Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 27, 2007
Publication Date: July 15, 2007
Citation: Green, C.H., Arnold, J.G., Williams, J.R., Haney, R.L., Harmel, R.D. 2007. Soil and Water Assessment Tool hydrologic and water quality evaluation of poultry litter application to small-scale subwatersheds in Texas. Transactions of the ASABE. 50(4):1199-1209. Interpretive Summary: Public concern regarding animal waste application to agricultural land has led to more research on its usage and affect on water quality. Poultry litter can contribute chemical pollutants that can degrade nearby water resources if not properly managed. This study uses the Soil and Water Assessment Tool hydrologic model to simulate runoff, sediment, and chemical loss from poultry litter in six watersheds in Texas. Statistical results showed that the SWAT model can be used to accurately predict runoff, sediment, and chemical loss. This study also demonstrates that field management and large rainfall events after poultry litter has been applied can greatly affect the water quality of nearby water resources.
Technical Abstract: The application of poultry litter to agricultural land has become a topic of interest for policy makers due to public concern about its effects on water quality. The Soil and Water Assessment Tool (SWAT) version 2005 is designed to assess nonpoint and point sources of pollution. In this study, six subwatersheds in Texas are used to evaluate the model’s ability to simulate water quality at a small scale. Each of these subwatersheds randomly received poultry litter rates of 0.0 to 13.4 Mg ha**-1. Model simulations are completed using two data scenarios. The first data scenario uses all of the available data (2000-2004) because it demonstrates the importance of the carryover effect of fertilizer treatments. The second data set uses the first year that both the fertilizer and land management practices occurred. The results of these scenarios demonstrate that higher Nash-Sutcliffe efficiency (ENS) values and less significance (alpha=0.05) occur with hydrologic, sediment and nutrient model simulations when all of the available data are used as compared to using only 2002. The autocalibration-parameter sensitivity analysis procedure embedded in SWAT was used to obtain an optimal parameter fit, based on ENS values, for the following parameters: the SCS runoff curve number for moisture condition II (CN2), the soil evaporation compensation factor (ESCO), surface runoff lag time (SURLAG), and initial soil water content expressed as a fraction of field capacity (FFCB). The six subwatersheds sensitivity analyses each resulted in CN2 and ESCO alternating as the most responsive parameter to input variability. The CN2 and ESCO parameters were found to be more sensitive than SURLAG and FFCB. The model that had manually adjusted parameters runoff parameters simulated monthly and daily for all of the watersheds for the period of 2000-2004 had monthly ENS and r**2 runoff values of at least 0.80 and 0.80 and 0.82 and 0.81, respectively. When only the 2002 data set that had manually adjusted parameters were used for model runoff simulation the monthly and daily ENS and r**2 values were at least 0.59 and 0.53 and 0.60 and 0.53, respectively. The results from the autocalibration tool combined with manual adjustment indicated that using the five years of data (2000-2004), rather than only the year 2002 with same type of simulation, also improved model runoff, sediment and nutrient results as evaluated using the ENS and p-values. The observed trends included SWAT’s overestimation of runoff in the dry periods and underestimation in the wet periods. The monthly ENS and r**2 values for sediment and nutrient losses were generally above 0.4 and 0.5, respectively. Paired t-tests for the monthly manually adjusted parameter simulation of sediment, organic N and P, NO3-N, and soluble P for the 2000-2004 period losses showed their respective SWAT means were not significantly different from the measured values (alpha=0.05), except for NO3-N losses for the Y10 watershed (p-value 0.042). The control watershed’s measured and simulated water quality results were significantly different (alpha=0.05) from the treated watersheds most likely due to the lack of crop growth which impacts nutrient uptake and impedes sediment erosion. Almost all of the subwatersheds that had poultry litter applied resulted in higher sediment, organic N, organic P, and soluble P losses than the control subwatershed upon averaging the monthly validation values. High NO3-N losses may have been a function of poultry litter and commercial fertilizers being applied before a large rain event occurred. The subwatersheds that had less amounts of commercial fertilizer and/or poultry litter lost more sediment, organic N and organic P than the subwatersheds that received the higher litter and/or fertilizer treatments. Overall, the SWAT simulated the hydrology and the water quality constituents at the subwatershed-scale more adequately when all of the data were used to simulate the model as evidenced by statistical measures.