Strongly heterogeneous patterns of groundwater depletion in Northwestern India

•High resolution spatio-temporal patterns of GW depletion in NW India for 1974-2010.•Hotspots of depletion broadly match groundwater abstraction metrics.•Spatial inhomogeneity in depletion is not explained by GW abstraction data.•Groundwater level decline corresponds with large-scale aquifer sedimentology. Northwestern India has been identified as a significant hotspot of groundwater depletion, with major implications for groundwater sustainability caused by excessive abstraction. We know relatively little about the detailed spatial and temporal changes in groundwater storage in this region, nor do we understand the interplay of factors controlling these changes. Groundwater managers and policymakers in India require such information to monitor groundwater development and make strategic decisions for the sustainable management of groundwater. Here, we characterise high-resolution spatio-temporal variability in groundwater levels and storage change across northwestern India through analysis of in situ measurements of historical groundwater level data. We note a slow gain in groundwater storage of + 0.58 ± 0.35 km3 for the pre-monsoon and + 0.40 ± 0.35 km3 for the post-monsoon period between 1974 and 2001. However, from 2002 to 2010, groundwater storage was rapidly depleted by −32.30 ± 0.34 km3 in the pre-monsoon and −24.42 ± 0.34 km3 in the post-monsoon period. Importantly, we observe marked spatial heterogeneity in groundwater levels and storage change and distinct hotspots of groundwater depletion with lateral length scales of tens of kilometers. Spatial variability in groundwater abstraction partially explains the depletion pattern, but we also find that the sedimentological heterogeneity of the aquifer system correlates broadly with long-term patterns of groundwater-level change. This correlation, along with the spatial agreement between groundwater level change and water quality, provides a framework for anticipating future depletion patterns and guiding groundwater monitoring and domain-specific management strategies.