Contribution of anthropogenic and hydroclimatic factors on the variation of surface water extent across the contiguous United States

Human pressure and climate variability are significantly threatening freshwater resources, with cascading effects on societies and ecosystems. In this context, it is crucial to understand the anthropogenic and climatic impacts on surface water dynamics. Here, we examine the interaction between the variation of surface water extent and the change in five potential concurrent drivers across river basins of the contiguous United States (CONUS) during the period 1984-2020. In particular, built-up area, population, and irrigated land are regarded as the anthropogenic drivers, while hydroclimatic drivers are represented by precipitation and potential evapotranspiration (PET). We perform statistical analyses in order to quantify the change in the considered variables and then identify significantly different spatial patterns and possible interrelations. Results show that almost 79% (169 out of 204 river basins) of the CONUS experienced an expansion of surface water extent mainly in the continental and temperate climatic regions (mean expansion 158.33 km(2)). Increasing precipitation is found to be the most widespread driver of the gain in surface water extent, affecting nearly 70% of river basins. The remaining 35 river basins of the CONUS, mostly located in the arid southwestern region of the country, faced a reduction in surface water extent (mean reduction -146.73 km(2)). The expansion of built-up areas and increasing PET resulted to contribute to the loss of surface water in all the river basins, followed by population growth (in similar to 75% of the river basins), decreasing precipitation (in similar to 60% of the river basins, all situated in southwestern US), and irrigated land expansion (in similar to 55% of the river basins). Our findings shed light on the potential impacts of the variability of anthropogenic and hydroclimatic factors on hydrology and surface water resources, which could support predictive adaptation strategies that ensure water conservation.