This report summarizes well sampling protocols, data collection procedures, and analytical results for the presence of pesticides in ground water developed by the California Department of Pesticide Regulation (DPR). Specific well sampling protocols were developed to meet regulatory mandates of the Pesticide Contamination Prevention Act (PCPA) of 1986 and to provide further understanding of the agronomic, chemical, and geographic factors that contribute to movement of residues to ground water. The well sampling data have formed the basis for the DPR's regulatory decisions. For example, a sampling protocol, the Four-Section Survey, was developed to determine if reported detections were caused by nonpoint-source agricultural applications, a determination that can initiate formal review and subsequent regulation of a pesticide. Selection of sampling sites, which are primarily rural domestic wells, was initially based on pesticide use and cropping patterns. Recently, soil and depth-to-ground water data have been added to identify areas where a higher frequency of detection is expected. In accordance with the PCPA, the DPR maintains a database for all pesticide well sampling in California with submission required by all state agencies and with invitations for submission extended to all local and federal agencies or other entities. To date, residues for 16 active ingredients and breakdown products have been detected in California ground water as a result of legal agricultural use. Regulations have been adopted for all detected parent active ingredients, and they have been developed regardless of the level of detection.

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, all were 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 fortotal maximum daily load (TMDL) assessments.

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