Contributions of Climate Variability and Anthropogenic Activities to Confined Groundwater Storage in Hengshui, North China Plain

Groundwater storage (GWS) in confined aquifer systems is often influenced by climate variability and anthropogenic activities, and it is vital to quantify their contributions for the purpose of groundwater management and surface water allocation plans. In this study, we characterize the spatiotemporal evolution of the GWS in confined aquifer systems across Hengshui, North China Plain, and investigate its relationships with changing climate conditions and human activities through the integration of InSAR-derived surface displacements with hydraulic head observations and precipitation data, during 2004-2010 and 2016-2020. Our results indicate that the GWS in confined aquifer systems decreased markedly by 4.59 +/- 0.35 km3 with an accelerating trend during the study period. The GWS variations show a strong correlation with precipitation during irrigation periods (March to July), and hence, the climate and anthropogenic-driven GWS variations can be separated from each other with a linear model. We find that the GWS depletion caused by climate variability and anthropogenic activities were -0.31 +/- 0.10 km3 and -4.28 +/- 0.40 km3, respectively, during the study period. The mean contribution of anthropogenic activities to the GWS variations was -71.9%, implying that the GWS variations in confined aquifer systems were primarily anthropogenic driven. It is also found that the well observations alone poorly characterize the spatiotemporal evolution of the GWS due to their limited spatial density, and the integrated InSAR/well approach appears to be promising for overcoming this challenge.

Automated summary

In this study, the spatiotemporal evolution of groundwater storage (GWS) in a confined aquifer system in Hengshui, North China Plain was analyzed. The results show a significant decrease in GWS during the study period, primarily driven by climate variability and anthropogenic activities. The integration of different data sources allows for the separation of these two influences. Additionally, traditional well observations alone are insufficient to capture the spatiotemporal evolution of GWS due to their limited spatial density.