The depletion of groundwater resources threatens food and water security in India. However, the relative influence of groundwater pumping and climate variability on groundwater availability and storage remains unclear. Here we show from analyses of satellite and local well data spanning the past decade that long-term changes in monsoon precipitation are driving groundwater storage variability in most parts of India either directly by changing recharge or indirectly by changing abstraction. We find that groundwater storage has declined in northern India at the rate of 2 cm yr in southern India between 2002 and 2013. We find that a large fraction of the total variability in groundwater storage in north-central and southern India can be explained by changes in precipitation. Groundwater storage variability in northwestern India can be explained predominantly by variability in abstraction for irrigation, which is in turn influenced by changes in precipitation. Declining precipitation in northern India is linked to Indian Ocean warming, suggesting a previously unrecognized teleconnection between ocean temperatures and groundwater storage. S ignificant depletion of groundwater storage in a number Changes in groundwater storage 32We estimated groundwater storage anomalies from GRACE for visible at GRACE resolution. However, standardized anomalies of groundwater level and GRACE-based groundwater storage change showed a close correspondence for north and south India, with correlation coefficients of 0.46 and 0.77 respectively (Fig. 1i,j). GRACE groundwater anomalies show a large pattern of declining groundwater in north India, but increasing groundwater level in south India. However, it is unclear if these patterns of changes in groundwater anomalies in north and south India are driven by groundwater abstraction for irrigation or long-term changes in precipitation. Trends were estimated using the non-parametric Mann-Kendall test and Sen's slope method. Monthly anomalies for January, May, August, and November were estimated from GRACE and in situ observations after removing the monthly mean. In situ groundwater well observations from the CGWB are available only for four months (January, May, August, and November). i,j, Area-averaged standardized departure (after removing mean and dividing by the standard deviation) from GRACE and in situ well observations for north (above 1996-2013 in a majority of observation wells located in north 1 India (23 • north, Fig. 2a-d). Moreover, we find that the number is a major crop-growing period ( Supplementary Fig. 2). In India, located in south India, which is consistent with GRACE data (Fig. 1). 13However, a minority of wells in each region show opposite trends 14 of decreasing groundwater levels in southern India and increasing 15 groundwater levels in northern India, highlighting the complexity 16 and heterogeneity of the data and localized influence of groundwater 17 pumping and recharge (Fig. 2). (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(...

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The 2015 drought in the Indo‐Gangetic Plain posed new challenges related to food and water security and affected the lives of millions. All‐India monsoon rainfall in 2015 was the tenth driest year on record (1906–2015) with a deficit of 14.5%, and the Indo‐Gangetic Plain witnessed a rainfall deficit of 25.8% (third rank event). Drought severity was amplified by deficits from the previous years in the Indo‐Gangetic Plain and other parts of India. The Indo‐Gangetic Plain faced a 2 year cumulative deficit of 51%, and the drought of 2014–2015 was unprecedented with a return period of 542 years. The GRACE data showed the occurrence of consecutive negative terrestrial water storage and groundwater anomalies in 2014 and 2015, mainly centered over the Indo‐Gangetic Plain region. Notwithstanding uncertainty in future projections, the multiyear droughts in the same regions can pose challenges for water resources and agriculture.

Groundwater is a lifeline for millions of people in India, which is affected by the year‐to‐year variability of precipitation amount and characteristics (low and high intensity). Precipitation intensity has been observed and projected to change in India. However, the crucial impact of precipitation intensity on groundwater recharge in India remains unknown. Here we use in situ data from more than 5,800 groundwater wells to show that precipitation intensity is strongly linked with groundwater recharge in India. In the northwest and north central India, the monsoon season groundwater recharge is linked with the low‐intensity precipitation, while in South India high‐intensity precipitation is a major driver of groundwater recharge. Observed long‐term changes in precipitation characteristics show a decline in the low‐intensity rain in the northwest and north central India that are strongly driven by sea surface temperature over the Pacific Ocean. Increases in the high‐intensity precipitation in South India are linked with the sea surface temperatures in the Atlantic Ocean. Our results highlight the importance of precipitation intensity for the monsoon season groundwater recharge in India, which can provide insights to sustainably manage rapidly declining groundwater resources in India.

Prediction of vegetation anomalies at regional scales is essential for management of food and water resources. Forecast of vegetation anomalies at 1–3 months lead time can help in decision making. Here we show that normalized difference vegetation index (NDVI) along with other hydroclimatic variables (soil moisture and sea surface temperature) can be effectively used to predict vegetation anomalies in India. The spatiotemporal analysis of NDVI showed significant greening over the region during the period of 1982–2013. The root‐zone soil moisture showed a positive correlation with NDVI, whereas the El Niño–Southern Oscillation index (Nino 3.4) is negatively correlated in most of the regions. We extended this relationship to develop a model to predict NDVI in 1 to 3 months lead time. The predicted vegetation anomalies compare well with observations, which can be effectively utilized in early warning and better planning in water resources and agricultural sectors in India.