Incorporating landscape depression heterogeneity into the Soil and Water Assessment Tool (SWAT) using a probability distribution

Abstract

Modelling the hydrology of North American Prairie watersheds is complicated because of the existence of numerous landscape depressions that vary in storage capacity. The Soil and Water Assessment Tool (SWAT) is a widely applied model for long‐term hydrological simulations in watersheds dominated by agricultural land uses. However, several studies show that the SWAT model has had limited success in handling prairie watersheds. In past works using SWAT, landscape depression storage heterogeneity has largely been neglected or lumped. In this study, a probability distributed model of depression storage is introduced into the SWAT model to better handle landscape storage heterogeneity. The work utilizes a probability density function to describe the spatial heterogeneity of the landscape depression storages that was developed from topographic characteristics. The integrated SWAT–PDLD model is tested using datasets for two prairie depression dominated watersheds in Canada: the Moose Jaw River watershed, Saskatchewan; and the Assiniboine River watershed, Saskatchewan. Simulation results were compared to observed streamflow using graphical and multiple statistical criterions. Representation of landscape depressions within SWAT using a probability distribution (SWAT–PDLD) provides improved estimations of streamflow for large prairie watersheds in comparison to results using a lumped, single storage approach. Copyright © 2016 John Wiley & Sons, Ltd.

On the relationship between flood and contributing area

“…Modelling schemes that can account for dynamic contributing areas have begun to emerge and could produce data to fill this gap. These have been shown to improve streamflow prediction (Evenson, Golden, Lane, & D'Amico, ; Hay et al, ; Mekonnen et al, ; Mekonnen, Mazurek, & Putz, ; Reaney et al, ; Smith et al, ; Wang, Yang, & Melesse, ; Yang et al, ), so there is confidence in their ability to simulate contributing area (Spence & Mengistu, ). However, there are two key shortcomings that prevent the use of these existing data for hypothesis testing using the mathematical framework above.…”

An improved representation of geographically isolated wetlands in a watershed‐scale hydrologic model

“…Mekonnen et al . () refined SWAT by representing depressional storage heterogeneity using a probability distribution function. However, Mekonnen et al .…”

SWAT Modeling for Depression-Dominated Areas: How Do Depressions Manipulate Hydrologic Modeling?

“…However, due to a series of complexities related to these depressions and their characteristics (e.g., hydrologic connectivity of depressions), hydrologic modeling for the PPR is a challenging task [2]. Different studies have been conducted to address the depression storage effects and simulate the characteristics of depression-dominated areas [3][4][5][6][7][8][9]. For example, Chu et al [6] developed a physically based hydrologic model which took the dynamic variations of puddles into account.…”

“…For instance, Yactayo [18] developed SWAT-karst by accounting for the unique relationship between surface water and groundwater in karst environments at a HRU scale to simulate hydrologic processes and nitrogen transport. Mekonnen et al [8] incorporated the heterogeneity of depression storage into the SWAT modeling. Their modified model, SWAT-probability distribution landscape distribution (SWAT-PDLD), was calibrated and validated for two watersheds within the PPR of North America [8].…”

“…Mekonnen et al [8] incorporated the heterogeneity of depression storage into the SWAT modeling. Their modified model, SWAT-probability distribution landscape distribution (SWAT-PDLD), was calibrated and validated for two watersheds within the PPR of North America [8]. They employed ArcGIS [19] tools to identify depressions, their storage and surface area.…”