Reprint

Natural Disasters Occurrence, Reduction, and Restoration in Mountain Regions

Edited by
April 2024
510 pages
  • ISBN978-3-7258-0858-8 (Hardback)
  • ISBN978-3-7258-0857-1 (PDF)

This book is a reprint of the Special Issue Natural Disasters Occurrence, Reduction, and Restoration in Mountain Regions that was published in

Biology & Life Sciences
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Public Health & Healthcare
Summary

Mountain regions are critical because of their diverse geological conditions, dynamic changes, and the multiple natural hazards that often occur. Mountains are high-risk environments that can experience a variety of natural hazards, since initiated hazards often trigger secondary, cascading hazards, having a significant impact not only on the area of occurrence but often also on up- and downstream regions. High economic losses and human casualties are caused by geophysical (rockfalls, earthquakes, and volcanic activities), hydrological (floods, avalanches, and dammed-lake outbursts), and sediment-related hazards (landslides, driftwood, debris/mud flows, and surface erosion). Under the impacts of global warming and climate change, the spatiotemporal patterns of rainfall and other weather events have become more unevenly distributed, often with a more extreme magnitude and/or intensity of events. The complexity of mountainous regions, in addition to the continued changes in climate and land use, have made it more challenging to predict mountainous hazards and their impacts on communities. Based on the countless efforts made worldwide on natural hazards in mountain regions, tight international collaboration is strongly required to answer questions related to the causes of disasters, the monitoring of hazardous phenomena, predicting disasters, and the effective reduction of hazardous consequences.

Format
  • Hardback
License
© 2024 by the authors; CC BY-NC-ND license
Keywords
debris flow occurrence; rainfall index; rainfall return period; probability; extreme drought; Mekong; SPI; Mann–Kendall; time series clustering; integrated multi-satellite retrievals (IMERG); harmony; preference; cognitive factors; physical elements; questionnaire survey; landslide potential; random forest; antecedent landslides; machine learning; landslide evolution; landslide activity; vegetation recovery time; spatiotemporal hotspot; landslide susceptibility analysis; event-based landslide inventory; ensemble model; Shihmen watershed; water quality; deep learning; recursive neural network; actions; reorganization; artificial disaster; young farmer; resilience community; land use; quantitative landslide assessment; Rize; satellite images; tea garden; debris flow; sediment transport mode; transition process; changing streambed gradient; sediment transport concentration; flow depth; gravel migration velocity; flume experiment; landslide hazard; land use evaluation; multiple logistic regression; rainfall variability; sediment disaster prevention; SABO; adaptation measure; climate change; Japan; discharge measurement; mean surface velocity; non-contact measurement; acoustic doppler flowmeter; magnetic-inductive current meter; genetic algorithm (GA); landslide-prone area; landslide scarp assessment; ellipse-referenced idealized curved surface (ER-ICS); flow paths; scenario investigation; sediment-related disaster; non-structural measurement; socio-economic conditions; human loss; community-based analysis; natural hazards; landslide; susceptibility; GIS; Vietnam; landslides; 3D engineering geological model; grid- and vector-based; surface and subsurface displacement monitoring; failure mechanisms; geotechnical engineering design; earthquake-induced landslides; landslide mobility; pumice; flume experiment; perennial groundwater zone; organic soil layers; clay mineral soil layers; headwater catchment; serpentine; unsaturated upward flux; deep learning; rainfall-induced landslide; sediment disaster; Keras; multilayer perceptron; hyperparameter tuning; mountain disaster risk reduction; landslide; large-scale landslide; triggering rainfall; early warning system; linear regression; nonlinear regression; uncertainty; visual language translation; mountain stream facilities; perception; qualitative analysis; scenic beauty estimation (SBE); caption evaluation method (CEM); landslide mitigation; monitoring; micro-hydro plant; costs reduction; gray-box model; physical modeling; rainfall; wedge slope; the intersection angle; half-wedge angle; landslide evolution; landslide recovery rate; local outlier analysis; Mann–Kendall trend test; spatiotemporal analysis; sub-watershed scale; Taiwan; mountain stream facilities; Nature-based Solutions (NbS); ecosystem services; climate change; disaster reduction; industry-government-academia collaboration; n/a