Computers and Electronics in Agriculture.pdf

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Computers and Electronics in Agriculture

Computers and Electronics in Agriculture 27 (2000) 315–333 Knowledge-based assessment of watershed condition Keith M. Reynolds a,*, Mark Jensen b, James Andreasen c, Iris Goodman d a USDA Forest Ser6ice, Pacific Northwest Research Station, 3200 SW Jefferson Way, Cor6allis, OR 97331, USA b USDA Forest Ser6ice, Northern Region, Missoula, MT, USA c US En6ironmental Protection Agency, National Center for En6ironmental Assessment, Washington, DC, USA d US En6ironmental Protection Agency Landscape Ecology Branch, Las Vegas, NV, USA Abstract The USDA Forest Service and Environmental Protection Agency have cooperatively developed a knowledge base for assessment and monitoring of ecological states and processes in sixth-code watersheds. The knowledge base provides a formal logical specification for evaluating watershed processes, patterns, general effects of human influence, and specific effects on salmon habitat. The knowledge base was designed in the NetWeaver knowledge base development system and evaluated in the Ecosystem Management Decision Support (EMDS) system. EMDS is an application framework for knowledge-based decision support of ecological landscape analysis at any geographic scale. The system integrates geographic information system and knowledge base system technologies to provide an analytical tool for environmental assessment and monitoring. The basic objective of EMDS is to improve the quality and completeness of environmental assessments and the efficiency with which they are performed. This paper presents an overview of the NetWeaver and EMDS systems, describes the general structure of the knowledge base for watershed assessment, and presents a small example of its use for evaluating erosion processes. Published by Elsevier Science B.V. Keywords: Watershed analysis; Watershed assessment; Ecosystem management; Decision support; NetWeaver /locate/compag  Paper presented at the IUFRO Conference: Application of Scientific Knowledge to Decisionmaking in Managi

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