought of 1988 and the flood of J. Geophys. Res., 104, Dirmeyer, P. A., and K. L. Brubaker, 2006: Evidence for trends in the Northern Hemisphere water cycle. Geophys. Res. Lett., 33, L14712, doi: /2006GL Dirmeyer, P. A., X. Gao, M. Zhao, Z. Guo, T. Oki and N. Hanasaki, 2006: The Second Global Soil Wetness Project (GSWP-2): Multi-model analysis and implications for our perception of the land surface. Bull. Amer. Meteor. Soc., 87, Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor., 5, Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, & D. Joseph, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP-DOE AMIP-II reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, Oki, T., and S. Kanae, 2004: Virtual water trade and world water resources. Water Sci. Tech., 49, Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J. K. Entin, J. P. Walker, C. Lohmann, and D. Toll, 2004: The global land data assilimation system. Bull. Amer. Meteor. Soc., 85, Sudradjat, A., 2002: Source-sink analysis of precipitation supply to large river basins. PhD Dissertation, [Available from University of Maryland, College Park, MD 20742, U.S.A.], 186 pp.. USCIA, 2005: The World Factbook 2005, United States Central Intelligence Agency, Washington, DC, USA. Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, Yoffe, S., G. Fiske, M. Giordano, M. Giordano, K. Larson, K. Stahl, and A. T. Wolf, 2004: Geography of international water conflict and cooperation: Data sets and applications, Water Resour. Res., 40, W05S04, doi: /2003wr

16 Table 1. Water cycle statistics for specific nations. Mean Annual Precipitation (GT water) Terrestrial Evaporative Source (TES; %) Recycling Ratio (RR; %) Scaled RR [1e5 km^2] TES-RR RR/TES Precip per capita (PPC; Tons water) Total Import from Nations with Lower PPC North America Belize ,691 11% Canada ,050 15% Costa Rica ,338 1% El Salvador ,521 0% Greenland ,008,869 19% Guatemala ,783 1% Honduras ,061 2% Mexico ,429 2% Nicaragua ,872 3% Panama ,698 27% United States ,820 4% South America Argentina ,720 5% Bolivia ,975 58% Brazil ,387 7% Chile ,719 0% Colombia ,836 3% Ecuador ,640 1% French Guiana ,155,975 12% Guyana ,066 11% Paraguay ,595 18% Peru ,762 5% Suriname ,848 12% Uruguay ,306 31% 15

17 Mean Annual Precipitation (GT water) Terrestrial Evaporative Source (TES; %) Recycling Ratio (RR; %) Scaled RR [1e5 km^2] TES-RR RR/TES Precip per capita (PPC; Tons water) Venezuela ,078 6% Europe Total Import from Nations with Lower PPC Albania ,248 9% Armenia ,559 12% Austria ,858 43% Azerbaijan ,879 20% Belarus ,912 41% Belgium ,586 1% Bosnia and ,781 35% Herzegovina Bulgaria ,818 35% Croatia ,586 32% Czech Republic ,615 26% Denmark ,762 13% Estonia ,609 26% Finland ,332 27% France ,298 4% Georgia ,357 47% Germany ,482 6% Greece ,680 19% Hungary ,176 24% Iceland ,921 6% Ireland ,776 3% Italy ,081 2% Latvia ,251 32% Lithuania ,344 30% Luxembourg ,695 10% 16

18 Mean Annual Precipitation (GT water) Terrestrial Evaporative Source (TES; %) Recycling Ratio (RR; %) Scaled RR [1e5 km^2] Precip per capita (PPC; Tons water) Total Import from Nations with Lower PPC TES-RR RR/TES Macedonia ,743 7% Moldova ,995 7% Netherlands ,682 0% Norway ,615 13% Poland ,970 16% Portugal ,827 1% Romania ,867 15% Russia ,296 17% Serbia and ,658 27% Montenegro Slovakia ,536 40% Slovenia ,834 48% Spain ,619 5% Sweden ,660 12% Switzerland ,608 10% Ukraine ,579 30% United Kingdom ,730 0% Africa Algeria ,012 5% Angola ,870 53% Benin ,761 37% Botswana ,504 65% Burkina Faso ,833 37% Burundi ,066 2% Cameroon ,363 38% Central African Republic ,900 69% 17

19 Mean Annual Precipitation (GT water) Terrestrial Evaporative Source (TES; %) Recycling Ratio (RR; %) Scaled RR [1e5 km^2] Precip per capita (PPC; Tons water) Total Import from Nations with Lower PPC TES-RR RR/TES Chad ,473 37% Congo ,166 60% Cote d'ivoire ,823 34% Djibouti ,020 36% Egypt % Equatorial Guinea ,973 30% Eritrea ,157 12% Ethiopia ,295 14% Gabon ,013 61% Gambia % Ghana ,702 23% Guinea ,645 50% Guinea-Bissau ,229 28% Kenya ,316 12% Lesotho ,087 0% Liberia ,310 39% Libya ,874 12% Madagascar ,407 6% Malawi ,052 0% Mali ,482 11% Mauritania ,289 21% Morocco ,350 0% Mozambique ,381 16% Namibia ,298 37% Niger ,426 8% Nigeria ,143 7% Rwanda ,009 1% 18

20 Mean Annual Precipitation (GT water) Terrestrial Evaporative Source (TES; %) Recycling Ratio (RR; %) Scaled RR [1e5 km^2] Precip per capita (PPC; Tons water) Total Import from Nations with Lower PPC TES-RR RR/TES Senegal ,206 5% Sierra Leone ,762 24% Somalia ,313 13% South Africa ,546 1% Sudan ,110 36% Swaziland ,308 0% Tanzania ,631 15% Togo ,906 27% Tunisia ,767 0% Uganda ,921 4% Western Sahara ,216 15% Zaire ,416 37% Zambia ,559 45% Zimbabwe ,848 13% Western Asia Afghanistan ,978 26% Bangladesh ,123 0% Bhutan ,887 74% India ,398 6% Iran ,734 13% Iraq ,048 6% Israel % Jordan ,302 3% Kazakhstan ,786 29% Kyrgyzstan ,698 47% Lebanon ,072 1% Nepal ,963 51% 19

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