Water Resources Research Act Program

Details for Project ID 2009IN219B

Remote Sensing of Water Quality Indicators in the Wabash River

Institute: Indiana
Year Established: 2009 Start Date: 2009-03-01 End Date: 2010-02-28
Total Federal Funds: $15,000 Total Non-Federal Funds: $45,348

Principal Investigators: Keith Cherkauer, Indrajeet Chaubey

Project Summary: Water quality is a major issue for rivers in the agriculturally dominated Midwestern United States. Most monitoring of water quality relies on the installation of expensive real-time monitoring stations, or the selection of permanent sampling sites where samples are collected by hand. The former results in good temporal resolution but is limited by cost to relatively few locations, the latter method allows the spatial coverage of the samples to increase at the expense of collecting samples less frequently, on a monthly basis for example. Remote sensing imagery has been used to monitor water quality on lakes, reservoirs and costal zones, providing high spatial resolution with relatively regular sampling frequencies interrupted only by clouds, however, their applicability in river ecosystems is not well tested. This project will apply existing techniques for extracting water quality information from remote sensing images, to images of the Wabash River to test the ability of satellite-based sensors to monitor water quality in this and other Midwestern river systems. In-situ water samples and spectral measurements will be collected coincident with satellite overpasses to develop a database of spectral signatures related to current flow and water quality conditions within the river channel. This information will be used to calibrate and evaluate the extraction of water quality parameters, such as chlorophyll-a (chl-a), total suspended solids (TSS) and dissolved organic matter (DOM), from remote sensing images. We expect this project to result in a better understanding of which image processing algorithms are effective and what sensor characteristics are required to produce highquality maps of the spatial distribution of regional water quality. This will eventually lead to the development of near real-time maps for the evaluation and monitoring of water quality in the region.