Surface Water Detection

Surface water detection involves identifying and monitoring bodies of water, such as lakes, rivers, and reservoirs, using various methods like remote sensing, satellite imagery, and GIS technologies.

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Remote stock water monitoring and worsening drought-induced water scarcity in U.S. Southwest

The exacerbation of climate change-induced droughts, among other weather extremes, is escalating into a critical global challenge particularly in arid regions like the Southwestern U.S. where droughts pose grievous environmental and socio-economic threats. Increasingly frequent, intense, and enduring droughts are commonplace generally in Western U.S. inflicting damages on crops and aggravating record-breaking wildfires year after year. Drought is the second-most expensive natural disaster in the U.S. behind hurricanes, costing an average of $9.6 billion in damages per event. Therefore, continuous innovation and deployment of cost-effective and time-efficient water resources monitoring tools could help mitigate severe environmental and socio-economic impacts of droughts which currently impact livestock and wildlife management in Southwest U.S. A recent innovation as a potential climate change adaptation solution is the Surface Water Identification and Forecasting Tool (SWIFT). The Google Earth Engine-based tool is a remote sensing-based technology that leverages optical imagery derived from Landsat 8 OLI and Sentinel-2 Multispectral Instrument (MSI), and radar imagery from Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) to monitor near real-time the availability of water in stock ponds and tanks. As drought conditions are expected to worsen with rising global temperatures, SWIFT is designed to provide a valuable and affordable stock water monitoring solution for cattle producers and land managers, etc.