Downscaling GRACE storage change to analyze groundwater dynamics and drought evaluation in the Ganga Basin

Groundwater over-exploitation, coupled with accelerated climate change, has led to a declining water table and multiple droughts over the Ganga basin. Monitoring this with in situ observations and modeling is limited due to inadequate data. The Gravity Recovery and Climate Experiment (GRACE) helped to overcome this limitation, but its coarse spatial resolution undermined the local abstractions. In this study, we employed monthly climatology-based regression models to downscale GRACE-change in terrestrial water storage (∆TWS) from its native resolution to a 0.25° × 0.25° grid. The random forest model outperformed others, achieving a better Pearson correlation of 0.78 and a root mean square error (RMSE) of 12.3 cm. Further, it was also found that both groundwater storage changes (∆GWS) estimated from the downscaled data and well observations showed a consistent declining trend across the basin. In comparison to previous studies, the fine-resolution ∆GWS showed a steeper declining trends of 4.69 to 7.16 cm/year, over Delhi-NCR and Western Uttar Pradesh. Additionally, we identified major hydrometeorological drought events using multiple drought indices, with the period from August 2015 to October 2017 being the most intense, lasting 27 months. Overall, the findings of this study enhance the understanding of local-scale groundwater abstractions, hence contributing to sustainable water resource management.