Water Resources Systems—Water availability and global change (Proceedings of symposium HS02a held
during IUGG2003 at Sapporo, July 2003). IAHS Publ. no. 280, 2003.

1

Global water resources assessment under climaticchange in 2050 using TRIP
TAIKAN OKI
Research Institute for Humanity and Nature, Kyoto 602-0878, Japan
taikan@iis.u-tokyo.ac.jp

YASUSHI AGATA, SHINJIRO KANAE, TAKAO SARUHASHI &KATUMI MUSIAKE
Institute of Industrial Science, Univ. of Tokyo, Tokyo 153-8505, Japan

Abstract Annual water availability was derived from annual runoff estimatedby land surface models using Total Runoff Integrating Pathways (TRIP) with
0.5° × 0.5° longitude/latitude resolution globally. Global distribution of water
withdrawal for each sector in the same horizontal spatial resolution was
estimated based on country-base statistics. Based on the framework, future
projections of the global water resources considering population growth,
climatic change, and the increase of water consumption per capita werecarried out. Change in annual runoff was estimated based on the climatic
simulation by a general circulation model coupled with TRIP. With theincrease of population only, future population under strong water scarcity,when water scarcity index is larger than 0.4, will increase by 90% in 2050
compared to the current situation in 1995. Consideration of the climaticchange due to global warming will relax this situation, and only 74% will be
under strong water scarcity according to the future projection used in thisstudy.[key words?]

INTRODUCTION
The water resources situation is seriously under pressure, even at present in some regionsof the earth, and it is anticipated that the situation will be worse during the first half of thetwenty-first century (Cosgrove & Rijsberman, 2000). The estimation of the current level ofwater stress is important for reliable projections of the severity of the water crisis in the
future. However, most of the previous global analysis on water scarcity have been carriedout on a country basis or a river basin basis with the exceptions of Takahashi et al. (2000),
Vörösmarty et al. (2000), and Oki et al. (2001), who presented water scarcities on a each
0.5° × 0.5° longitude and latitude grid for the globe. Considering the importance of global
water scarcity, future projections should be evaluated by multiple procedures, models, andmethods at multiple organizations, since the reliability of the estimates will be supported if
similar results are obtained from different scientific approaches, information, and dataprocessing. As the future projection of global warming has been done under IPCC
(Intergovernmental Panel on Climate Change), such an 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

2Taikan Oki et al.

municipal water supply and industrial water use, were assumed to be proportional tothe population distribution, and agricultural intake was assumed to be proportional tothe irrigated land area. Detailed procedures are described in Oki et al. (2001), andfuture projections of world water resources assessment were carried out using theframework, considering the change in climatic conditions estimated by a generalcirculation 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° × 0.5°
longitude/latitude grid boxes globally, except for grid boxes which are more than halfcovered by ice or water. The result was examined with water stress levels in terms ofincrease or decrease compared to the current situation in 1995, and the dominantfactors on the increase were evaluated among population growth, climate change, andthe increase of water usage per capita.

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 water
resources assessment. This is straightforward, however, model outputs often sufferbias errors, particularly river runoff 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 the
insufficiency of utilizing model outputs, but the spatial resolution is becoming rapidly
higher. Regional climate models may be nested in the global projection of the futureclimate in order to obtain the future projection with higher spatial resolution. However,
the model bias should be removed.
There are ways to downscale the frequency of weather pattern to the climate on
regional scales. It assumes the current relationship between weather pattern andclimatic variables, such as pressure distribution and precipitation at each point, persistsin the future. There is no guarantee to assume the persistence and 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
historic climatic data when it was warmer, as a proxy of the future situation. This
procedure is also claimed to be ambiguous since, for example, there is no guaranteethat the hydrologic cycles are similar for the past warm period and future climate underglobal warming. It is practically difficult to apply this proxy method for global water
resources assessment because it is not easy to obtain global information on water
availability in the 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 runoff distribution on a global scale, offline runsby 10 different LSMs were used. Under the Global Soil Wetness Project (GSWP;IGPO (1995)), the global water balance was estimated by 11 LSMs using forcing data,Global water resources assessment under climatic change in 2050 using TRIP

3such 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 Runoff
Integrating Pathways) (Oki & Sud, 1998) was used for the river routing calculations toconvert runoff from LSMs into river discharge. Details are described in Oki et al.
(2001), but basically the estimated annual discharge corresponded fairly well withobservation where forcing data to run LSMs were made with enough real observations,such as rainfall (Oki et al., 1999). As seem in Oki et al. (2001), the river discharge
here is smaller compared to the previous estimates by approximately 20%, and thisshortcoming is one of the critical points of the current study for further improvement.
Two methods are applied here to adjust the current river runoff into future river
runoff. One method is to use the difference in GCM simulation for current and futureclimatic conditions, and the other one is to use the ratio. Both methods may suffertechnical problems when adjusting current river runoff to the future. The difference
method estimates future river runoff r fd by modifying current river runoff rn with thedifference of current Rn and future R f runoff simulations by GCM:

r fd = rn + ( R f − Rn )(1)

As equation 1 can be written as:
r fd = R f − ( Rn − rn ) = R f − ∆R(2)with the model bias ∆R = Rn − rn , it implicitly assumes the water balance estimated by
the GCM may have a bias error but that is constant through the future. The technicalproblem is that the negative runoff can be estimated when the model bias is larger thanGCM estimates of future river runoff ∆R > R f . Practically negative runoff should be
filled with zero runoff.
The ratio method estimates future runoff r fr by:
r fr = rn ×

Rf
Rn

(3)

and it assumes the systematic error by GCM simulation keeps the ratio constantly. r fr
may be estimated tremendously big if current GCM runoff (Rn) is close to zero, butsome future runoff (Rf) is predicted (Rf/Rn is huge), and real runoff (rn) is not zero.
Such a situation occurs mainly in desert regions where the availability of water
resources can be neglected; therefore such an unrealistic estimate may be neglected foruse in water resources assessment. In this study, both rfd and rfr are estimated and used
for future water resources assessments.
An atmospheric general circulation model (AGCM) of the Centre for Climate
System Study, University of Tokyo and the National Institute of Environmental
Studies, Japan (Numaguti et al., 1997) was run with boundary conditions of sea
surface temperature in both 1990 and 2060, that are obtained from coupled oceanatmospheric general circulation model (AOGCM) run for increasing carbon dioxide
conditions.

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Taikan Oki et al.

The horizontal resolution of the model simulation was carried out with T106,
which corresponds to approximately 100-km grid boxes globally. Daily runoff
estimates from AGCM outputs were taken and routed using TRIP. The annual meandischarges in 1990 and 2060 were regarded as current (Rn) and future (Rf) riverdischarge. The difference Rf – Rn and ratio Rf /Rn are shown in Figures 1 and 2.

Fig. 1 The difference of the simulated river discharge for 1990 (Rf ) and 2060 (Rnf).

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

From this particular simulation, the Asian monsoon is enhanced due to the enhancementof the temperature difference between the Indian Ocean and the Eurasian continent. River
discharge is expected to increase in the Indian sub-continent through the western part of the
Indo-China Peninsula. Northern China, where water is relatively scarce at present, is also
expected to increase its potentially available water resources, and a decrease is projected in
between. Most of Europe is projected to decrease its annual river discharge. In contrast, themodel simulation projects an increase in Central to Western Africa.

Global water resources assessment under climatic change in 2050 using TRIP

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The ratio Rf /Rn is sometimes extremely large near the dry region in Fig. 2, and thesmall increase of river runoff is exaggerated, as expected. The future river runoff
estimated using difference rfd is negative in some parts of the western US (not shown).
The difference of these two kinds of future estimates (rfr – rfd) is shown in Fig. 3. Since
the area of 0.5° grid cell is approximately 2500 km2 in tropical regions, 5000 × 106 m3
per 0.5 grid cell corresponds to a difference of 2000 mm year-1. Therefore for someregions future projection is highly dependant on the assumption employed for bias
error correction of GCM.

Fig. 3 The difference of river discharge in 2050 estimated by difference method r fd andratio method r fr .

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

Both estimates of rfr and rfd were used to assess the water resources in 2050,
together with the future projection of water withdrawals described in the next section.

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Taikan Oki et al.

FUTURE WATER WITHDRAWAL

The current water withdrawal estimated in Oki et al. (2001) was used for the baseline
for the future prediction of water withdrawal in the world. Three scenarios wereassessed in this study. The first scenario assumes that 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 rfd and rfr 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 scenarios 1 and 2, according to
the population growth. In scenario 3, the unit municipal water withdrawal will changewith the ratio projected by Takahashi et al. (2000). Water use efficiency will increasein North America where unit withdrawal will decrease by approximately 20%. Water
use efficiency will be neutral for OECD and Western Europe, but gradually increase indeveloping countries.
The industrial water withdrawal will change only under scenario 3 with the ratio
by Takahashi et al. (2000). In scenario 3, it was also assumed that the unit water
withdrawal would increase proportional to the growth of GDP predicted by Raskin etal. (1995) in each region.
The future projection of irrigation withdrawal in this study is not sophisticated andwill need further refinements. From the past 40 years of records it was found that theincrease in irrigation area in the world is approximately proportional to the increase in
the world population, and it was assumed the situation would continue for the next 50
years. Since the unit irrigation withdrawal was assumed to be constant in each 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 scenario 3. Basically it reflects the change in population and therefore decreases
in developed countries and increases in developing countries.
GLOBAL WATER RESOURCES ASSESSMENT IN THE FUTURE

The assessment of the water scarcity in this study adopted the index based on the ratioof the annual water withdrawal W to the available annual water Q, and used by UN etal. (1997) and Vörösmarty et al. (2000). Following Heap et al. (1998), the desalinatedwater resource S was subtracted from W, and the water scarcity index Rws Falkenmark
et al. (1989) was derived as:
Rws =

W −S
Q

(4)

The global distribution of estimated Rws is shown in Fig. 5 for scenario 3 using r fd .
Generally the severity of water scarcity is judged as:
Rws ≤ 0.1
no water stress;

Global water resources assessment under climatic change in 2050 using TRIP

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0.1 < Rws ≤ 0.2 low water stress;
0.2 < Rws ≤ 0.4 moderate water stress;
0.4 ≤ Rws
high water stress
Following these criteria, it is evident from Fig. 5 that water scarcity is severe in theriver basins of the Yellow, Indus, Ganges, and Amu-Darya rivers, and in the mid-westof the United States. These distributions are generally similar to the current situation.

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

Fig. 6 The change in the ratio of water withdrawal to availability in 2050 compared tothat of in 1995.

However, looking at the change in ratio of Rws in the future to the current Rws (Fig. 6), it is apparent
that a drastic change is anticipated in Africa. In the continent, current

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Taikan Oki et al.

Table 1 World Population (billion people) under each Water Stress Level projected in 2050. Future
river discharge under climatic condition was estimated in two ways rfd using the difference and rfr using
the ratio of current and future GCM simulations.
Stress level

Current(1995)

Population
growth onlyHigh
Moderate
Low
No

1.67
0.58
0.62
2.78

2.66
0.91
0.94
4.31

+ Climate change+ Unit demand increase

r fd

r fr

r fd

r fr

2.43
0.93
0.96
4.45

2.57
0.93
0.94
4.28

2.51
0.97
1.00
4.28

2.65
0.95
0.96
4.15

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 isalready high because social infrastructure to secure water resources and better water
resources management system should already be in place in such regions. However, asudden increase in Rws should demand the development of such an infrastructure andbetter management systems. The situation will become serious if this cannot be
achieved.
Impacts of climatic change and economic growth associated with technology
development are assessed in Table 1 for rfd and rfr. The estimated values for the current
situation are also presented in Table 1 for comparison. Basically, the population
growth has the largest impact on the increase of people under high water stress levelfrom 1.7 billion now to 2.5, through 2.7 billion in 2050. Since global river runoff
increases in the GCM simulation used in this study, the water stress level is somewhat
relaxed by climate change effect. This is the opposite result to that by Vörösmarty et al.
(2000) in which the population under high water stress level increases if the impact ofclimate change is considered. However, the impact of climate change effect is not as
dominant as population growth in their estimates. Of course, in developed countries,
population will decrease and the water stress level will be reduced. Therefore theprecise prediction of the impact of climate changes should have more relevance indeveloped countries.
Even though the difference of rfd and rfr are large in some regions, the difference 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 eachwater stress level is useful to know the relative impact of the factors changing thewater supply and demand. However, further indexing and detailed presentation are
also necessary to assess the change in water resources situation in the future.

SUMMARY AND FUTURE RESEARCH NEEDS

A framework to assess the future water resources condition by grid base globally was
shown and preliminary results are 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 temperature andGlobal water resources assessment under climatic change in 2050 using TRIP

9

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 ofpotential water resources is used for assessment, since global warming will change thesnow accumulation and the timing of snow melt. In such time scales, river runoff
routing calculations should be incorporated with anthropogenic activities onhydrologic cycles, such as reservoir operations and water withdrawals. According to
the increase of human impact on nature, “natural” hydrologic cycles excluding
anthropogenic activities are different from “real” hydrologic cycles now. It is
important for water resources assessment to deal with “real” hydrologic cycles.
Much more effort should be made to investigate the robust information we canextract from GCM simulations. The ultimate goal should be to utilize the realistic andunbiased 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 necessary to consider thevirtual water trade, how much water resources are saved by importing agricultural andcattle products. Including such aspects, an integrated approach to improve the accuracyof 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 the twenty-first century.
Acknowledgments The authors would like to thank all the data providing agencies
and bodies, and exclusively wish to thank Dr. Petra Döll for providing their valuable
data sets. This research is partially supported by the Core Research for Evolutional
Science and Technology of the Japan Science and Technology Corporation, and theNo. 5 project of the Research Institute for Humanity and Nature, “Integrated
management system for water issues of global environmental information library andworld water model”.
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