Location: Water Quality and Ecology Research
Project Number: 6060-13660-008-02-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 12, 2016
End Date: Mar 31, 2021
The objectives of this cooperative research are to (1) Review and evaluate existing hydrodynamic and water quality models that are able to predict pesticide concentration, frequency, and duration in streams, rivers, and other water bodies, (2) Develop input data, and evaluate the performance of the selected models (AnnAGNPS and RICEWQ) for the study area, (3) Provide data to all interested interagency partners, specifically the amount of applied pesticides and location information for the study area, so it can be incorporated in additional analyses, (4) Develop frameworks/common procedures that will link the modeled results to the ecological risk assessment of pesticides on endangered and threatened species, using probabilistic and weight of evidence techniques, and (5) Assess uncertainty and quantitatively propagate it through the ecological risk assessment of pesticides so that it is clearly reflected in the eventual risk estimates.
Agency and the Cooperator will conduct holistic literature reviews of models suitable for hydrodynamic and pesticide simulation that can be coupled with species-based ecological risk analyses. Compare the pros and cons of existing models and their applicability for different regions of the study area. Data will be collected and prepared for model inputs, including geospatial data on topography, soil, land use and land cover, hydrography, meteorology, geology, and habitat as well as pesticides usage data from the California Pesticide Use Database. The relevance and quality of these data will be verified. An evaluation of the hydrodynamic and water quality performance of the selected model(s) will be performed by conducting simulations on study watersheds and comparing simulated results with field observations. A framework/common procedure will be developed that associates the modeling results with the results for the ecological risk assessment of pesticides on endangered and threatened species, by reviewing the current, most successful approaches, evaluating new trends, as well as proposing a unified approach that could lead to future improvements. Uncertainty analyses will be performed, which are key to evaluating the ecological risk assessment, using the best available science (e.g. Bayesian models and Monte Carlo techniques) for chemical risk assessment.