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The predicted climate change is likely to cause extreme storm events and, subsequently, catastrophic disasters, including soil erosion, debris and landslide formation, loss of life, etc. In the decade from 1976, natural disasters affected less than a billion lives. These numbers have surged in the last decade alone. It is said that natural disasters have affected over 3 billion lives, killed on average 750,000 people, and cost more than 600 billion US dollars. Of these numbers, a greater proportion are due to sediment-related disasters, and these numbers are an indication of the amount of work still to be done in the field of soil erosion, conservation, and landslides. Scientists, engineers, and planners are all under immense pressure to develop and improve existing scientific tools to model erosion and landslides and, in the process, better conserve the soil. Therefore, the purpose of this Special Issue is to improve our knowledge on the processes and mechanics of soil erosion and landslides. In turn, these will be crucial in developing the right tools and models for soil and water conservation, disaster mitigation, and early warning systems.

landslide --- image classification --- spectrum similarity analysis --- extreme rainfall-induced landslide susceptibility model --- landslide ratio-based logistic regression --- landslide evolution --- Typhoon Morakot --- Taiwan --- vegetation community --- vegetation importance value --- root system --- soil erosion --- grey correlation analysis --- sediment yield --- RUSLE --- Lancang–Mekong River basin --- rainfall threshold --- landslide probability model --- debris flow --- Zechawa Gully --- mitigation countermeasures --- Jiuzhaigou Valley --- water erosion --- susceptibility --- Gaussian process --- climate change --- radial basis function kernel --- weighted subspace random forest --- extreme events --- extreme weather --- naive Bayes --- feature selection --- machine learning --- hydrologic model --- simulated annealing --- earth system science --- PSED Model --- loess --- ICU --- static liquefaction --- mechanical behavior --- pore structure --- alpine swamp meadow --- alpine meadow --- degradation of riparian vegetation --- root distribution --- tensile strength --- tensile crack --- soil management --- land cover changes --- Syria --- hillslopes --- gully erosion --- vegetation restoration --- soil erodibility --- land use --- bridge pier --- overfall --- scour --- landform change impact on pier --- shallow water equations --- wet-dry front --- outburst flood --- TVD-scheme --- MUSCL-Hancock method --- laboratory model test --- extreme rainfall --- rill erosion --- shallow landslides --- deep lip surface --- safety factor --- rainfall erosivity factor --- USLE R --- Deep Neural Network --- tree ring --- dendrogeomorphology --- landslide activity --- deciduous broadleaved tree --- Shirakami Mountains --- spatiotemporal cluster analysis --- landslide hotspots --- dam breach --- seepage --- overtopping --- seismic signal --- flume test --- breach model --- n/a --- Lancang-Mekong River basin

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Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

Research & information: general --- precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data --- precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- n/a --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data