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

The Numerical Formulation of Simple Hysteretic Models to Simulate the Large‐Scale Hydrological Impacts of Prairie Depressions

“…In this note, we focus on the general problem of simulating storage‐discharge dynamics in complexes of depressional wetlands (Evenson, Golden, et al., 2018; Fan & Miguez‐Macho, 2011; Golden et al., 2014). We are interested in depressional wetland complexes because the storage dynamics of wetland complexes and the outflow from the wetlands affects the catchment‐scale hydrological connectivity (e.g., Shook & Pomeroy, 2011; M. Mekonnen et al., 2014; Shook et al., 2021; Zeng & Chu, 2021). In framing our work in terms of depressional wetlands, we recognize that the ponds of water in prairie depressions are ephemeral, and hence may not satisfy the strict definition that wetlands must have hydric soils (e.g., van der Kamp et al., 2016).…”

Incorporating the Filling–Spilling Feature of Depressions into Hydrologic Modeling

“…After the surface topography is characterized, the intrinsic influence of depressions on hydrologic connectivity is analyzed by using the method proposed by Zeng and Chu [19]. Specifically, a filling procedure is implemented to determine the relationship between water input and filling-spilling conditions of depressions.…”

“…Following Zeng and Chu [19], the intrinsic changing patterns of depression storage and contributing area of a depression-dominated subbasin are determined, which can be further used to simulate the formation of subbasin-contributing area and generation of surface runoff during a rainfall/snowmelt event. Different from the event model proposed by Zeng and Chu [19], SWAT-D is a continuous model in which more impact factors, such as water losses from depressions, are simulated. Therefore, SWAT-D tracks not only the filling-spilling overland flow dynamics during wet time periods but also water depletion in depressions during dry time periods.…”

“…However, the real influence of depressions cannot be revealed by the lumped depression approach due to a lack of characterizing the filling-spilling-merging-splitting of depressions [14,15]. To represent the filling-spilling dynamics of overland flow, the hydro-topographic characteristics of depressions were analyzed and implemented to improve depression-dominated hydrologic modeling [14][15][16][17][18][19][20]. For example, Wang et al [15] developed an event-based, depression-oriented hydrologic model, in which a depression-dominated subbasin was divided into a non-depressional area and a depressional area.…”

“…Grimm and Chu [16] analyzed the relationship between depression storage and outflow from the depressional area of a subbasin, which was further employed to improve the lumped depression approach. Zeng and Chu [19,20] identified the intrinsic changing patterns of depression storage and contributing area of a depression-dominated subbasin by tracking the filling-spilling processes of depressions. The determined intrinsic changing patterns were further utilized to simulate the variable contributing area, depression storage, and surface runoff for depression-dominated watersheds.…”