SWAT-Based Streamflow and Embayment Modeling of Karst-Affected Chapel Branch Watershed, South Carolina

Abstract

SWAT is a GIS-based basin-scale model widely used for the characterization of hydrology and water quality of large, complex watersheds; however, SWAT has not been fully tested in watersheds with karst geomorphology and downstream reservoir-like embayment. In this study, SWAT was applied to test its ability to predict monthly streamflow dynamics for a 1,555 ha karst watershed, Chapel Branch Creek, which drains to a large embayment and is comprised of highly diverse land uses. SWAT was able to accurately simulate the monthly streamflow at a cave spring (CS) outlet draining mostly agricultural and forested lands and a golf course plus an unknown groundwater discharging area, only after adding known monthly subsurface inputs as a point source at that location. Monthly streamflows at two other locations, both with multiple land uses, were overpredicted when lower lake levels were prevalent as a result of surface water flow to groundwater (losing streams). The model underpredicted the flows during rising lake levels, likely due to high conductivity and also a deep percolation coefficient representing flow lost to shallow and deep groundwater. At the main watershed outlet, a wide section performing as a reservoir embayment (R-E), the model was able to more accurately simulate the measured mean monthly outflows. The RE storage was estimated by using a daily water balance approach with upstream inflows, rainfall, and PET as inputs and using parameters obtained by bathymetric survey, LiDAR, and downstream lake level data. Results demonstrated the substantial influence of the karst features in the water balance, with conduit and diffuse flow as an explanation for the missing upstream flows appearing via subsurface conveyance to the downstream cave spring, thus providing a more accurate simulation at the embayment outlet. Results also highlighted the influences of downstream lake levels and karst voids/conduits on the watershed hydrologic balance. Simulation performance of hydrology could be improved with more accurate DEMs obtained from LiDAR for karst feature identification and related modification of SWAT parameters. This SWAT modeling effort may have implications on nutrient and sediment loading estimates for TMDL development and implementation in karst watersheds with large downstream embayments that have significant changes in water level due to adjoining lakes.

The Impacts of Climate Variability and Land Use Change on Streamflow in the Hailiutu River Basin

“…In the SWAT model, two forms of groundwater storage (shallow and deep) are applied, of which only the shallow storage is active to simulate the groundwater flow. Researchers found that SWAT has poor performance in dry seasons or in areas where groundwater system is complicated and groundwater is the main source of streamflow [64][65][66]. Therefore, using more active groundwater storage to simulate the groundwater flow could result in a more realistic representation of hydrological cycle in these special cases.…”

Streamflow and Nutrients from a Karst Watershed with a Downstream Embayment: Chapel Branch Creek

“…An Infinities data logger (Port Orange, FL) measured stream stage, and an ISCO 2700 automated water sampler took daily time-based water quality samples. Flow was calculated from a rating curve developed by repeated manual stream cross-sectional flow measurements (Amatya et al 2010(Amatya et al , 2011a. This instrument collected valid measurements from January to October 2009.…”

“…Understanding watershed hydrology is critical to management decisions such as total maximum daily load (TMDL) development, as hydrology is often a primary driving force for nutrient cycling and loading dynamics and subsequent downstream water quality effects (Amatya et al 2011a). Karst watersheds have complex hydrologic and transport processes by which groundwater can variably influence surface water flow, both in magnitude and duration.…”

“…Rather than occurring as overland and channel flow via streams, karst water flows below ground through systems of conduits and fractures until it typically emerges as a spring (White 1988). The geology of karst-influenced watersheds has been generally characterized by very high infiltration rates perhaps because of some direct linkage between the surface and subsurface conduits (Felton 1994;Pasquarell and Boyer 1995;Boyer and Pasquarell 1996;Baffaut and Benson 2009;Amatya et al 2011a). Pasquarell and Boyer (1995) reported fecal bacteria can travel in karst aquifers over distances of several kilometers and that karst resurgence springs of the most intensively agricultural basin were contaminated with these bacteria.…”

Application of SWAT Model with a Modified Groundwater Module to the Semi-Arid Hailiutu River Catchment, Northwest China

“…Shirmohammadi et al [18] observed that the SWAT underestimates groundwater flow, especially during wet periods, in a piedmont physiographic region. Amatya et al [19] found that the SWAT was unable to get accurate monthly outflows simulation results when it was applied to simulate streamflow in a karst watershed where runoff was dominated by groundwater. Cheng et al [20] observed that the SWAT model was not effective in simulating the base flow in the Kuye River basin, a basin with coarse sand in the middle of the Yellow River watershed with a semi-arid climate.…”