Determining Nutrient and Sediment Critical Source Areas with SWAT: Effect of Lumped Calibration

Abstract

In many watershed modeling studies, due to limited data, model parameters for flow, sediment, and nutrients are calibrated and validated against observed data only at the watershed outlet. Model parameters are adjusted systematically for the entire watershed to obtain the closest match between the model-simulated and observed data at the watershed outlet (lumped calibration). It is hypothesized that the relative loadings of pollutants and/or sediments contributed by each computational unit are not affected by this calibration procedure. In other words, areas generating relatively higher pollutant loads with an uncalibrated model will still generate relatively higher loads after calibration. This study explored the effect of lumped calibration of the Soil and Water Assessment Tool (SWAT) on locations of sediment and nutrient critical source areas (CSAs). Two watersheds in Alabama with differing size, topography, hydrology, and land use/cover characteristics were used to study the variations in locations of sediment, total phosphorus (TP), and total nitrogen (TN) CSAs identified by calibrated and uncalibrated SWAT models. Identified CSAs for sediment, TP, and TN were mostly the same with and without the calibration of the model in both watersheds. This study thus concluded that lumped calibration of the SWAT model using data at the watershed outlet has little effect on the locations of CSAs. Based on the results from these two watersheds, it was further concluded that SWAT can be used without calibration for identification of CSAs in watersheds that lack sufficient data for model calibration, but not for all other modeling purposes. More studies are encouraged to support these findings.

Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT

“…Agriculture to evaluate the impact of land management and climate change on flow and water quality processes [2]. Relevant functions of SWAT include weather components, hydrology, land use, crop growth, sediment transport routines, fate of nutrients, and conservation practices, which are capable of evaluating various hydrological, hydrochemical, and biophysical processes [3,6,28]. SWAT is a complex watershed simulation model conducted on daily time steps.…”

“…The semi-distributed watershed simulation model, Soil and Water Assessment Tool (SWAT) [1] has been applied worldwide to identify critical source areas of water quality impairments and evaluate potential solutions through land use change and water resource planning and management [2][3][4][5][6][7][8][9]. Various SWAT applications have been conducted to explore sediment loading from watersheds [10][11][12][13].…”

Identifying Nutrient Contributors in North Carolina’s Coastal Plain Blackwater Rivers

“…A watershed model, Soil and Water Assessment Tool (Winchell et al, 2009), was used to perform systematic analysis of these nutrient parameters to support the water quality evaluation and management plans for the LCFR watershed in North Carolina. SWAT model is a wellestablished watershed scale hydrologic model which has been used in numerous water quality assessment studies worldwide (Borah, et al, 2006;Busteed et al, 2009;Jha et al, 2007;Kirsh et al, 2002;Ouyang et al, 2008;Niraula et al, 2012;Veith et al, 2005).…”

Simulating the impact of flooding events on non-point source pollution and the effects of filter strips in an intensive agricultural watershed in China

“…The ability of SWAT to simulate other daily NPSPs (including nitrate N and organic N) could not be verified because of the lack of observations. Fortunately, as a type of physical process-based model, the ability of SWAT to estimate or predict nutrients under data deficiencies has been partly recognized in previous studies (Niraula et al 2012;Glavan et al 2011;Chu et al 2004). Meanwhile, it was believed that the application of this model under data limitations could still facilitate the evaluation of management strategies if appropriately parameterized (Panagopoulos et al 2011).…”