Land Use and Water Quality Trends in Rock Creek Watershed (Seneca Co., Ohio), 1982-2005: Impact of Core-4 Conservation Practices

Project Summary

The USDA Conservation Effects Assessment Project has provided a research grant to Heidelberg College Water Quality Laboratory to demonstrate the water quality benefits of agricultural management practices at the watershed level, and to evaluate the influence on water quality of the choice of practices, the timing of their implementation, and their location in the watershed. The project will be conducted between September 2004 and September 2007.

The two broad objectives of the research are (1) to conduct statistical trend analyses of water quality in Rock Creek and of agricultural practices in the Rock Creek watershed (90 km2), and evaluate the strength of the connection between the two; and (2) to develop an AnnAGNPS model of Rock Creek watershed, calibrate and validate it using the water quality data, and use it to investigate a number of hypotheses about the impact on water quality of the choice, location, and timing of practices applied in the watershed. Additionally, survey research will explore those social and economic factors that act to either encourage or inhibit adoption of conservation practices.

The project is supported by a very extensive water quality dataset that includes flow, sediment, and nutrient data for more than 11,000 samples collected once to three times per day since 1982 at a Heidelberg College sampling station near the mouth of Rock Creek. Linear regression will be used for trend analysis, with variance reduction by log transformation, adjustment of concentrations for correlation with flow, and the use of seasonal variables; this approach has been used successfully by members of the project team in a previous study of Rock Creek over a shorter span of time (1982-1995).

Other members of the project team* have extensive experience with AnnAGNPS, including a recently completed project on a larger, nearby watershed in northwest Ohio. We believe that the analysis of a highly detailed dataset in a watershed of appropriate size and with significant water quality trends, combined with the use of a sophisticated land use/water quality model to investigate alternative scenarios, provides a unique opportunity to build a strong, scientifically defensible case for the success of BMPs in improving water quality at the watershed scale, and to improve our understanding of the ways in which the choice and location of BMPs affect water quality outcomes.

*Project Director: R. Peter Richards, Heidelberg College; Co-Project Director: Timothy T. Loftus, Heidelberg College; Co-Project Director: Kevin P. Czajkowski, University of Toledo; Additional Collaborators: The Ohio State University Extension, and USDA Natural Resources Conservation Service, Ohio State Office