Projection of future world water resources under SRES scenarios: an integrated assessment

Figures & data

Table 1 Descriptions of climate forecasting data used for water resources analysis.

Model name	Short name	Organization	Original resolution
Current (1986–1995)
Multi-model	GSWP2	GEWEX/GSWP2	1° × 1°
Future (2000–2100)
GISS-ER	GISSer	NASA/Goddard Institute for Space Studies, USA	5.0 × 4.0
MIROC3.2-Med	MIROC3	CCSR/NIES, Japan	T42L20
MPI-ECHAM5	ECHAM5	Max Planck Institute for Meteorology, Germany	T63L31
MRI-CGCM2.3.2a	CGCM2	Meteorological Research Institute, Japan	T42L30
NCAR-CCSM3.0	CCSM3	National Center for Atmospheric Research, USA	T85L26
UKMO-HadCM3	HadCM3	Hadley Centre for Climate Prediction and Research, MetOffice, UK	2.5 × 3.75L19

Fig. 1 Schematic of technical routing and data processing in this study.

Table 2 Comparison of the current water resources by GSWP2 with previous studies in eight regions and for the world (in km³/year).

Region	GSWP2	Shiklomanov (2000)	Vorosmarty et al. (2000)
N. America	8 000	6 800	5 900
L. America	11 400	13 100	11 700
Europe	3 800	2 900	2 800
M. East + N. Africa	470	500
Sub-Saharan Africa	5 200	4 000
CIS	6 500	3 400	18 200
Asia	9 100	9 700
Oceania	1 600	2 400	700
World	46 070	42 800	39 300

Fig. 2 Projected changes in water resources availability in eight regions and the world by the six GCMs. The names of the models giving highest and lowest projections are marked next to the points for the 2070s.

Fig. 3 Potential change directions of available water resources (total runoff) under A1b, A2 and B1 SRES scenarios as simulated by the 6 GCM models in 2020s, 2050s, and 2070s, respectively. SI indicates a significant increasing trend, SD a significant decreasing trend, and MC a subtle change. The area with UC or white shows large uncertainty in change directions among the different GCMs.

Fig. 4 Distributions of basins with various extents of water stress as defined by the two indices: (a) W/Q and (b) Q/c, in the present time slice.

Fig. 5 Distribution of future water stressed basins as defined by W/Q and Q/c in the 2050s and 2075s. The multi-model ensemble mean of discharge was used as the water resource availability (Q).

Fig. 6 Current and future projections of highly water-stressed population ratio in the world for scenarios A1b, A2 and B1 measured by (a) W/Q and (b) Q/c. The error bars shows the range caused by water resource projections of different GCMs.

Fig. 7 The highly water-stressed population of eight regions and the world total at present measured by index W/Q. The numbers above each bar illustrate the total population living in highly water-stressed basins in each region. (1: North America; 2: Latin America; 3: Europe; 4: Middle East & North Africa; 5: sub-Saharan Africa; 6: CIS; 7: Asia; 8: Oceania).

Fig. 8 The relative change of highly water-stressed population against 2000 in three future time slices for different regions and globally. The bar graph illustrates the average of the six GCM models; the error bar shows the range amongst the GCMs. (1: North America; 2: Latin America; 3: Europe; 4: Middle East & North Africa; 5: sub-Saharan Africa; 6: CIS; 7: Asia; 8: Oceania. For Region 5, the change rate was scaled by 0.1).

Table 3 Effects of population, socio-economic and climatic changes on worldwide population living in highly water-stressed basins.

			Case 1^a		Case 2		Case 3^d
		World population (10^6)	HSP^b (10^6)	%^c	HSP (10^6)	%	HSP (10^6)	%
2000		6133	2534	41.3	2534	41.3	2534	41.3
2025	A1^b	7935	3593	45.3	3706	46.7	3684	46.4
	A2	8724	3972	45.5	4744	54.4	4653	53.3
	B1	7935	3593	45.3	3789	47.8	3822	48.2
	B2	8042	3644	45.3	3703	46.0	−	−
2055	A1^b	8718	4417	50.7	4764	54.6	4571	52.4
	A2	11791	6330	53.7	7567	64.2	7350	62.3
	B1	8718	4417	50.7	4556	52.3	4423	50.7
	B2	9544	4493	47.1	4776	50.0	−	−
2075	A1^b	8317	4120	49.5	4657	56.0	4495	54.0
	A2	13556	7451	55.0	9011	66.5	8635	63.7
	B1	8317	4120	49.5	4239	51.0	4092	49.2
	B2	10065	5213	51.8	5436	54.0	−	−

^aCase 1 represents the situation with population change only, socio-economic (as water withdrawal intensity) and climatic conditions are fixed to the current level; Case 2 is the situation with population and socio-economic changes but the climate is fixed; Case 3 represents the situation with all the population, socio-economic, and climatic changes.

^bHSP means highly-stressed population.

^cThe columns illustrate what percentage of the increased population against year 2000 will live in highly-stressed basins.

^dThe numbers for Case 3 refer to the multi-GCM ensemble mean.

Fig. 9 Relative impact of climate warming on the world population living in highly water-stressed basins by six GCMs in different future time slices. The y-axis denotes the ratio of highly-stressed population in Case 3 to that in Case 2. The ratio of highly-stressed population globally calculated using the present and future water availability for each GCM, and the population and water withdrawal vary according to the scenarios and time slices.

Fig. 10 Relative impacts of (a) population, (b) water use and (c) climate on the number of people living in highly water-stressed basins in different regions and the world in 2050s under three different scenarios. Relative impacts are calculated by the ratio of highly-stressed population in Case 1 and 2000; by the ratio of Case 2 and Case 1; and by the ratio of Case 3 and Case 2. (1: North America; 2: Latin America; 3: Europe; 4: Middle East & North Africa; 5: sub-Saharan Africa; 6: CIS; 7: Asia; 8: Oceania).

Fig. 11 Impacts of population, water use and climate warming on water stress level in the 2050s. Background water stress maps represent the situation after the changes in population, water use and climate change based on index W/Q in the 2050s. By comparing any map with the map to its left, readers can understand which basin will be likely to deteriorate or be mitigated from one class of stress level to another due to the changes in water use or climate warming.

Table 4 Comparison of water stressed population in the world with other studies using the indicator Q/c (<1000 m³ c^-1 year^-1) (in million persons).

		CC			NCC		CC-NCC
		This study	Arnell (2004)	Alcamo et al. (2007)	This study	Arnell (2004)	This study	Arnell (2004)
Current		1755	1368	1601	1755	1368	0	0
2025	A1b	3081–3315	2938	−	3283	2882	−202 ~ 433	56
	A2	3546–3660	2564–3478	3576–4286	3641	3320	−95 ~ 19	−756 ~ 158
	B1	3203–3323	2368	−	3283	2882	−80 ~ 40	−514
	B2	−	2306–2994	3208–3727	3351	2883	−	−577 ~ 111
2055	A1b	3587–3765	2512	−	3740	3400	−153 ~ 25	−888
	A2	5488–6215	4351–5747	6432–6920	6158	5596	−670 ~ 57	−1245 ~ 151
	B1	3681–3850	2757	−	3740	3400	−59 ~ 110	−643
	B2	−	2766–3958	4909–5166	4243	3988	−	−1222 ~ −30
2075	A1b	2733–3595	1667	−	3550	2860	−817 ~ 45	−1193
	A2	6489–7389	5966–8066	7842–8096	7400	8065	−911 ~ −11	−2099 ~ 1
	B1	3471–3686	2225	−	3550	2860	−79 ~ 136	−635
	B2	−	3234–4634	4617–5962	5047	4530	−	−1296 ~ 104

Note: CC means the situation with climate change (warming); NCC is without climate change.

Table 5 Comparison of water stressed population in the world with other studies using the indicator W/Q (>0.4) (in million persons).

		CC		NCC	Effect of climate warming (CC-NCC)
		This study	Alcamo et al. (2007)	This study
Current		2534	2278	2534	0
2025	A1b	3618–3744	−	3706	−88 ~ 38
	A2	4165–4761	4004–4138	4744	−579 ~ 17
	B1	3800–3838	−	3789	11 ~ 49
	B2	−	3755–3888	3703	−
2055	A1b	4301–4754	−	4764	−463 ~ −10
	A2	6991–7578	6657–6806	7567	−576 ~ 11
	B1	4163–4591	−	4556	−393 ~ 35
	B2	−	5147–5241	4776	−
2075	A1b	4146–4971	−	4657	−511 ~ 314
	A2	8181–8913	6879–8030	9011	−830 ~ −98
	B1	3799–4267	−	4239	−440 ~ 28
	B2	−	5650–5962	5436	−

Note: CC means the situation with climate change (warming); NCC is without climate change.

Table 6 List of the 20 most water-stressed countries at present according to population living in water-stressed basins by index W/Q > 0.4 (The percentage shows the share of highly water-stressed population in the total population).

Rank	Country	Water stressed population (10^6)	National mean W/c (m^3 c^-1 year^-1)	National mean Q/c (m^3 c^-1 year^-1)	National W/Q
1	India	774.9 (77%)	639	1198	0.53
2	China	562.0 (43%)	488	1638	0.30
3	Indonesia	146.7 (69%)	390	10701	0.04
4	Pakistan	144.5 (98%)	1160	499	2.33
5	USA	98.6 (35%)	1712	13173	0.13
6	Iran	63.6 (86%)	995	1335	0.75
7	Mexico	60.9 (61%)	780	2292	0.34
8	Japan	50.4 (40%)	697	3223	0.22
9	Turkey	34.0 (51%)	557	3513	0.16
10	Spain	29.6 (74%)	890	2934	0.30
11	Thailand	27.8 (45%)	1399	5342	0.26
12	Italy	25.8 (45%)	772	2224	0.35
13	Uzbekistan	25.1 (99%)	2299	863	2.66
14	Egypt	24.1 (35%)	988	199	4.97
15	Iraq	23.5 (100%)	1803	600	3.00
16	Afghanistan	23.2 (100%)	1009	1584	0.64
17	Morocco	22.6 (75%)	420	431	0.98
18	Saudi Arabia	19.9 (93%)	806	663	1.22
19	Viet Nam	19.8 (25%)	893	3520	0.25
20	Peru	19.5 (75%)	780	23999	0.03

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