Modeling drainage practice impacts on the quantity and quality of stream flows for an agricultural watershed in Ohio

Nonpoint source pollution from agricultural systems is considered to be a leading source of water pollution with sediments, nutrients, and pesticides being the major pollutants. In this study, a water quality modeling methodology which utilizes remotely sensed data, a field scale process model, and a GIS to assess flow, sediment, and agrichemical discharges on small agricultural watersheds was used for simulating impacts of drainage practices on Rock Creek Watershed in northern Ohio. A GIS data base was developed for the watershed to derive input data for the model. Model inputs such as land use and tillage practices were derived from Landsat TM data. A set of crop rotation systems was developed for deriving crop-related model inputs. The ADAPT model was used for predicting water quality with and without considering subsurface processes on the watershed. The predictions were evaluated against measured stream flow and its constituents such as sediment, nitrate-N, and four pesticides data for three years. Pollutant loadings from surface runoff and drainage, with and without drainage systems were compared at a watershed level. Impacts of drainage practices on pollutant discharges in the watershed and the role of water table management models and their shortcomings are discussed.