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Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling
Authors:ES Brooks  SM Saia  J Boll  L Wetzel  ZM Easton  TS Steenhuis
Institution:1. Department of Biological and Agricultural Engineering, University of Idaho, Moscow, Idaho;2. Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York;3. Environmental Science and Water Resources Program, University of Idaho, Moscow, Idaho;4. Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia
Abstract:There is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.
Keywords:best management practices  surface water hydrology  transport and fate  nonpoint source pollution  soil erosion control  Water Erosion Prediction Project  decision‐support tool
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