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Prokopy, Linda Stalker, Z. Asligül Göçmen, Jing Gao, Shorna Broussard Allred, Joseph E. Bonnell, Kenneth Genskow, Alicia Molloy, and Rebecca Power, 2011. Incorporating Social Context Variables Into Paired Watershed Designs to Test Nonpoint Source Program Effectiveness. Journal of the American Water Resources Association (JAWRA) 47(1):196‐202. DOI: 10.1111/j.1752‐1688.2010.00508.x Abstract: In a traditional paired watershed study, watersheds are selected to be as similar as possible so that conclusions may be drawn about the performance of Best Management Practices. We have extended the paired watershed concept to examine the effectiveness of watershed management programs by adding comparative criteria for social characteristics. For four different 8 or 11/12 digit hydrologic unit code (HUC) watersheds in the Midwest, we have piloted a systematic method for selecting paired subwatersheds. First, we developed a list of 11 key variables. Next, a factor analysis was conducted to determine the underlying structure of the 11 input variables. Finally, in each of the four watersheds, potential paired subwatersheds (all 14 digit HUCs) were selected using the factors in a cluster analysis. Informal interviews were then held with key informants in each watershed to provide qualitative assessments of criteria that could impact the comparability of the subwatersheds. This method for selecting paired watersheds should be helpful for other researchers to test the effectiveness of watershed management programs focused on behavior change.  相似文献   
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ABSTRACT: SWMHMS is a conceptual computer modeling program developed to simulate monthly runoff from a small nonurban watershed. The input needed to run model simulations include daily precipitation, monthly data for evapotranspiration determination (average temperature, crop consumptive coefficients, and percent daylight hours), and six watershed parameter values. Evapotranspiration was calculated with the Blaney-Criddle equation while surface runoff was determined using the Soil Conservation Service curve number procedure. For watershed parameter evaluation, SWMHMS provides options for both optimization and sensitivity analysis. Observed runoff data are required along with the model input previously mentioned in order to conduct parameter optimization. SWMEIMS was tested with data from six watersheds located in different regions of the United States. Model accuracy was generally found to be very good except on watersheds having substantial snowfall accumulation. In having only six watershed parameters, SWMHMS is less complex to use than many other computer programs that calculate monthly runoff. Consequently, SWMHMS may find its greatest application as an educational tool for students learning principles of hydrologic modeling, such as parameter evaluation procedures and the impacts of input data uncertainty on model results.  相似文献   
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