Modeling Nutrient Loading to Utah Lake using GIS-RS Geospatial Analysis Techniques

Keywords: Nutrient Loading, Utah Lake, GIS, Remote Sensing
Session Type: Virtual Paper Abstract
Day: Saturday
Session Start / End Time: 2/26/2022 09:40 AM (Eastern Time (US & Canada)) - 2/26/2022 11:00 AM (Eastern Time (US & Canada))
Room: Virtual 73

Abstract

Utah lake, one of the largest freshwater lakes west of Mississippi River, experiences frequent harmful algal blooms due to excessive nutrient (N and P) loading to the lake. The overarching goal of this project is to model nutrient loading to Utah Lake from non-point sources using GIS and remote sensing geospatial analysis techniques within the Utah Lake Watershed. Utilizing high resolution spatial data acquired from the Utah Mapping Portal we can classify land use land cover (LULC) into Agricultural Land, Barren, Wetlands, Developed Areas, Herbaceous Land, and Shrubland. We will produce a series of LULC maps, calculate the area for each class, and subsequently combine this information with empirical models for nutrient runoff to estimate nutrient loading to Utah Lake from each LULC class. This study will present the best supervised and unsupervised classification techniques for this unique watershed analysis. The accuracy assessment will be presented for the algorithms. Our preliminary results indicate that the maximum likelihood classification method is suitable for the study area and it is feasible to accurately quantify nutrient loading from each LULC class to Utah Lake. This project will be the first comprehensive high-resolution LULC analysis in the Utah lake Watershed. The findings of the project will help many state agencies in Utah to address harmful algal bloom issues and implement meaningful watershed planning and management policies.