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This study empirically estimates the multiple benefits of a subsidy policy that would offer payments to farmers in return for the adoption of conservation tillage, and compares the outcomes of alternative targeting designs for such a policy. The least-cost incentive payment policy schemes are simulated for the State of Iowa by using the data for roughly 12,000 National Resource Inventory (NRI) points. We use an economic conservation tillage adoption model to evaluate the costs of adoption and a physical process simulation model (EPIC) to estimate the environmental benefits due to adoption at each of the NRI points.Two targeting options are considered. We assess the costs and environmental consequences of a practice-based policy instrument (which maximizes the acres of land in conservation tillage, regardless of its level of environmental benefits) and contrast it to a performance-based instrument (which yields the highest amount of environmental benefits per dollar spent). Carbon sequestration in agricultural soils, reduction of soil erosion by wind and water, and the reduction in nitrogen runoff are considered as possible targets for the performance-based instruments. We find that the practice-based instrument provides high proportions of the four benefits relative to the policies that target the benefits directly, especially at the higher policy budget levels. Similarly, we estimate that targeting one of the four benefits individually provides high percentages of the other benefits as compared with the amounts of the benefits obtainable if they were targeted directly.  相似文献   
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This article reviews the key, cross‐cutting findings concerning watershed‐scale cost‐effective placement of best management practices (BMPs) emerging from the National Institute of Food and Agriculture Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost‐effectiveness problem: (1) how to assess the location‐ and farmer‐specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within‐watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify cost‐effective BMP placements; (6) tradeoffs between total conservation costs and watershed‐scale cost‐effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost‐effectiveness problem; and (8) systemic and modeling uncertainties alter cost‐effective BMP placements considerably.  相似文献   
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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.  相似文献   
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