Development Of A Spatial Decision Support Tool For Watershed Critical Area Identification Of Soil Loss And Best Management Practices Bmps Evaluation PDF Download

Spatial decision support systems (SDSS) integrate the state of the art technology, such as GIS, database and distributed models into decision support systems to support geospatial analysis that is particularly useful for watershed management, such as TMDL development on watersheds required by the Clean Water Act. This dissertation focuses on the development of a SDSS to assess the economic and environmental impacts from various best management practices (BMPs) in reducing sediment yield on rangeland watersheds. The SDSS included three major parts: the models, database and web-based interfaces. The model part is the core of the SDSS that provides the functionality of watershed economic analysis. The model maximized the profit of a representative ranch assumed to cover the whole watershed with the constraints of production technology, resource, sediment control objectives and sustainable utilization. A watershed was spatially segmented into basic units, each unit with similar plant growth and forage utilization. There are two major types of models, static and dynamic. Each model type supported variations in plant growth, grazing and ranch operations. Upland erosion was estimated through RUSLE2 and the sediment yield of a watershed was estimated from upland erosion and sediment delivery ratios for each basic unit. GAMS programs were used to solve the optimization models. The SDSS provides a platform to automatically implement the models. The database was the major tool in managing spatial and non-spatial data. A series of customized web pages were developed to support users' inputs, watershed analysis and result visualization. The embedded procedures were integrated into the SDSS to support analytical functionality, including geospatial analysis, model parameterization and web page generation. The SDSS was used to assess sediment control on the Walnut Gulch Experimental Watershed. The SDSS was parameterized primarily using publicly available data and a preliminary validation was made. The SDSS functionality was illustrated through eight applications. The results showed that given recent prices, new infrastructure practices would cause a financial burden to ranches. Better grazing management may provide an economic alternative to meet the sediment control objective and cost sharing could provide ranchers the incentives to participate in conservation plans.