This study employs the Darcy-Brinkman-Stokes equations to characterize the coupled seepage process in porous media of the karst aquifer and the free flow process in karst conduit and stream. Results show that the impact of different water retention models on the interaction process is quite significant. The degree of change in water level of the stream also varies, and this change can affect the ease with which different strata media in the karst aquifer recharge the stream.

This study explores how climate change affects river temperatures under hydropower influence using numerical modeling. While average warming is similar to natural rivers, hydropower both increases vulnerability in low-flow areas and helps limit extreme temperatures through cold lake releases in summer. This research helps adapt hydropower production to protect aquatic species in a changing climate.

Environmental changes can cause hydrological model biases that vary over time (nonstationarity). We demonstrate a new calibration framework to detect and correct nonstationary streamflow biases after a large wildfire, which reduces predictive uncertainty and constrains parameter equifinality.

This study assesses how small on-farm reservoirs (OFRs) can impact surface hydrology using a new framework combining remote sensing and hydrological modeling. Findings show that reservoirs can reduce annual flow by 14–24 % and peak flow by 43–60 %, with effects varying by location and reservoir's capacity. This is relevant as the number of OFRs is expected to increase globally as an adaptation to climate change under severe drought conditions.

By coupling PLUS-InVEST models under 24 climate-land scenarios, we constructed a water supply-demand risk (WSDR) assessment framework to quantify impacts of climate change and anthropogenic activities on water resource allocation patterns and associated risks. Results demonstrate that significant cultivated land expansion drives a surge in water demand. The root cause lies in frequent anthropogenic perturbations (land use change), which intensify conflicts between water demand-supply capacity.

By involving soil oxygen dynamics, we explore tile drainage impacts on the coupled hydrology–biogeochemistry–crop system. We find that soil oxygen dynamics is the key mediator of tile–system dynamics. Tile drainage lowers soil water content and improves soil oxygen levels, helping crops grow during wet springs. The developed roots also help mitigate drought stress in dry summers. Overall, tile drainage increases crop resilience to climate change, making it a valuable future agricultural practice.

We developed a new method to improve hydrological modeling by jointly using soil moisture and groundwater level data from field sensors in a catchment in Germany. By updating the model separately for shallow and deep soil zones, we achieved more accurate predictions of soil water, groundwater depth, and evapotranspiration. Our results show that combining both data types gives more balanced and reliable outcomes than using either alone.