Pesticides have been recognized as one major agricultural non-point source (NPS) pollution to the environment and surface water in United States. Numerous mathematical models have been developed over the last decades to simulate the fate and transport of NPS at watershed scale. Geographic Information System (GIS) combined with models extends the spatial and temporal scopes of the research by integrating a variety of climates, soils, land covers, and management practices. The Annualized Agricultural Nonpoint Source model (AnnAGNPS) has received considerable attention in the United States for estimating runoff, sediment yield, pesticide and nutrients transport from ungauged agricultural watershed. However, few studies have been conducted on pesticide loading prediction in surface water using AnnAGNPS. In this study, the AnnAGNPS model was calibrated and validated for prediction of stream flow and chlorpyrifos loading for an agricultural dominated watershed of Orestimba Creek, in Central Valley, California. Large amounts of chlorpyrifos are applied to almonds, walnuts and other stone-fruit orchards in this area every year, which caused significant concern regarding their contamination to the San Joaquin River. Variety of data obtained from multiple sources were utilized as model input, including climate, land use, topology, soil, crop management and schedule, non-crop data, and pesticide. The model's performance was quantitatively analyzed using mean, standard deviation, coefficient of determination (r2), coefficient of efficiency (NSE), and root mean square error (RMSE). Model's prediction was considered to be unsatisfactory if NSE < 0.36, satisfactory if 0.36 < NSE < 0.75 and good if NSE > 0.75. Monthly stream flow discharge prediction was satisfactory and fit the observed data during model calibration mode. The prediction had major improvement in validation mode with modified curve number and rainfall interception values (r2 = 0.78 and NSE = 0.77). The AnnAGNPS predictions of chlorpyrifos concentrations in runoff water were unsatisfactory in both calibration and validation modes. Predicted chlorpyrifos concentrations at rainfall events were 1/1000 of observed data and it was impossible to improve the results through any type of calibration. The overall results suggested the model's poor performance was most likely a result of coarse sampling resolution of observed chlorpyrifos concentrations and lack of irrigation data.

Little historical water quality data is available for the Upper Pearl River Basin (UPRB), yet there are UPRB waters listed as impaired. Objectives of this research were to measure pesticide and sediment concentrations in UPRB surface waters and validate the Annualized Agricultural Nonpoint-Source (AnnAGNPS) runoff model with the measured data for a portion of the UPRB. An additional objective was to quantify effects of land use changes on UPRB surface waters from 1987 to 2002 using AnnAGNPS. Of the fifteen compounds analyzed, hexazinone was most frequently detected, in 94% of samples, followed by metolachlor, tebuthiuron, and atrazine. Metribuzin was detected in only 6% of samples. Total dissolved solids (TDS) concentrations were highest at Carthage, which drains the largest area of three sites sampled for TDS. Most samples measured below Environmental Protection Agency (EPA) standards for pesticides and TDS in drinking water and also below levels toxic to aquatic organisms. For eight of twelve months analyzed between October 2001 and January 2003, average monthly sediment loadings for measured and AnnAGNPS-simulated data differed no more than 109%, resulting in an R&178; value of 0.328. A comparison of measured and simulated atrazine and metolachlor loadings by event resulted in R&178; values of 0.095 and 0.062, respectively. Most daily atrazine and metolachlor loadings for measured and predicted data were very low. On May 18, 2003, AnnAGNPS predicted a metolachlor loading of 80 mg, while measured data showed a loading of 5.6 mg. Measured data showed an earlier spike on January 20, 2003 that was not mirrored by the model. Atrazine comparisons followed the same trend, except measured loadings did not spike until February 22, 2003. The 2002 AnnAGNPS simulation resulted in 15% more average annual runoff than the 1987 simulation, although both simulations had the same precipitation. The 2002 simulation also had higher values for sediment and organic carbon loading. Nitrogen loading was the only runoff or pollutant loading category that was less for 2002 than for 1987. Urban land cover contributed more runoff and pollutant loadings from 1987 to 2002, while traditional row crop agriculture had less of an impact on pollutant loadings.

Evaluation of an On-Farm Water Storage (OFWS) system as a Best Management Practice (BMP) for nutrient and sediment loading control and irrigation in East Mississippi has shown that the system can effectively reduce sediment and nutrient loading as it was able to capture 46 tons of sediment and 558 kg of phosphorus over the monitoring period. The system was also able to decrease nitrogen loading as shown from the nitrogen concentration in the captured storm runoff events although an accurate estimate could not be made using AnnAGNPS because adequate model input data was not available. The system was able to provide about 63 million gallons of water for irrigation as a result of which increased corn and soybean yield was also obtained in irrigated fields when compared to non-irrigated fields. Water from the storage pond used for irrigation did not have adequate nutrient recycling to reduce commercial fertilizer application.

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