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Remote Sensing in Hydrology and Water Resources Management
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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.

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Keywords

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

Links

DOI: 10.3390/books978-3-0365-2700-0

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