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To promote scientific understanding of surface processes in East Asia, we have published details of the CMADS dataset in the journal, Water, and expect that users around the world will learn about CMADS datasets while promoting the development of hydrometeorological disciplines in East Asia. We hope and firmly believe that scientific development in East Asia and our understanding of this typical region will be further advanced.

sensitivity analysis --- non-point source pollution models --- reservoirs --- operation rule --- East Asia --- climate variability --- Qinghai-Tibet Plateau (TP) --- potential evapotranspiration --- precipitation --- capacity distribution --- GLUE --- soil temperature --- land use change --- JBR --- CFSR --- Jinsha River Basin --- impact --- runoff --- CMADS --- hydrological modeling --- aggregated reservoir --- reanalysis products --- Lijiang River --- spatio-temporal --- uncertainty --- total nitrogen --- Han River --- streamflow simulation --- meteorological --- CMADS-ST --- Erhai Lake Basin --- uncertainty analysis --- Biliuhe reservoir --- hydrological --- bayesian model averaging --- blue and green water flows --- SUFI-2 --- TMPA-3B42V7 --- statistical analysis --- satellite-derived rainfall --- streamflow --- satellite-based products --- Xiang River basin --- SWAT hydrological simulation --- PERSIANN-CDR --- hydrological processes --- SUFI2 --- CMADS dataset --- ParaSol --- hydrological modelling --- accumulation --- meteorological input uncertainty --- soil moisture content --- Yellow River --- SWAT --- Noah LSM-HMS --- sediment yield --- Yalong River --- TRMM --- Penman-Monteith --- IMERG --- PERSIANN --- hydrological elements --- freeze–thaw period --- land-use change --- parameter sensitivity --- China --- reservoir parameters --- soil moisture --- sloping black soil farmland --- hydrological model --- SWAT model --- hydrologic model

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The main aim of this book is to present various implementations of ML methods and metaheuristic algorithms to improve modelling and prediction hydrological and water resources phenomena having vital importance in water resource management.

groundwater --- artificial intelligence --- hydrologic model --- groundwater level prediction --- machine learning --- principal component analysis --- spatiotemporal variation --- uncertainty analysis --- hydroinformatics --- support vector machine --- big data --- artificial neural network --- nitrogen compound --- nitrogen prediction --- prediction models --- neural network --- non-linear modeling --- PACF --- WANN --- SVM-LF --- SVM-RF --- Govindpur --- streamflow forecasting --- Bayesian model averaging --- multivariate adaptive regression spline --- M5 model tree --- Kernel extreme learning machines --- South Korea --- uncertainty --- sustainability --- prediction intervals --- ungauged basin --- streamflow simulation --- satellite precipitation --- atmospheric reanalysis --- ensemble modeling --- additive regression --- bagging --- dagging --- random subspace --- rotation forest --- flood routing --- Muskingum method --- extension principle --- calibration --- fuzzy sets and systems --- particle swarm optimization --- EEFlux --- irrigation performance --- CWP --- water conservation --- NDVI --- water resources --- Daymet V3 --- Google Earth Engine --- improved extreme learning machine (IELM) --- sensitivity analysis --- shortwave radiation flux density --- sustainable development --- n/a

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Anthropogenic and natural disturbances to freshwater quantity and quality are a greater issue for society than ever before. To successfully restore water resources requires understanding the interactions between hydrology, climate, land use, water quality, ecology, and social and economic pressures. This Special Issue of Water includes cutting edge research broadly addressing investigative areas related to experimental study designs and modeling, freshwater pollutants of concern, and human dimensions of water use and management. Results demonstrate the immense, globally transferable value of the experimental watershed approach, the relevance and critical importance of current integrated studies of pollutants of concern, and the imperative to include human sociological and economic processes in water resources investigations. In spite of the latest progress, as demonstrated in this Special Issue, managers remain insufficiently informed to make the best water resource decisions amidst combined influences of land use change, rapid ongoing human population growth, and changing environmental conditions. There is, thus, a persistent need for further advancements in integrated and interdisciplinary research to improve the scientific understanding, management, and future sustainability of water resources.

Research & information: general --- physical habitat --- aquatic ecology --- stream health --- environmental flows --- land use --- hydrology --- hydroecology --- ecohydrology --- climate change --- Appalachia --- reforestation --- land use-land cover --- land-atmosphere coupling --- water quality --- environmental perceptions --- human dimensions --- spatial models --- socioeconomics --- urban watershed management --- municipal watershed --- water quality impairment --- collaborative adaptive management --- water resources --- urban watersheds --- endocrine disrupting chemical --- opioid --- pathway analysis --- ontology --- metabolomics --- decision-making --- logit regression --- farmer perceptions --- social networks --- public funds --- water conservation adoption --- good governance --- sanitation --- sustainability --- water supply --- water-saving agriculture --- Chinese provincial input efficiency --- three-stage DEA model --- environmental variables --- Boufakrane river watershed --- remote sensing --- LULCC --- water balances --- vulnerability --- total dissolved solids --- drinking water --- Appalachian Mountains --- streamflow sensitivity --- water security --- water balance partitioning --- Budyko --- Escherichia coli --- Suspended particulate matter --- Water quality --- Land use practices --- Watershed management --- basin --- hydrologic model --- reaeration rates --- stream metabolism --- watershed --- physicochemistry --- land use practices --- experimental watershed --- suspended particulate matter --- stream water temperature --- watershed management --- bacteria --- land-use practices --- environmental persistence --- saturated hydraulic conductivity --- pedotransfer function --- model validation --- Chesapeake Bay Watershed --- experimental watershed study --- human dimensions of water --- watershed modeling --- hydrological modeling --- water pollutants

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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.

Technology: general issues --- Environmental science, engineering & technology --- 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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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