Publisher's Synopsis
Over the past two decades, remote sensing techniques have progressively revealed their competence to monitor components of the water balance of large river basins on time scales ranging from months to decades: satellite altimetry routinely monitors water level changes in large rivers, lakes and floodplains. The use of remote sensing for the assessment of our aquatic resources provides several advantages compared to conventional approaches for water quality assessments. Remote sensing provides water quality data with a high spatial and temporal resolution for thousands of lakes at a time. It supports the evaluation of environmental problems and potential health risks through the analysis of changes in water quality and the detection of harmful algal blooms. Several remote sensing programs provide historical data for studies of trends in water quality and the potential impacts of land use and land cover change on water quality. Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives. Remote Sensing and Water Resources brings together research and reviews showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. The pressure on water resources has been on the rise and will continue to increase in the coming years because of increased frequency of drought, urbanization, urban population growth, and deforestation, increased use of fertilizers and pesticides, and spread of invasive species. Therefore, accurate, inexpensive, and fast monitoring tools using remote sensing technology are needed for timely implementation of conservation and restoration measures in problematic areas. This volume is intended to highlight some of the remote sensing-driven applied research currently being performed to solve the aforementioned problems in water resources. It also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers.
