A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions

Abstract

Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes.