T9 Management and Restoration of Fluvial Systems with Broad Historical Changes and Human Impacts I

Sunday, 28 October 2007
8:00 AM - 12:00 PM

EVALUATING SEDIMENT SOURCES, STORAGE, AND POLICY IMPLICATIONS IN THE AGRICULTURAL LE SUEUR RIVER WATERSHED, CENTRAL MINNESOTA

Paper number: T9-2
Program: Technical Sessions
Time: 8:05 AM – 8:20 AM

Authors

Abstract

We are creating a sediment budget for the Le Sueur River, a tributary to the Minnesota River that delivers 31% of the sediment load with only 7% of land area in the Middle Minnesota watershed. The Le Sueur carries a flow weighted mean concentration of 349 mg/l of suspended solids, far exceeding the standard of 58 mg/l which serves as a surrogate for turbidity (Data from the Water Resources Center, MN State University, Mankato). This watershed has a long history of cooperative monitoring by state agencies (MPCA, DNR, and MDA), federal agencies (USGS) and the Water Resources Center at MN State University. Our work builds on that of these groups and is being funded by the MPCA through state Clean Water Legacy funding.

The Le Sueur River flows into the incised Minnesota River valley, with knickpoints migrating up into low-gradient agricultural uplands. Primary sediment sources include uplands, ravines, high bluffs downstream of knickpoints, and streambanks. Our sediment budget is based on two parallel approaches: 1) a cosmogenic and fallout radionuclide budget to apportion sediment by sources, and 2) a physical sediment budget utilizing repeat surveys of bluffs and ravines, long-term history of meander migration, areas and ages of flood plains, channel geometry, and sediment gaging data. These data will inform models of sediment movement in and out of storage along the channel bed and floodplain.

Understanding sediment sources helps decision-makers identify potential management actions; however, actual policy implementation requires consideration of socioeconomic issues. Parallel projects by NCED social scientists include surveys to determine public preference and willingness to pay for management practices. They are also developing a decision-making analysis model that incorporates uncertainties in the science and in predicted outcomes of “best management practices” to iteratively determine the best and most economic approaches for managing sediment loads.