HR: 1340h
AN: H53A-0962    [Abstracts]
TI: A Simulation Framework for Evaluating Sampling Strategies and Determining Load Accuracies in Suspended Sediment Loads
AU: * Bajcsy, P
EM: pbajcsy@ncsa.uiuc.edu
AF: NCSA/UIUC, 1205 W. Clark, Urbana, IL 61801, United States
AU: Li, Q
EM: qili3@uiuc.edu
AF: NCSA/UIUC, 1205 W. Clark, Urbana, IL 61801, United States
AU: Crowder, D
EM: crowderd@sws.uiuc.edu
AF: Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820, United States
AU: Markus, M
EM: mmarkus@sws.uiuc.edu
AF: Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820, United States
AB: Excessive river sedimentation can cause extensive economic and ecological damage. Expensive dredging operations are needed to keep navigation channels clear and to maintain the capacity of water supply reservoirs. Deposition of fine sediments in rivers can eliminate pool habitats, decrease embryo survival rates of certain fish, and affect macroinvertebrate density and diversity. Sedimentation is often associated with anthropogenic watershed activities (e.g. urbanization and agricultural practices). Effort has been spent on developing Best Management Practices (BMPs) to reduce the sediment loads caused by specific watershed activities. Sediment monitoring networks have also been implemented to measure loads within streams and help determine the efficacy of BMPs over time. Yet, fundamental questions remain regarding how accurately loads can be estimated. Research suggests watershed hydrologic and geomorphic characteristics, sampling method and frequency, along with the method used to develop sediment-discharge rating curves can substantially affect the accuracy and precision at which sediment load estimates are made. The confidence at which one can estimate sediment loads, based on a specific sampling protocol, is one of several important pieces of information that hydrologic observatories need to understand in order to help monitor load trends. A computer program is being developed that allows one to estimate sediment loads using several sediment- discharge rating curves and bias correction factors. Using USGS mean daily sediment data for the Illinois River at Valley City, the program is employed to perform Monte Carlo simulations to predict confidence limits for loads estimated using different sampling protocols (e.g. weekly, monthly and hydrologic event based sampling). Results of the different sampling approaches are compared. A discussion regarding how these results, combined with future simulations representative of different sediment monitoring locations, can help guide future monitoring efforts is provided.
DE: 1816 Estimation and forecasting
DE: 1847 Modeling
DE: 1861 Sedimentation (4863)
SC: Hydrology [H]
MN: 2007 Fall Meeting