Soil-Water Conservation, Erosion, and Landslide

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 l...

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Bibliographic Details
Other Authors: Chen, Su-Chin (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
ICU
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Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a 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. 
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653 |a landslide 
653 |a image classification 
653 |a spectrum similarity analysis 
653 |a extreme rainfall-induced landslide susceptibility model 
653 |a landslide ratio-based logistic regression 
653 |a landslide evolution 
653 |a Typhoon Morakot 
653 |a Taiwan 
653 |a vegetation community 
653 |a vegetation importance value 
653 |a root system 
653 |a soil erosion 
653 |a grey correlation analysis 
653 |a sediment yield 
653 |a RUSLE 
653 |a Lancang-Mekong River basin 
653 |a rainfall threshold 
653 |a landslide probability model 
653 |a debris flow 
653 |a Zechawa Gully 
653 |a mitigation countermeasures 
653 |a Jiuzhaigou Valley 
653 |a water erosion 
653 |a susceptibility 
653 |a Gaussian process 
653 |a climate change 
653 |a radial basis function kernel 
653 |a weighted subspace random forest 
653 |a extreme events 
653 |a extreme weather 
653 |a naive Bayes 
653 |a feature selection 
653 |a machine learning 
653 |a hydrologic model 
653 |a simulated annealing 
653 |a earth system science 
653 |a PSED Model 
653 |a loess 
653 |a ICU 
653 |a static liquefaction 
653 |a mechanical behavior 
653 |a pore structure 
653 |a alpine swamp meadow 
653 |a alpine meadow 
653 |a degradation of riparian vegetation 
653 |a root distribution 
653 |a tensile strength 
653 |a tensile crack 
653 |a soil management 
653 |a land cover changes 
653 |a Syria 
653 |a hillslopes 
653 |a gully erosion 
653 |a vegetation restoration 
653 |a soil erodibility 
653 |a land use 
653 |a bridge pier 
653 |a overfall 
653 |a scour 
653 |a landform change impact on pier 
653 |a shallow water equations 
653 |a wet-dry front 
653 |a outburst flood 
653 |a TVD-scheme 
653 |a MUSCL-Hancock method 
653 |a laboratory model test 
653 |a extreme rainfall 
653 |a rill erosion 
653 |a shallow landslides 
653 |a deep lip surface 
653 |a safety factor 
653 |a rainfall erosivity factor 
653 |a USLE R 
653 |a Deep Neural Network 
653 |a tree ring 
653 |a dendrogeomorphology 
653 |a landslide activity 
653 |a deciduous broadleaved tree 
653 |a Shirakami Mountains 
653 |a spatiotemporal cluster analysis 
653 |a landslide hotspots 
653 |a dam breach 
653 |a seepage 
653 |a overtopping 
653 |a seismic signal 
653 |a flume test 
653 |a breach model 
653 |a n/a 
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