Surface Water Detection

气候变化导致的干旱及其他极端天气现象正演变为一项严峻的全球性挑战，尤其在如美国西南部等干旱区域，干旱已构成严重的环境与社会经济威胁。在美国西部，日益频繁、强烈和持久的干旱已成常态，连年摧残农作物，并加剧破纪录的森林火灾。在美国，干旱是仅次于飓风的第二大成本最高的自然灾害，单次事件造成的损失平均高达96亿美元。 因此，持续研发并推广经济高效的水资源监测工具，将有助于缓解干旱带来的严重环境与社会经济影响——这些影响当前正严重制约美国西南部的畜牧业与野生动物管理。近期一项具有气候变化适应潜力的创新成果是地表水识别与预报工具（SWIFT）。这款基于谷歌地球引擎的平台，是一种遥感技术，它综合利用 Landsat 8 OLI 和 Sentinel-2 多光谱仪的光学影像，以及 Sentinel-1 C波段合成孔径雷达的雷达影像，实现对畜牧池塘和水箱水量的近实时监测。随着全球气温上升预计将加剧干旱状况，SWIFT旨在为牧场主及土地管理者等提供一种高性价比的畜牧用水监测方案。

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.