Institute: Connecticut
Year Established: 2010 Start Date: 2010-03-01 End Date: 2011-02-28
Total Federal Funds: $24,080 Total Non-Federal Funds: $48,397
Principal Investigators: Daniel Civco, James Hurd
Project Summary: Protecting lake water quality is a major concern for local, regional, and state agencies, as well as citizens and non-profit organizations. Comprehensive water quality data are essential for improved management and policy decisions. It is, however, prohibitively expensive to monitor water quality in a significant number of lakes and ponds using conventional in situ methods. As such, many lakes and ponds remain unmonitored resulting in the inability of agencies to identify potential problems and act on them. Satellite remote sensing has been used successfully in the United States and elsewhere to assess lake water clarity. Research in the Northern Plains, for example, has found there is a strong correlation between Secchi Disk Transparency (SDT) measurements and the Landsat-collected spectral response of lake surface water, particularly in the blue and red spectral bands. In the Northern Plains region, regression analysis has been used to develop models based on SDT measurements for a select number of lakes and applied to Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) imagery to develop a comprehensive assessment of lake water clarity, an indicator of water quality, for all water bodies in the image scene(s). Satellite remote sensing, thereby, provides a means by which to get at the big picture of statewide lake and pond water quality. We propose to adopt similar procedures as used in the Northern Plains region to derive lake water clarity assessments for Connecticut. We will make use of existing SDT measurements collected for select lakes and ponds over the past four decades, and found in the literature or through other sources, to generate a multi-temporal dataset using Landsat MSS, TM, and ETM imagery collected near-contemporaneously with the SDT information. The Landsat multispectral data will be atmospherically-corrected and radiometrically-calibrated to facilitate the creation of a consistent multi-temporal image database and subsequent statistical analysis. The results will provide a historical record of water clarity in Connecticut’s lakes and ponds. In addition, given the availability of satellite imagery and SDT field samples for the mid-July through mid-September 2010 time period, we will conduct similar analysis to derive a current map of Connecticut water clarity that can be compared to the historic data to identify trends and assess current conditions. Together, the results of this research will provide a methodology for continued assessment of lake water clarity into the future. Ultimately the results will provide us with the means to allocate resources to the areas most at need and help to examine more efficiently factors that are contributing to decreased water clarity and associated water quality.