1
Taikan Oki
Research Institute for Humanity and Nature
Yasushi Agata, Shinjiro Kanae, Takao Saruhashi, and Katumi Musiake
Institute of Industrial Science, Univ. of Tokyo

Global Water Resources Assessment under Climatic Change
in 2050 using TRIP

Short title:

Manuscript:

GLOBAL WATER RESOURCES IN 2050

2

Abstract. Annual water availability was derived from annual runo estimatedby land surface models using Total Runo

Integrating Pathways (TRIP) with 0.5

degree by 0.5 degree longitude/latitude resolution globally. Global distribution of water
withdrawal for each sector in the same horizontal spatial resolution was estimated basedon country-base statistics of municipal water use, industrial water use, and agricultural
intake, using global geographical information system with global distributions of
population and irrigated crop land area. Based on the framework, future projectionsof the global water resources considering population growth, climatic change, and theincrease of water consumption per capita were carried out. Population growth scenario
follows the UN projection in each country. Change in annual runo was estimated basedon the climatic simulation by a general circulation model by the Center of Climate
System Study, U of Tokyo, and the National Institute for Environmental Studies,
coupled with TRIP. The increase in unit consumption of water was related to thepredicted growth of GDP. With the increase of population only, future population understrong water scarcity, with water scarcity index is larger than 0.4, will increase by 90%
in 2050 compared to the current situation in 1995. Consideration of the climatic change
due to the global warming will relax this situation, and only 74% will be under thestrong water scarcity according to the future projection used in this study.

3

1. Introduction
The water resources situation is seriously under pressure even at present in someregions of the earth, and it is anticipated that the situation will be worse during the rst
half of this century (Cosgrove and Rijsberman, 2000). The estimation of the current
level of water stress is important for reliable projections of the severity of the watercrisis in the future. However, most of the previous global analysis on water scarcity
have been carried out on a country basis or a river basin basis with the exceptions of
Takahashi et al. (2000), Vorosmarty et al. (2000), and Oki et al. (2001), who presented
water scarcities on a each 0.5 degree by 0.5 degree longitude and latitude grid for the
globe. Considering the importance of global water scarcity, future projections shouldbe evaluated by multiple procedures, models, and methods at multiple organizations,since the reliability of the estimates will be supported if the similar results are obtained
from di erent scienti c approaches, information, and data processing. As the future
projection of the global warming has been done under IPCC (Intergovernmental Panelon Climate Change), such a approach to evaluate the future prediction by multiple
models/procedures is expected to reduce the uncertainty naturally embodied in the
projections.
In this study, water balances estimated by land surface models (LSMs) were used
for the global estimates of water availability, country-based statistics, such as municipal
water supply and industrial water use are assumed to be proportional to the population
distribution, and agricultural intake is assumed to be proportional to the irrigated landarea. Detailed procedures are described in Oki et al. (2001), and future projection ofworld water resources assessment was carried out using the frame work, considering the

4change in climatic conditions estimated by a general circulation model (GCM).
From these estimates of global annual water supply and demand in 2050, theglobal distribution of water stress was estimated for every 0.5 degree by 0.5 degree
longitude/latitude grid boxes globally, except for grid boxes more than half of that arecovered by ice or water. The result is examined with water stress levels in terms ofincrease or decrease compared to current situation in 1995, and the dominant factors on
the increase was evaluated among population growth, climate change, and the increaseof water usage per capita.

2. Water Availability in 2050
There are several methods to be adopted to estimate the water availability in the
future.
Firstly, the projected water cycles by climate model may be directly used for thewater resources assessment. This is straightforward, however, model outputs often su erbias errors, particularly river runo estimates, and correcting the errors is generally
required for quantitative estimation of available water resources in the future. The
coarse spatial resolution of the ordinary climate model is repeatedly claimed as for theinsuciency of utilizing model outputs, but the spatial resolution is becoming higher
rapidly in these days. Regional climate model may be nested in the global projection of
the future climate in order to obtain the future projection with higher spatial resolution,
however, the model bias should be removed anyway even in the case.
There are ways to down-scale the frequency of weather pattern to the climate on
regional scales. It assumes the current relationship between weather pattern and climatic
variables, such as pressure distribution and precipitation at each point, persists in the

5future. There is no guarantee to assume the persistence, and also another uncertaintyof the relationship to convert weather pattern to climatic variables is involved in the
future projection in addition to the uncertainty originated from the climate models.
Another way to estimate the future situation under global warming is to use
the historical climatic data when it was warmer as a proxy of future situation. This
procedure is also claimed to be ambiguous since there is no guarantee that the hydrologic
cycles are similar for past warm period and future climate under global warming, forexample. It is practically dicult to apply this proxy method for global water resources
assessment because it is not easy to obtain global information on water availability inthe past.
In this study, the current global distribution of available water resources wasestimated, adjusted using GCM simulation on the future climate, and used for global
water resources assessment.
For the estimation of the current runo distribution on global scale, oine runsby 10 di erent LSMs are used. Under the Global Soil Wetness Project (GSWP;IGPO (1995)), the global water balance was estimated by 11 LSMs using forcing data,such as precipitation, downward short wave and long wave radiation, wind speed,
temperature, humidity, and surface pressure, from ISLSCP (International Satellite Land
Surface Climatology Project) (Meeson et al., 1995). TRIP (Total Runo Integrating
Pathways) (Oki and Sud, 1998) was used for the river routing calculations to convert
runo from LSMs into river discharge. Details are described in Oki et al. (2001) but
basically the estimated annual discharge corresponded fairly well with observation where
forcing data to run LSMs were made with enough real observations, such as rainfall (Okiet al., 1999). As seem in Oki et al. (2001), the river discharge here is smaller compared6
to the previous estimates by approximately 20%, and this shortcomings is one of thecritical points of current study for further improvement.
Two methods are applied here to adjust the current river runo into future river
runo . One method is to use the di erence in GCM simulation for current and futureclimatic conditions, and the other one is to use the ratio. Both methods may su ertechnical problem when adjusting current river runo to the future. The di erence
method estimates future river runo rf d by modifying current river runo rn with thedi erence of current Rn and future Rf runo simulations by GCM:
rfd = rn + (Rf

0 Rn )(1)

As Eq. 1 can be written as
rf d = Rf

0 (Rn 0 rn) = Rf 0 1R

(2)

with the model bias 1R = Rn 0 rn , it implicitly assumes the water balance estimatedby the GCM may have a bias error but that is constant through future. The technicalproblem is the negative runo can be estimated in the case the model bias is larger thanGCM estimates of future river runo 1R > Rf . Practically negative runo should be
lled with zero runo .
The ratio method estimates future runo rf r by
rf r = rn

2 RRf

n

(3)

and it assumes the systematic error by GCM simulation keeps the ratio constantly. rf r
may be estimated tremendously big if current GCM runo (Rn ) is close to zero, butRsome future runo (Rf ) is predicted ( Rnf is huge), and real runo (rn ) is not zero. Sucha situation occurs mainly in desert region where the availability of water resources can

7
be neglected, therefore such an unrealistic estimate may be neglected for use in water
resources assessment. In this study, both rf d and rf r are estimated and used for futurewater resources assessments.
An atmospheric general circulation model (AGCM) of the Center for Climate
System Study, University of Tokyo and the National Institute of Environmental
Studies (Numaguti et al., 1997) was run with boundary conditions of sea surface
temperature in both 1990 and 2060, that are obtained from coupled ocean-atmosphericgeneral circulation model (AOGCM) run for increasing carbon dioxide conditions.
The horizontal resolution of the model simulation was carried out with T106, whichcorresponds to approximately 100km grid boxes globally. Daily runo estimates fromAGCM outputs were taken and routed using TRIP. The annual mean discharges in 1990
and 2060 were regarded as current (Rn ) and future (Rf ) river discharge. The di erenceRf

0 Rn and ratio Rf =Rn are shown in Figures 1 and 2.
From this particular simulation, Asian monsoon is enhanced due to the enhancementof the temperature di erence between Indian Ocean and Eurasian continent, and riverdischarge is expected to increase in Indian sub-continent through western part ofIndo-China Peninsula. Northern China, where water is relatively scarce at present,is also expected to increase its potentially available water resources, and decrease is
projected in between. Most part of Europe is projected to decrease its annual riverdischarge, on the contrary, the model simulation projects increase in Central to Western
Africa.
The ratio Rf =Rn is sometimes extremely large near the dry region in Figure 2,
and the small increase of river runo is exaggerated, as expected. The future river
runo estimated using di erence rf d is negative in some part in the western US (not

8shown). The di erence of these two kinds of future estimates (rf r 0 rf d ) is shown in
Figure 3. Since the area of 0.5 degree grid cell is approximately 2,500 km2 in tropicalregion, 5,0002106 m3 /0.5 grid cell corresponds 2,000mm/y of di erence. Therefore someregion, the future projection is highly depend on the assumption employed for bias error
correction of GCM.
The both estimates of rf r and rf d were used to assess the water resources in 2050
together with the future projection of water withdrawals described in the next section.

3. Future Water Withdrawal
The current water withdrawal estimated in Oki et al. (2001) was used for thebaseline for the future prediction of the water withdrawal in the world. Three scenarios
were assessed in this study. The rst scenario assumes only the population will increase
according to the medium prediction of the United Nations. The river discharge willchange due to the climatic variation in the second scenario, in addition to the increaseof population. The future river discharges of rf d and rf r presented in the previous
section were used. The unit withdrawal of municipal and industrial water will increaseor decrease because of the economic growth and technology development in the third
scenario, in addition to the population growth and climatic change.
The municipal water withdrawal increases even in the scenarios 1 and 2 according
to the population growth. In the scenario 3, the unit municipal water withdrawal willchange with the ratio projected by Takahashi et al. (2000). Water use eciency will
increase in North America and unit withdrawal will decrease by approximately 20%
there, neutral for OECD and Western Europe, but gradually increase in developing
countries.

9
The industrial water withdrawal will change only under the scenario 3 with theratio by Takahashi et al. (2000), as well. In the scenario 3, it was also assumed thatthe unit water withdrawal will increase proportional to the growth of GDP predicted by
Raskin et al. (1995) in each region.
The future projection of irrigation withdrawal in this study is not sophisticatedand should need further re nements. From the past 40 years of record, it was foundthat the increase in irrigation area in the world is approximately proportional to theincrease in the world population, and it was assumed the situation will continue inanother 50 years. Since the unit irrigation withdrawal was assumed to be constant ineach country, as a result, the increase in irrigation withdrawal is proportional to the
population growth here.
Figure 4 illustrates the change in the predicted total water withdrawal per year
under the scenario 3. Basically it re ects the change in population, therefore decreases
in developed countries and increases in developing countries.

4. Global Water Resources Assessment in the Future
The assessment of the water scarcity in this study adopted the index based on theratio of the annual water withdrawal W to the available annual water Q, and used by
UN et al. (1997) and Vorosmarty et al. (2000). Following Heap et al. (1998), thedesalinated water resource S was subtracted from W , and the water scarcity index Rws
Falkenmark et al. (1989) was derived
Rws =

W

0S

Q

(4)

10
The global distribution of estimated Rws is shown in Fig. 5 for scenario 3 using rf d .
Generally the severity of water scarcity is judged as:
Rws < 0.1

no water stress

0.1  Rws < 0.2

low water stress

0.2  Rws < 0.4

moderate water stress

0.4  Rws

high water stress

Following this criteria, it is evident from Fig. 5 that water scarcity is severe in
the river basins of Yellow, Indus, Ganges, and Amu-Darya, and in the middle west of
the United States. These distributions are generally similar to the current situation.
However, looking at the change in ratio of Rws in the future to the current Rws (Figure6), it is apparent that the drastic change is anticipated in Africa. In the continent,
current water withdrawal is comparatively little, however, rapid increase of water
withdrawal is projected according to the population growth. The situation should be
more serious than those regions where Rws will be as high as these African regions but
Rws is already high now, because social infrastructure to secure water resources andbetter water resources management system should have already be ready in such regions,at least somehow. However, sudden increase in Rws should demand the development ofsuch an infrastructure and better management system, and the situation will be serious
if that cannot be achieved.
Impacts of the climatic change and economic growth associated with the technology
development are assessed in Table 1 for rf d and rf r . The estimated values for current
situation is also presented in Table 1 for comparison. Basically, the population growth
have the large impact on the increase of people under high water stress level from 1.7
billion now to 2.5 through 2.7 billion in 2050. Since global river runo increases in

11
the GCM simulation used in this study, the water stress level is somewhat relaxed byclimate change e ect. This is opposite to the result by Vorosmarty et al. (2000) in
which the population under high water stress level increases if the impact of climatechange is considered, however, the impact of climate change e ect is not as dominant
as population growth in their estimates, as well. Of course, in developed countries,
population will decrease and the water stress level will be reduced. Therefore the precise
prediction of the impact of climate changes should have more relevance in developed
countries.
Even though the di erence of rfd and rf r are large in some regions, the di erence inTable 1 is comparatively small. The impact of unit demand increase is also small. These
results may suggest that such a presentation showing population under each water stresslevel is useful to know the relative impact of the factors changing the water supply anddemand, however, further indexing and detailed presentation are also necessary to assess
the change in water resources situation in the future.

5. Summary and Future Research Needs
A framework to assess the future water resources condition by grid base globally
was shown and preliminary results were presented. However, each component of the
future projection should be sophisticated, particularly about the irrigation withdrawal.
It should be coupled with the changes of land use and climate, such as temperatureand precipitation. Urbanization was not explicitly considered in this research, however,it may have a big impact particularly in developing countries and may need to beconsidered separately.
The impact of climatic change may be evaluated more if seasonal change of12potential water resources is used for assessment since the global warming will change
the snow accumulation and the timing of snow melt. In such time scales, river runo
routing calculations should be incorporated with anthropogenic activities on hydrologic
cycles, such as reservoir operations and water withdrawals. According to the increase ofhuman impact on nature, \natural" hydrologic cycles excluding anthropogenic activities
is di erent from \real" hydrologic cycles now. It is important for water resources
assessment to deal \real" one.
Much more e orts should be paid to investigate what is the robust information
we can extract from GCM simulations. Ultimate goal should be to utilize the realistic
and unbiased simulation of hydrologic cycles by GCM directly for water resources
assessment, however, it may not be achieved within several years and we need someproxy method for practical needs at least for a while.
As for the evaluation of water stress level, it may be required to consider the virtualwater trade, how much water resources is saved by importing agricultural and cattle
products. Including such aspects, an integrated approach to improve the accuracy of
future projections on both the natural and social sides of the water resources should
be promoted for developing action plans to mitigate the water crisis anticipated in theearly stage of this 21st century.

Acknowledgments: The authors would like to thank all the data providing agencies
and bodies, and exclusively wish to thank Dr. Petra Doll for providing their valuable
datasets.
This research is partially supported by the Core Research for Evolutional Science

13
and Technology of the Japan Science and Technology Corporation, and the No.5 projectof the Research Institute for Humanity and Nature, \Integrated management system forwater issues of global environmental information library and world water model."14

References:
Cosgrove, W. J. and F. R. Rijsberman, 2000:

World Water Vision. Earthscan

Publications Ltd, London.
Falkenmark, M., J. Lundqvist and C. Widstrand, 1989: Macro-scale water scarcity
requires micro-scale approaches; Aspects of vulnerability in semi-arid development.

Natural Resources Forum, 14, 258{267.

Heap, C., E. Kemp-Benedict and P. Raskin, 1998:

Conventional Worlds: Techinical

Description of Bending the Curve Scenarios. Polestar Series Report.

IGPO, , 1995: Global Soil Wetness Project. Technical report, International GEWEX
Project Oce, Silver Spring, MD 20910.
Meeson, B. W., F. E. Corprew, J. M. P. McManus, D. M. Myers, J. W. Closs, K.-J.
Sun, D. J. Sunday and P. J. Sellers, 1995: ISLSCP Initiative I | Global Data
Sets for Land-Atmosphere Models, 1987-1988., Published on CD-ROM by NASA
(USA NASA GDAAC ISLSCP 001 - USA NASA GDAAC ISLSCP 005).
Numaguti, A., S.Sugata, M. Takahashi, T. Nakajima and A. Sumi, 1997: Study on the
climate system and mass transport by a climate model.

CGER's Supercomputer

Monograph Report, 3, National Institute for Environmental Studies, Environment
Agency of Japan (Eds.).

15
Oki, T. and Y. C. Sud, 1998: Design of Total Runo Integrating Pathways (TRIP){ A global river channel network.

Earth Interactions, 2, [Available on-line at

http://EarthInteractions.org/].
Oki, T., T. Nishimura and P. Dirmeyer, 1999: Assessment of annual runo
from land surface models using Total Runo

J. Meteor. Soc. Japan, 77, 235{255.

Integrating Pathways (TRIP).

Oki, T., Y. Agata, S. Kanae, T. Saruhashi, D. Yang and K. Musiake, 2001: Global
Assessment of Current Water Resources using the Total Runo

Integrating

Hydrol. Sci. J., 46, 1159{1171.
Raskin, P., E. Hansen and R. Mongolis, 1995: Water and Sustainability: Global Outlook.
Pathways.

No. 4 in POLESTAR Series Report, Stockholm Envirnment Institute.
Saruhashi, T., 2001: Global Water Resource Assessment using Total Runo Integrating
Pathways. Master's thesis, Graduate School of Engineering, University of Tokyo.
Takahashi, K., Y. Matsuoka, Y. Shimada and R. Shimamura, 2000: Development of
the model to assess water resources problems under climate change.

Symposium on Global Environment, 8, 175{180.

Proc. 8th

UN, , UNDP, UNEP, FAO, UNESCO, WMO, W. Bank, WHO, UNIDO and SEI,
1997:

Comprehensive Assessment of the Freshwater Resources of the World. World

Meteorological Organization, pp.33.
Vorosmarty, C. J., P. Green, J. Salisbury and R. B. Lammers, 2000: Global Water
Resources: Vulnerability from Climate Change and Population Growth.

289, 284{288.

Science,16

T. Oki, Research Institute for Humanity and Nature, Kyoto, 602-0878, Japan(e-mail: oki@chikyu.ac.jp)
Received |; revised |; accepted |.

17

List of Figures
1

The di erence of the simulated river discharge for 1990 (Rn ) and 2060 (Rf ). 19

2

The ratio of the simulated river discharge in 2060 (Rf ) to that of in 1990
(Rn ). : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :3

The di erence of river discharge in 2050 estimated by di erence method
rf d and ratio method rf r . : : : : : : : : : : : : : : : : : : : : : : : : : : :

4

20

21

The change in the total water withdrawal per year under the scenario 3 in
2050. : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :22

5

The future projection of the water withdrawal to availability ratio in 2050. 23

6The change in the ratio of water withdrawal to availability in 2050 compared to that of in 1995. : : : : : : : : : : : : : : : : : : : : : : : : : : :24

List of Tables
1

World Population (billion people) under each Water Stress Level projected
in 2050. Future river discharge under climatic condition was estimted in
two ways; rf d using the di erence and rf r using the ratio of current andfuture GCM simulations. : : : : : : : : : : : : : : : : : : : : : : : : : : :

18

18

Table 1. World Population (billion people) under each Water Stress Level projected in 2050. Future river discharge under climatic condition was estimted in
two ways; rf d using the di erence and rfr using the ratio of current and future
GCM simulations.
StressCurrent

Population+ Climate+ Unit Demand

Level(1995)

Growth Only

ChangeIncrease

rf d

rf r

rf d

rf r

High water stress

1.7

2.66

2.43

2.57

2.51

2.65

Moderate water stress

0.6

0.91

0.93

0.93

0.97

0.95

Low water stress

0.6

0.94

0.96

0.94

1.00

0.96

No water stress

2.8

4.31

4.45

4.28

4.28

4.15

19

Annual Change in River Discharge[106 m3/0.5ogrid cell]

2060-1990
CCSR-NIES-GCM1

210˚

240˚

270˚

300˚

330˚

0˚

30˚

60˚

90˚

120˚

150˚

180˚

60˚

30˚

0˚

-30˚

-60˚
-5000

-1000

-500

-100

-10

10

100

500

1000

5000

Figure 1. The di erence of the simulated river discharge for 1990 (Rn) and 2060 (Rf ).

20

Annual Change Ratio in River Discharge
2060-1990
CCSR-NIES-GCM1

210˚

240˚

270˚

300˚

330˚

0˚

0.80

1.00

1.20

30˚

60˚

90˚

120˚

150˚

180˚

5.00

10.00

100.00

60˚

30˚

0˚

-30˚

-60˚
0.01

0.10

0.50

1.50

2.00

Figure 2. The ratio of the simulated river discharge in 2060 (Rf ) to that of in 1990
(Rn ).

21

Annual Change in River Discharge[106 m3/0.5ogrid cell]

2050
GSWP-GCM-2-GSWP-GCM-Diff-1

210˚

240˚

270˚

300˚

330˚

0˚

30˚

60˚

90˚

120˚

150˚

180˚

60˚

30˚

0˚

-30˚

-60˚
-5000

-1000

-500

-100

-10

10

100

500

1000

5000

Figure 3. The di erence of river discharge in 2050 estimated by di erence method rf dand ratio method rf r .

22

Annual Change in Water Withdrawal[106 m3/0.5ogrid cell]

2050-1995
Ver1-Scenario4-Irr-1

210˚

240˚

270˚

300˚

330˚

0˚

30˚

60˚

90˚

120˚

150˚

180˚

60˚

30˚

0˚

-30˚

-60˚
-500

-100

-50

-20

-5

5

20

50

100

500

Figure 4. The change in the total water withdrawal per year under the scenario 3 in
2050.

23

Annual Withdrawal-to-Availability Ratio
2050
GSWP-GCM-Diff1-Ver1-Scenario4

210˚

240˚

270˚

300˚

330˚

0˚

30˚

60˚

90˚

120˚

150˚

180˚

60˚

30˚

0˚

-30˚

-60˚
0.000

0.001

0.010

0.100

0.200

0.400

0.600

0.800

1.000

Figure 5. The future projection of the water withdrawal to availability ratio in 2050.

24

Rws Change[Ratio]
210˚

240˚

270˚

300˚

330˚

0˚

30˚

2050-1995
60˚

90˚

120˚

150˚

180˚

60˚

30˚

0˚

-30˚

-60˚
0.1

0.5

0.9

1.0

1.5

2.0

3.0

4.0

5.0

6.0

Figure 6. The change in the ratio of water withdrawal to availability in 2050 comparedto that of in 1995.