Spatiotemporal variability analysis of nutrient and sediment loads in surface water using improved hydrologic modeling for depression-dominated watersheds.

This project helps engineers study how nutrients and sediment move over time and space in watersheds that contain many surface depressions. Typical hydrological models often miss the way these depressions store water and then release it, which can make water‑quality forecasts inaccurate. To fix that, the project adds a new modeling framework that directly includes depressional storage, fill‑and‑spill behavior, and the slowing of runoff in local low spots. The model runs simulations of total suspended solids, nitrogen, and phosphorus for different time periods and landscape layouts. This lets us see whether small depressions reduce or increase the amount of pollutants that reach downstream areas. We will calibrate the updated model

with past weather records, land‑use maps, and water‑quality measurements. The finished framework gives clear guidance for evaluating watershed‑scale conservation actions and for predicting nutrient‑sediment loads when climate conditions change. Environmental engineers can use this tool to fine‑tune watershed management plans and to improve monitoring of surface‑water quality in areas with complex terrain.

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