Presentation: 2025 ND EPSCoR Annual conference
October 21, 2025, NDSU Memorial Union, Fargo, North Dakota
Redefinition of hydrologic response units for capturing dynamic partial contributing areas in depression-dominated watersheds
Tiansong
Qi
Doctoral Student
North Dakota State University
Co-author: Xuefeng Chu, Professor, North Dakota State University
Session
Poster number: 94
Ballroom
Surface depressions are important topographic properties of watersheds and play a significant role in watershed hydrologic cycle by affecting surface runoff generation and other processes. The filling-spilling-merging (FSM) processes over surface depressions result in dynamic variations in runoff contributing areas. However, such complex hydrologic dynamics are usually oversimplified in conventional watershed models. The objective of this study is to improve watershed-scale hydrologic modeling by capturing the dynamic nature of contributing areas in depression-dominated watersheds. To achieve this objective, spatial distributions and topographic properties of individual surface depressions were characterized and incorporated into watershed modeling for simulating the threshold-controlled FSM dynamics of depressions. The specific tasks included: (1) develop a new depression-oriented, four-factor hydrologic response unit (HRU) redefinition technique to incorporate the spatial distribution of each surface depression and (2) utilize an HRU-level, threshold-controlled depression module to simulate the FSM dynamics. In the four-factor HRU redefinition technique, individual surface depressions were conceptualized as depressional HRUs, based on which a modified Soil and Water Assessment Tool (SWAT) was developed. A depression module was integrated into the modified SWAT to simulate overflow from surface depressions for each redefined depressional HRU and dynamic variations in runoff contributing areas. The new modeling approach was applied to the Upper Forest River watershed in North Dakota, demonstrating its improved capability and enhanced performance in watershed modeling.
