Sensitivity Analysis of SWAT Nutrient Modeling under different Management Practices

Abstract

Water quality due to agricultural management practices is an issue, where non-point source pollution such as nutrient losses from cropland is a major concern in the U.S. Soil and Water Assessment Tool (SWAT) model is one of the most cost effective tools used to simulate numerous best management practices (BMPs) to reduce agricultural pollutants especially nutrients in crop lands. The objectives of this study were to assemble all necessary field data from the Integrated Agricultural management Systems (IAMS) Franklin site in Kansas to calibrate SWAT using sensitivity analysis approach, and validate the model performance to evaluate the effectiveness of BMPs for nutrient reduction. In this study, SWAT model was calibrated using measured data over the field plots in sorghum-soybean cropping sequence for a period of 2001-2004. Combination of tillage and nutrient application methods tested were: till (chisel) with fertilizer broadcast then incorporated, no-till with fertilizer broadcast without incorporation, and no-till with fertilizer incorporated (knifed). The model predicted total-N and total-P were compared with the measured values at each plot for daily and monthly time step using median based Nash-Sutcliffe efficiency (Ef) and coefficient of determination (R2). Calibrated daily total-N model predicted well for no-till surface broadcast with higher Ef>0.60 and R2>0.65. In all the plots, calibrated monthly total-N losses were over predicted during high precipitation months of May, June, and July. Model performed well in simulating the validation plots with best daily statistics for no-till surface broadcast. Calibration results showed reduced total-P losses for no-till with fertilizer incorporated. The model performed well in simulating the validation plots and no-till with fertilizer incorporated gave the highest daily Ef of 0.58. Sensitivity analysis of the model showed that the nutrients transported from cropland in southeastern Kansas were most sensitive to the parameters like, nitrogen percolation coefficient, residue decomposition coefficient, biological mixing coefficient for total-N and biological mixing coefficient, phosphorous uptake distribution parameter, phosphorous percolation coefficient for total-P. Overall, the results showed that SWAT was able to predict the effects of BMPs on nutrient losses and model is a useful tool for simulating BMPs in other fields and watersheds where no measured nutrients data are available.