Spatiotemporal Monitoring Of Toc Concentrations In Lake Mead With A Near Real-Time Multi-Sensor Network

Forest fires, soil erosion, and land use changes in watersheds nearby Lake Mead and inflows from Las Vegas Wash into the lake are considered as sources of the lake\u27s water quality impairment. These conditions result in higher concentration of Total Organic Carbon (TOC). TOC in contact with Chlorine which is often used for disinfection purposes of drinking water supply causes the formation of trihalomethanes (THMs). THM is one of the toxic carcinogens controlled by the EPA\u27s disinfection by-product rule. As a result of the threat posed to the drinking water used by the 25 million people downstream, recreational area, and wildlife habitat of Lake Mead, it is necessary to develop a method for near real-time monitoring of TOC in this area. Monitoring through a limited number of ground-based monitoring stations on a weekly/monthly basis is insufficient to capture both spatial and temporal variations of water quality changes. In this study, the multi-sensor remote sensing technology linking those ground-based TOC analyzers and two satellites with the aid of data fusion and mining techniques provides us with near real time information about the spatiotemporal distribution of TOC for the entire lake on a daily basis. A data fusion method was applied to bridge the gap of poor 250/500m spatial resolution for the land bands of Moderate Resolution Imaging Spectroradiometer (MODIS) imageries with the 30 m enhanced spatial resolution of Landsat\u27s imageries which suffers from long overpass of 16 days. Consequently, nearreal time Integrated Multi-sensor Fusion and Mining (IDFM) techniques produce synthetic fused images of MODIS and Landsat satellites with both high spatial and temporal resolution in order to create near-real time TOC distribution maps updated by ground-based TOC analyzers and lead to sustainable water quality management with the aid of IDFM in Lake Mead watershed