HR: 1340h
AN: H43E-0407    [Abstracts]
TI: A Statistical Model Predicting Time Series of Pesticide Load in the Sacramento River Based on Precipitation and Pesticide Use in the Sacramento River Watershed
AU: * Guo, L
EM: lguo@cdpr.ca.gov
AF: California Department of Pesticide Regulation, 1001 I St., Sacramento, CA 95812-4015 United States
AU: Spurlock, F C
EM: fcspurlock@cdpr.ca.gov
AF: California Department of Pesticide Regulation, 1001 I St., Sacramento, CA 95812-4015 United States
AU: Johnson, B R
EM: bjohnson@cdpr.ca.gov
AF: California Department of Pesticide Regulation, 1001 I St., Sacramento, CA 95812-4015 United States
AU: Goh, K S
EM: kgoh@cdpr.ca.gov
AF: California Department of Pesticide Regulation, 1001 I St., Sacramento, CA 95812-4015 United States
AB: Transport of pesticides by surface runoff during rainfall events is a major process contributing to pesticide contamination in rivers. This study presents an empirical regression model that relates pesticide loading over time in the Sacramento River with the precipitation and pesticide use in the Sacramento River watershed. The model closely simulated loading dynamics of diazinon, simazine, and diuron during 1991-1994 and 1997-2000 winter storm seasons. The coefficients of determination for regression ranged from 0.168 to 0.907, and were all significant at $<$0.001. The results of this study provide strong evidence that precipitation and pesticide use are the two major environmental variables dictating the dynamics of pesticide transport into surface water in a watershed. The capability of the statistical model to provide time-series estimates on pesticide loading in rivers is unique and may be useful for Total Maximum Daily Load (TMDL) assessment.
DE: 1800 HYDROLOGY
DE: 1854 Precipitation (3354)
DE: 1860 Runoff and streamflow
DE: 1871 Surface water quality
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting