An Enhanced Modeling Framework for Simulating Hydrologic Processes in a Depression-dominated Watershed

In conventional watershed hydrologic models, it is difficult to account for the impacts of surface depressions on hydrologic processes, as the watershed delineation is based on a depressionless terrain surface. Particularly, it is a challenge to incorporate the influences of individual small surface depressions into watershed-scale models. The aim of this study is to improve the watershed-scale hydrologic modeling by taking into account topographic features, land use and land cover (LULC), and soil types of depressional areas. To achieve this objective, an enhanced modeling framework was proposed, consisting of a surface delineation algorithm, a spatial analysis algorithm for LULC and soil types, and a semi-distributed hydrologic model. A two-step modeling process was performed. First, the topographic properties, LULC, and soil types of individual surface depressions were identified. Second, the semi-distributed hydrologic model was modified to simulate threshold-controlled overland flow processes among individual surface depressions. The enhanced modeling approach was applied to the depression-dominated Upper Forest River watershed in North Dakota. The results demonstrated its capability in the modeling of hydrologic processes under the influence of surface depressions.