The purpose of watershed assessments is to give information about conditions of water quality, stream morphology, and biological integrity to identify the sources of stressors and their impacts. In recent decades, different watershed assessment methods have been developed to evaluate the cumulative impacts of human activities on watershed health and the condition of aquatic systems. In the current research, we propose a new approach for assessing watershed vulnerability to contamination based on spatial analysis by using geographic information systems (GIS) and the analytic hierarchy process (AHP) technique. This new procedure, designed to identify vulnerable zones, depends on six basic factors that represent watershed characteristics: land use/land cover, soil type, average annual precipitation, slope, depth to groundwater, and bedrock type. The general assumptions for assessing watershed vulnerability are based on the response of watersheds to different contamination impacts and how the six selected factors interact to affect watershed health. The new watershed vulnerability assessment technique was used to create maps showing the relative vulnerabilities of specific sub-watersheds in the Eagle Creek Watershed in central Indiana. The results showed a remarkable difference in watershed susceptibility between the sub-watersheds in their vulnerability to pollution. To test the reliability of the proposed vulnerability assessment technique, the SWAT (Soil and Water Assessment Tool) model was applied to predict the water quality in each sub-watershed. Using the SWAT model, some parameters (e.g., total suspended solids [TSS] and nitrate) were tested based on the availability of the data needed for comparison. Both the SWAT and the newly proposed method produced good results in predicting water quality loads, which validated the proposed method. Hence, the results of the evaluation of the predictive reliability of the watershed vulnerability assessment method revealed that the proposed approach is suitable as a decision-making tool to predict watershed health.
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