Location: Water Quality and Ecology Research
Project Number: 6060-13660-008-08-I
Project Type: Interagency Reimbursable Agreement
Start Date: Jun 1, 2016
End Date: May 31, 2021
The overall objectives of this multi-agency research effort are to develop, demonstrate, and advance the science to improve the EPA’s Ecological Risk Assessment (ERA) process conducted in compliance with the Endangered Species Act (ESA). The part of the research to be conducted through this interagency agreement addresses these more detailed objectives: 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 the 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; 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.
1) 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. 2) Collect and prepare input data for the models, 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. Check the relevance and quality of these data. 3) Evaluate the hydrodynamic and water quality performance of the selected model(s) by conducting simulations on study watersheds and comparing simulated results with field observations. 4) Develop a framework/common procedure 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. 5) Perform uncertainty analyses, 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.