Water Resources Research Act Program

Details for Project ID 2008SD131B

Development of a Decision Support System for Water Resources Management of Shallow Glacial Alluvial Aquifers: A Laboratory Proof of Concept Study

Institute: South Dakota
Year Established: 2008 Start Date: 2008-03-01 End Date: 2011-02-28
Total Federal Funds: $54,785 Total Non-Federal Funds: $116,689

Principal Investigators: Suzette Burckhard, Patrick Emmons

Project Summary: Starting in 2000, various regions across the United States, especially in the Western United States, saw a decrease in precipitation causing drought conditions. As these conditions have persisted, concerns have been raised regarding public and private water supplies. Many cities across the Western United States are developing plans for sustainable water supply alternatives to address concerns including climate changes and economic factors. Local water resources managers need tools they can employ in predicting water supply quantities and quality as a function of time especially when considering how to optimize the use of these resources in a sustainable manner. Previously, a GIS based model Decision Support System, the Paulson model, was developed that predicted stream flow using remotely sensed data as part of a flood risk DSS. Improvements to the GIS based watershed scale model have been made that allow the model to predict event based groundwater recharge in stream channels. The quality of these improvements needs to be verified. A first step toward verification of the model is to acquire laboratory data by constructing a laboratory scale surface runoff/subsurface infiltration apparatus to verify groundwater recharge parameters that have been formulated as part of an existing GIS based runoff model. The goal of this proposed laboratory study is to construct the laboratory apparatus and acquire data for various flow and stream bed conditions to verify the existing GIS model. Sensitivity analyses will be performed on the GIS based model to assess the optimal quantity and quality of data necessary to achieve meaningful water resources management results.