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Over the past few decades, global warming and climate change have impacted the hydrologic cycle. Many models have been developed to simulate hydrologic processes. Obtaining accurate climatic data on local/meso, and global scales is essential for the realistic simulation of hydrologic processes. However, the limited availability of climatic data often poses a challenge to hydrologic modeling efforts. Hydrologic science is currently undergoing a revolution in which the field is being transformed by the multitude of newly available data streams. Historically, hydrologic models that have been developed to answer basic questions about the rainfall–runoff relationship, surface water, and groundwater storage/fluxes, land–atmosphere interactions, have been optimized for previously data-limited conditions. With the advent of remote sensing technologies and increased computational resources, the environment for water cycle researchers has fundamentally changed to one where there is now a flood of spatially distributed and time-dependent data. The bias in the climatic data is propagated through models and can yield estimation errors. Therefore, the bias in climatic data should be removed before their use in hydrologic models. Climatic data have been a core component of the science of hydrology. Their intrinsic role in understanding and managing water resources and developing sound water policies dictates their vital importance. This book aims to present recent advances concerning climatic data and their applications in hydrologic models.

Technology: general issues --- History of engineering & technology --- statistical weather generator --- stochastic process --- Diyala River basin --- Wilks’ technique --- hydrological models --- rainfall --- surface runoff --- linear regression models --- curve number --- SCS.CN model --- mulching --- wildfire --- prescribed fire --- n/a --- CHIRPS --- GPM-IMERG --- rainfall data scarcity --- agro-hydrology --- Rift Valley Lake Basin --- hydrological research basin --- precipitation --- temperature --- long-term trends --- climate change --- evapotranspiration --- groundwater recharge --- thresholds --- seasonality --- spatiotemporal variations --- regional-scale --- long-term --- HydroBudget model --- cold and humid climates --- Quebec (Canada) --- tank cascade system --- dry zone --- water governance --- flood control --- traditional knowledge --- community participation --- Sri Lanka --- Wilks' technique

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Over the past few decades, global warming and climate change have impacted the hydrologic cycle. Many models have been developed to simulate hydrologic processes. Obtaining accurate climatic data on local/meso, and global scales is essential for the realistic simulation of hydrologic processes. However, the limited availability of climatic data often poses a challenge to hydrologic modeling efforts. Hydrologic science is currently undergoing a revolution in which the field is being transformed by the multitude of newly available data streams. Historically, hydrologic models that have been developed to answer basic questions about the rainfall–runoff relationship, surface water, and groundwater storage/fluxes, land–atmosphere interactions, have been optimized for previously data-limited conditions. With the advent of remote sensing technologies and increased computational resources, the environment for water cycle researchers has fundamentally changed to one where there is now a flood of spatially distributed and time-dependent data. The bias in the climatic data is propagated through models and can yield estimation errors. Therefore, the bias in climatic data should be removed before their use in hydrologic models. Climatic data have been a core component of the science of hydrology. Their intrinsic role in understanding and managing water resources and developing sound water policies dictates their vital importance. This book aims to present recent advances concerning climatic data and their applications in hydrologic models.

Technology: general issues --- History of engineering & technology --- statistical weather generator --- stochastic process --- Diyala River basin --- Wilks' technique --- hydrological models --- rainfall --- surface runoff --- linear regression models --- curve number --- SCS.CN model --- mulching --- wildfire --- prescribed fire --- CHIRPS --- GPM-IMERG --- rainfall data scarcity --- agro-hydrology --- Rift Valley Lake Basin --- hydrological research basin --- precipitation --- temperature --- long-term trends --- climate change --- evapotranspiration --- groundwater recharge --- thresholds --- seasonality --- spatiotemporal variations --- regional-scale --- long-term --- HydroBudget model --- cold and humid climates --- Quebec (Canada) --- tank cascade system --- dry zone --- water governance --- flood control --- traditional knowledge --- community participation --- Sri Lanka --- statistical weather generator --- stochastic process --- Diyala River basin --- Wilks' technique --- hydrological models --- rainfall --- surface runoff --- linear regression models --- curve number --- SCS.CN model --- mulching --- wildfire --- prescribed fire --- CHIRPS --- GPM-IMERG --- rainfall data scarcity --- agro-hydrology --- Rift Valley Lake Basin --- hydrological research basin --- precipitation --- temperature --- long-term trends --- climate change --- evapotranspiration --- groundwater recharge --- thresholds --- seasonality --- spatiotemporal variations --- regional-scale --- long-term --- HydroBudget model --- cold and humid climates --- Quebec (Canada) --- tank cascade system --- dry zone --- water governance --- flood control --- traditional knowledge --- community participation --- Sri Lanka

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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

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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.

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

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Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne.

satellite radiance --- WRF-Hydro --- meteorological radar --- QPE --- microstructure of rain --- TMPA --- evaluation --- precipitation --- volume matching --- CFSR --- GMI --- terminal velocity --- TRMM-TMPA --- surface rain intensity --- retrieval algorithm --- rain gauges --- tropical cyclone --- CMORPH --- T-Matrix --- Global Precipitation Measurement (GPM) --- statistical evaluation --- vertical air velocity --- heavy rainfall prediction --- GPM IMERG v5 --- Tianshan Mountains --- Red River Basin --- precipitation retrieval --- satellite precipitation --- PERSIANN-CCS --- validation network --- PEMW --- satellite rainfall estimate --- high latitude --- Cyprus --- GPM --- wet deposition --- CloudSat --- thundercloud --- GPS --- satellite remote sensing --- assessment --- numerical weather prediction --- mineral dust --- complex terrain --- mesoscale precipitation patterns --- GNSS meteorology --- lumped models --- satellites --- Southern China --- error analysis --- topography --- cloud scavenging --- radar reflectivity–rain rate relationship --- CHAOS --- RADOLAN --- hydrometeor classification --- TRMM --- thunderstorm --- CHIRPS --- satellite precipitation retrieval --- GPM/IMERG --- GSMaP --- bias correction --- Precise Point Positioning --- Mainland China --- supercooled droplets detection --- SEID --- Saharan dust transportation --- Huaihe River basin --- GPM Microwave Imager --- satellite --- TMPA 3B42RT --- forecast model --- quality indexes --- SEVIRI --- radiometer --- triple collocation --- satellite precipitation product --- Mandra --- synoptic weather types --- drop size distribution (DSD) --- Amazon Basin --- weather radar --- X-band radar --- downscaling --- precipitation rate --- neural networks --- rain rate --- CMIP --- GPM-era IMERG --- GR models --- weather --- typhoon --- satellite rainfall retrievals --- TRMM 3B42 v7 --- validation --- low-cost receivers --- rainfall retrieval techniques --- snowfall detection --- GPM satellite --- Zenith Tropospheric Delay --- 3B42 --- hurricane Harvey --- PERSIANN_CDR --- TRMM 3B42 V7 --- snow water path retrieval --- DPR --- satellite precipitation adjustment --- Peninsular Spain --- RMAPS --- daily rainfall estimations --- streamflow simulation --- regional climate models --- Red–Thai Binh River Basin --- Ensemble Precipitation (EP) algorithm --- cloud radar --- disdrometer --- TRMM-era TMPA --- hydrometeorology --- MSG --- radar data assimilation --- dust washout process --- runoff simulations --- geostationary microwave sensors --- radar --- topographical and seasonal evaluation --- goGPS --- XPOL radar --- TMPA 3B42V7 --- telemetric rain gauge --- harmonie model --- tropical storm rainfall --- linear-scaling approach --- Milešovka observatory --- precipitable water vapor --- heavy precipitation --- hydrological simulation --- reflectivity --- Ka-band --- Tibetan Plateau --- satellite rainfall estimates --- regional rainfall regimes --- Lai Nullah --- microwave scattering --- remote sensing --- pre-processing --- rainfall rate --- MSWEP --- climatology --- VIC model --- CMORPH_CRT --- IMERG --- single frequency GNSS --- PERSIANN --- flood-inducing storm --- climate models --- Pakistan --- precipitating hydrometeor --- data assimilation --- rainfall --- kriging with external drift --- dual-polarization --- quantitative precipitation estimates --- flash flood --- Satellite Precipitation Estimates --- gridded radar precipitation --- regional rainfall sub-regimes --- polar systems --- Environmental engineering. --- Environmental monitoring. --- Biomonitoring (Ecology) --- Ecological monitoring --- Environmental quality --- Monitoring, Environmental --- Applied ecology --- Environmental engineering --- Pollution --- Environmental control --- Environmental effects --- Environmental stresses --- Engineering --- Environmental health --- Environmental protection --- Sustainable engineering --- Measurement --- Monitoring