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This reprintshows recent advances in dam safety related to overtopping and the prevention, detection, and risk assessment of geostructural risks. Related to overtopping, the issues treated are: the throughflow and failure process of rockfill dams; the protection of embankment dams against overtopping by means of a rockfill toe or wedge-shaped blocks; and the protection of concrete dams with highly convergent chutes. In the area of geostructural threats, the detection of anomalies in dam behavior from monitoring data using a combination of machine learning techniques, the numerical modeling of seismic behavior of concrete dams, and the determination of the impact area downstream of ski-jump spillways are also studied and discussed. In relation to risk assessment, three chapters deal with the development of fragility curves for dikes and dams in relation to various failure mechanisms.
Technology: general issues --- History of engineering & technology --- hydraulic structure --- sky-jump --- spillway --- flip bucket --- chute --- basin --- erosion --- flow rate --- jet flow --- wave overtopping --- levee --- cover --- probabilistic framework --- slope stability --- piping --- overtopping --- fragility curves --- Monte Carlo simulation --- dam --- stilling basin --- bucket --- flood --- weir --- safety --- protection --- dam protection --- wedge-shaped block --- WSB --- dam spillway --- dam safety --- ACUÑA --- rockfill dams --- throughflow --- numerical modeling --- non-Darcy flow --- porous media --- Forchheimer equation --- high velocity --- crushed rock --- rounded materials --- hydraulic mean radius --- intrinsic permeability --- shape of particles --- angularity of particles --- surface roughness of particles --- river levees --- geogrid reinforcement --- First Order Reliability Method (FORM) --- Surface Response Method (SRM) --- high gravity dams --- dam-foundation-reservoir dynamic interaction --- earthquake input mechanisms --- hydrodynamic pressure --- foundation size --- reservoir length --- stacking --- blending --- combination --- meta-learner --- experts --- machine learning --- Cross Validation --- radial displacement --- rockfill dam --- dam failure --- overflow --- floods --- dam breach --- n/a --- ACUÑA
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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 --- 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
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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
Choose an application
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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