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Model for Prioritizing Best Management Practice Implementation: Sediment Load Reduction
Authors:Taeil Jang  George Vellidis  Jeffrey B Hyman  Erin Brooks  Lyubov A Kurkalova  Jan Boll  Jaepil Cho
Institution:1. Department of Rural Construction Engineering, Chonbuk National University, Jeonju-si, Jeonbuk, 561-756, Republic of Korea
2. Crop & Soil Sciences Department, University of Georgia, 2360 Rainwater Road, Tifton, GA, 31793-5766, USA
3. Conservation Law Center, Bloomington, IN, 47408, USA
4. Biological and Agricultural Engineering Department, University of Idaho, Moscow, ID, 83844, USA
5. Department of Economics and Energy and Environmental Systems Program, North Carolina A&T State University, Greensboro, NC, 27411, USA
6. Biological and Agricultural Engineering Department, University of Idaho, Moscow, ID, 83844, USA
7. Climate Change Research Team, Climate Research Department, APEC Climate Center, Haeundae-gu, Busan, 612-020, Republic of Korea
Abstract:Understanding the best way to allocate limited resources is a constant challenge for water quality improvement efforts. The synoptic approach is a tool for geographic prioritization of these efforts. It uses a benefit-cost framework to calculate indices for functional criteria in subunits (watersheds, counties) of a region and then rank the subunits. The synoptic approach was specifically designed to incorporate best professional judgment in cases where information and resources are limited. To date, the synoptic approach has been applied primarily to local or regional wetland restoration prioritization projects. The goal of this work was to develop a synoptic model for prioritizing watersheds within which suites of agricultural best management practices (BMPs) can be implemented to reduce sediment load at the watershed outlets. The model ranks candidate watersheds within an ecoregion or river basin so that BMP implementation within the highest ranked watersheds will result in the most sediment load reduction per conservation dollar invested. The model can be applied anywhere and at many scales provided that the selected suite of BMPs is appropriate for the evaluation area’s biophysical and climatic conditions. The model was specifically developed as a tool for prioritizing BMP implementation efforts in ecoregions containing watersheds associated with the USDA-NRCS conservation effects assessment project (CEAP). This paper presents the testing of the model in the little river experimental watershed (LREW) which is located near Tifton, Georgia, USA and is the CEAP watershed representing the southeastern coastal plain. The application of the model to the LREW demonstrated that the model represents the physical drivers of erosion and sediment loading well. The application also showed that the model is quite responsive to social and economic drivers and is, therefore, best applied at a scale large enough to ensure differences in social and economic drivers across the candidate watersheds. The prioritization model will be used for planning purposes. Its results are visualized as maps which enable resource managers to identify watersheds within which BMP implementation would result in the most water quality improvement per conservation dollar invested.
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