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South Asian agriculture increasingly dependent on meltwater and groundwater


Irrigated agriculture in South Asia depends on meltwater, monsoon rains and groundwater. Climate change alters the hydrology and causes shifts in the timing, composition and magnitude of these sources of water supply. Simultaneously, socio-economic growth increases water demand. Here we use a high-resolution cryosphere–hydrology–crop model forced with an ensemble of climate and socio-economic projections to assess how the sources of irrigation water supply may shift during the twenty-first century. We find increases in the importance of meltwater and groundwater for irrigated agriculture. An earlier melt peak increases meltwater withdrawal at the onset of the cropping season in May and June in the Indus, whereas increasing peak irrigation water demand during July and August aggravates non-renewable groundwater pumping in the Indus and Ganges despite runoff increases. Increasing inter-annual variability in rainfall runoff increases the need for meltwater and groundwater to complement rainfall runoff during future dry years.

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Fig. 1: Historical irrigation withdrawals by source and projected future changes.
Fig. 2: Future shifts in runoff and irrigation demand.
Fig. 3: Shifting composition of irrigation withdrawals in the Indus basin.
Fig. 4: Composition of irrigation withdrawals during years with highest irrigation demand.
Fig. 5: Contribution of meltwater and groundwater to irrigation for key crop types in the Indus river basin.
Fig. 6: Non-renewable groundwater abstraction.

Data availability

The data generated in this study (that is, outputs of model simulations) are available in an online archive at Elevation data used in this study are available at The reference climate data and downscaled climate change scenarios used in this study are available at Glacier outlines used in this study are available at Snow-cover data used in this study are available at Soil data used in this study are available at Land use data used in this study are available at and SSP data used in this study are available at Population data used in this study are available at IMAGE v3.0 data used in this study are available at

Code availability

Code for the SPHY model is available at Code for the LPJmL model is available at


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Part of this work was carried out by the Himalayan Adaptation, Water and Resilience (HI-AWARE) consortium under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) with financial support from the UK government’s Department for International Development and the International Development Research Centre, Ottawa, Canada. Part of this work was performed for the project ‘Targeting a climate change hotspot: science to support the SDGs and sustainable water management in the transboundary Indus river basin (SustainIndus)’ and received funding from the Netherlands Organization for Scientific Research under the WOTRO Joint Sustainable Development Goals (SDG) research programme (grant W 07.30318.002). The views expressed in this work are those of the creators and do not necessarily represent those of the UK government’s Department for International Development, the International Development Research Centre, Canada, or its board of governors and are not necessarily attributable to their organizations.

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Authors and Affiliations



A.F.L., H.B., C.S. and W.W.I. designed the study. R.R.W., A.F.L. and S.N. developed and ran the upstream model. H.B. developed the downstream model with help from C.S. A.F.L. downscaled future climate forcing, and H.B. and R.R.W. implemented socio-economic scenarios. A.F.L. and H.B. analysed the data and prepared the figures. A.F.L. wrote the article with major contributions from all co-authors.

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Correspondence to A. F. Lutz.

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Nature Climate Change thanks Yong Nie, Xiaoming Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Historical irrigation withdrawal and projected future changes.

Average annual irrigation withdrawals during 1981–2010 (IWREF) (panel a). Change in average annual irrigation withdrawal (ΔIW) between 2071–2100 and 1981–2010 for the ensemble mean of RCP4.5-SSP1 (panel b) and RCP8.5-SSP3 (panel c). Background digital elevation model (GTOPO30) from ref. 45.

Extended Data Fig. 2 Historical irrigation withdrawals by source and projected future changes (RCP8.5-SSP3).

a) Average contribution of glacier and snowmelt (GS) contribution to irrigation withdrawal during 1981–2010 (IWREF). Grid cells with IWREF < 10 mm yr−1 are excluded. b) RCP8.5-SSP3 ensemble mean of projected changes in GS contribution to irrigation withdrawal for 2071–2100 vs 1981–2010. c) Thirty-year average monthly irrigation withdrawals for the Indus, Ganges and Brahmaputra basins during 1981–2010 differentiated by source. GS = glacier and snowmelt, RB = rainfall-runoff and baseflow, GW = groundwater. Black line indicates RCP8.5-SSP3 ensemble mean of projected change in average monthly total irrigation withdrawal 2071–2100 vs 1981–2010 (ΔIW). Error bars indicate the ensemble spread in projections. d) Average monthly projected changes in irrigation withdrawal per source for 2071–2100 vs 1981–2010 (ΔIW). Lines and shading indicate the ensemble mean and ensemble range for RCP8.5-SSP3. Upstream and downstream river basin boundaries (light grey tones) and main rivers (dark grey tones) are indicated in panels a and b. Background digital elevation model (GTOPO30) from ref. 45. River data from ref. 46.

Extended Data Fig. 3 Historical and projected future contributions to irrigation withdrawals for groundwater and rainfall and baseflow.

Contributions of groundwater (GW, panel a) and rainfall and baseflow (RB, panel b) to irrigation withdrawals (IW) during the reference period. Ensemble mean projections for change in groundwater contribution (∆IWGW) and rainfall and baseflow contribution (∆IWRB) between 2071–2100 and 1981–2010 for RCP4.5-SSP1 (panels c, d) and RCP8.5-SSP3 (panels e,f).

Extended Data Fig. 4 Shifting sources of irrigation withdrawal in the Indus basin during the month of May.

Dots indicate annual fractional basin-averaged contribution to irrigation withdrawal from groundwater (x-axis), meltwater (y-axis) and rainfall and baseflow (indicated by grey lines), for inidvidual years 1981–2100. Convex hulls indicate the range of years 1981–2010, 2036–2065, and 2071–2100). The color scale shows the 30 year moving average starting at 1981–2010 and ending at 2071–2100. Separate plots are shown for cold/wet (a), cold/dry (b), warm/dry (c), and warm/wet (d) future scenarios. In each panel results are shown for RCP4.5-SSP1 (lower left part of panel) and RCP8.5-SSP3 (upper right part of panel, with flipped axis direction).

Extended Data Fig. 5 Shifting sources of irrigation withdrawal in the Indus basin during the month of August.

Dots indicate annual fractional basin-averaged contribution to irrigation withdrawal from groundwater (x-axis), meltwater (y-axis) and rainfall and baseflow (indicated by grey lines), for inidvidual years 1981–2100. Convex hulls indicate the range of years 1981–2010, 2036–2065, and 2071–2100). The color scale shows the 30 year moving average starting at 1981–2010 and ending at 2071–2100. Separate plots are shown for cold/wet (a), cold/dry (b), warm/dry (c), and warm/wet (d) future scenarios. In each panel results are shown for RCP4.5-SSP1 (lower left part of panel) and RCP8.5-SSP3 (upper right part of panel, with flipped axis direction).

Extended Data Fig. 6 Contribution of meltwater and groundwater to irrigation for key crop types in the Ganges river basin.

Panels a-c show the 30 year daily mean contribution of meltwater to irrigation during the reference period (1981–2010) and end of century period (2071–2010) for each ensemble member in the RCP4.5-SSP1 and RCP8.5-SSP3 ensembles, for rice (a), wheat (b), and sugarcane (c). Panels d-f show the same for the groundwater contribution to irrigation for rice (d), wheat (e), and sugarcane (f).

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Lutz, A.F., Immerzeel, W.W., Siderius, C. et al. South Asian agriculture increasingly dependent on meltwater and groundwater. Nat. Clim. Chang. 12, 566–573 (2022).

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