Integrating depression storages and their spatial distribution in watershed-scale hydrologic modeling

Abstract

Surface depressions are important topographic characteristics for surface runoff initiation, and the spatial distribution of depressions may further affect the timing and quantity of surface runoff reaching channels and outlets. However, many hydrologic models simulate the fill-spill processes for depression-dominated areas in a lumped manner and release outflows from depressions to channels or outlets directly. As a result, the progressive formation of contributing area (CA) and the dynamic runoff contribution process are not well characterized. The objective of this study is to improve depression-oriented hydrologic modeling by incorporating the influence of depression storages and their spatial distribution into the simulation of surface runoff generation and flow routing. To achieve this objective, a modified depression-oriented variable contributing area (MD-VCA) model is developed to simulate the depression-dominated catchment response during rainfall events, which employs a new depressional time-area zone scheme to deal with the spatially distributed depression storages, tracks the intrinsic changing patterns of the connected areas and depression storage, simulates the connected area-based surface runoff generation dynamics, implements a new CA-based surface runoff routing technique, and quantifies the likelihood of occurrence of outlet CA and runoff contributions using the joint probability distribution associated with depression storages and their spatial distribution. The performance of the MD-VCA model was evaluated through the application to a depression-dominated watershed in the Prairie Pothole Region of North Dakota. Simulation results demonstrated that the MD-VCA model was able to simulate the threshold-controlled overland flow dynamics under different rainfall conditions, and it effectively revealed the influences of depression storages and their spatial distribution on surface runoff generation and propagation processes.