Prioritizing watersheds for conservation actions in the southeastern coastal plain ecoregion.

The aim of this study was to apply and evaluate a recently developed prioritization model which uses the synoptic approach to geographically prioritize watersheds in which Best Management Practices (BMPs) can be implemented to reduce water quality problems resulting from erosion and sedimentation. The model uses a benefit-cost framework to rank candidate watersheds within an ecoregion or river basin so that BMP implementation within the highest ranked watersheds will result in the most water quality improvement per conservation dollar invested. The model was developed to prioritize BMP implementation efforts in ecoregions containing watersheds associated with the USDA-NRCS Conservation Effects Assessment Project (CEAP). We applied the model to HUC-8 watersheds within the southeastern Coastal Plain ecoregion (USA) because not only is it an important agricultural area but also because it contains a well-studied medium-sized CEAP watershed which is thought to be representative of the ecoregion. The results showed that the three HUC-8 watersheds with the highest rankings (most water quality improvement expected per conservation dollar invested) were located in the southern Alabama, northern Florida, and eastern Virginia. Within these watersheds, measures of community attitudes toward conservation practices were highly ranked, and these indicators seemed to push the watersheds to the top of the rankings above other similar watersheds. The results, visualized as maps, can be used to screen and reduce the number of watersheds that need further assessment by managers and decision-makers within the study area. We anticipate that this model will allow agencies like USDA-NRCS to geographically prioritize BMP implementation efforts.

Model for prioritizing best management practice implementation: sediment load reduction.

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.