SWAT Modeling of Non-Point Source Pollution in Depression-Dominated Basins under Varying Hydroclimatic Conditions

Abstract

Non-point source (NPS) pollution from agricultural lands is the leading cause of various water quality problems across the United States. Particularly, surface depressions often alter the releasing patterns of NPS pollutants into the environment. However, most commonly-used hydrologic models may not be applicable to such depression-dominated regions. The objective of this study is to improve water quantity/quality modeling and its calibration for depression-dominated basins under wet and dry hydroclimatic conditions. Specifically, the Soil and Water Assessment Tool (SWAT) was applied for hydrologic and water quality modeling in the Red River of the North Basin (RRB). Surface depressions across the RRB were incorporated into the model by employing a surface delineation method and the impacts of depressions were evaluated for two modeling scenarios, MS1 (basic scenario) and MS2 (depression-oriented scenario). Moreover, a traditional calibration scheme (CS1) was compared to a wet-dry calibration scheme (CS2) that accounted for the effects of hydroclimatic variations on hydrologic and water quality modeling. Results indicated that the surface runoff simulation and the associated water quality modeling were improved when topographic characteristics of depressions were incorporated into the model (MS2). The Nash–Sutcliffe efficiency (NSE) coefficient indicated an average increase of 30.4% and 19.6% from CS1 to CS2 for the calibration and validation periods, respectively. Additionally, the CS2 provided acceptable simulations of water quality, with the NSE values of 0.50 and 0.74 for calibration and validation periods, respectively. These results highlight the enhanced capability of the proposed approach for simulating water quantity and quality for depression-dominated basins under the influence of varying hydroclimatic conditions.

Evaluation of the Offsets of Artificial Recharge on the Extra Run-Off Induced by Urbanization and Extreme Storms Based on an Enhanced Semi-Distributed Hydrologic Model with an Infiltration Basin Module

“…This type of underestimation of the spring peaks due to snowmelt can be attributed to the limited capability of SWAT to simulate snowpack-and snowmelt-related hydrologic processes in cold regions. Similar findings were also demonstrated by Shabani et al [33], Tahmasebi Nasab et al [34], and Zeng et al [35] in their SWAT modifications and applications to watersheds in cold regions. CH_N1.sub Manning's "n" value for the tributary channels 0.065375 Note(s): * The relative method was applied for those parameters, and the replace method was applied for the rest of the parameters.…”

“…This type of underestimation of the spring peaks due to snowmelt can be attributed to the limited capability of SWAT to simulate snowpack-and snowmelt-related hydrologic processes in cold regions. Similar findings were also demonstrated by Shabani et al [33], Tahmasebi Nasab et al [34], and Zeng et al [35] in their SWAT modifications and applications to watersheds in cold regions.…”

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

“…The black box shows the location of Devils Lake and Sheyenne River within the RRNB. Two graphs at the top left show observed daily water levels of Devils Lake from 1993 to 2018 and simulated variation of sulfate concentration from the west end to the east end on July 1, 2012 (Shabani et al ). Two rectangles in the sulfate distribution insert denote the approximate locations of the West and East outlets.…”

“…For calibration, the SWAT Calibration Uncertainty Program (Abbaspour ) was used to run the model for 2000 iterations using SUFI‐2 algorithm to evaluate the sensitivity of daily discharge simulated at the four gauging stations for the 22 parameters listed in Table . This set of parameters was used to properly characterize snowmelt, soil and land management, channel conditions, wetlands, and potholes within the watershed (Wang et al ; Kharel et al ; Shabani et al ; Tahmasebi Nasab et al ). Among the parameters, the simulated discharge was found to be sensitive to the following seven: threshold temperature for snowmelt, snowmelt lag factor, curve number, baseflow recession constant, soil evaporation compensation coefficient, effective hydraulic conductivity, and Manning’s roughness coefficient for the main channel.…”

Incorporating the Filling–Spilling Feature of Depressions into Hydrologic Modeling

“…Hydrologic models have become an effective tool to explore the spatial and temporal variations of hydrologic processes, evaluate water quantity and quality, as well as provide valuable information for water resources management and planning [1][2][3][4]. However, it was found that traditional hydrologic models, where surface depressions are often removed to create a well-connected drainage system, tend to overestimate streamflow [5][6][7] and may not reproduce the spatial distribution of water yields [7] for depression-dominated watersheds. Therefore, incorporating the influences of depressions into hydrologic modeling is of significance for understanding depression-oriented hydrologic processes and estimating water resources of depression-dominated areas.…”