Estimation of spatio-temporal groundwater storage variations in the Lower Transboundary Indus Basin using GRACE satellite

• Uncertainty measurement of different GRACE products. • EOF analysis to compute spatio-temporal variability in groundwater storage . • Groundwater storage depletion. • Impact of climate change on groundwater storage. In the Lower Transboundary Indus Basin (LTIB), excessive groundwater is being consumed in combination with surface water to meet the increasing demand for irrigation and resulting in groundwater depletion. This study employed the generalized three-cornered hat method (GTCH) to assess uncertainty of different Gravity Recovery and Climate Experiment (GRACE) derived-terrestrial water storage anomalies (TWSA) measurements using GRACE (-TWSA) data and the variance variability in space and time of GRACE derived groundwater storage anomalies (GWSA) using Empirical Orthogonal Function (EOF) analysis, respectively. Furthermore, monthly GRACE derived GWSA were estimated using Global Land Data Assimilation System (GLDAS) model data and GWSA time series trend and depletion of groundwater storage were evaluated using the MannKendal (MK) trend test and Sen’s slope estimator in the LTIB. The TWSA and precipitation data depict seasonal characteristics with peaks in the summer and dips in the winter, which reflect variation in GWSA, respectively. Additionally, it is observed that the variations in GWSA exhibit a downward trend from 2003 to 2016. The results revealed that more than 80% of total variance variability was explained by the first 2 EOF modes. The results showed that GRACE derived GWSA is being depleted at a rate of 4.16 ± 0.26 mm per year (2.97 ± 0.19 km 3 per year). Long-term monthly mean of GRACE derived GWSA showed remarkable agreements of correlation of determination (R 2 ) with PCRaster Global Balance (PCR-GLOBWB) model 75% and WGHM (WaterGap Global Hydrological model) 81%. The GRACE-derived GWSA also showed a good correlation of 0.69 and 0.82 with in situ data on seasonal and annual scales, respectively. This study would be insightful to calculate the agro-economic impact of excessive groundwater withdrawal.