Relating Nearshore Algal Blooms Determined Using Satellite Imagery to Nutrient Loading, Watershed Land Use, and Storm Events

Wednesday, 17 December 2014: 10:50 AM
Robert Jan Stevenson1, David W Hyndman1, Jiaguo Qi1, Peter Esselman1, Linda Novitski1, Anthony D Kendall1, Sherry L Martin2 and Shengpan Lin1, (1)Michigan State University, East Lansing, MI, United States, (2)Michigan State University, Department of Geological Sciences, East Lansing, MI, United States
The overarching goal of our project was to relate algal biomass in the coastal zone of the Great Lakes, nutrient concentrations, watershed land use, and storm events. Algal biomass was determined using MODIS and Landsat remote sensing images. Nutrient loading from rivers into coastal zones was estimated with watershed land use, soils, geology, size and precipitation records. Our models of chlorophyll a based on remote sensing images (RS inferred chl a) and nutrient loading in coastal zones were validated with measured chlorophyll concentrations in the Great Lakes and nutrients in rivers. RS-inferred chl a was related to nutrient loading from rivers, which was dependent upon recent storm events and land use in watersheds. RS-inferred chl a was more related to nutrient loads during the week preceeding measurement of chl a than other periods before or during chl measurement. This lag time is presumably related to algal growth following nutrient loading, and was non-linearly related to nutrient loading. Our results indicate that these tools will improve understanding of land use effects on algal blooms in coastal zones of the Great Lakes and will help identify priority watersheds for restoration.