Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning

Landslides are destructive processes causing casualties and damage worldwide. The majority of the landslides are triggered by intense and/or prolonged rainfall. Therefore, the prediction of the occurrence of rainfall-induced landslides is an important scientific and social issue. To mitigate the ris...

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יצא לאור: MDPI - Multidisciplinary Digital Publishing Institute 2022
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גישה מקוונת:ONIX_20220111_9783036509303_203
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collection Directory of Open Access Books
description Landslides are destructive processes causing casualties and damage worldwide. The majority of the landslides are triggered by intense and/or prolonged rainfall. Therefore, the prediction of the occurrence of rainfall-induced landslides is an important scientific and social issue. To mitigate the risk posed by rainfall-induced landslides, landslide early warning systems (LEWS) can be built and applied at different scales as effective non-structural mitigation measures. Usually, the core of a LEWS is constituted of a mathematical model that predicts landslide occurrence in the monitored areas. In recent decades, rainfall thresholds have become a widespread and well established technique for the prediction of rainfall-induced landslides, and for the setting up of prototype or operational LEWS. A rainfall threshold expresses, with a mathematic law, the rainfall amount that, when reached or exceeded, is likely to trigger one or more landslides. Rainfall thresholds can be defined with relatively few parameters and are very straightforward to operate, because their application within LEWS is usually based only on the comparison of monitored and/or forecasted rainfall. This Special Issue collects contributions on the recent research advances or well-documented applications of rainfall thresholds, as well as other innovative methods for landslide prediction and early warning. Contributions regarding the description of a LEWS or single components of LEWS (e.g., monitoring approaches, forecasting models, communication strategies, and emergency management) are also welcome.
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spelling doab-20.500.12854ir-764672024-03-28T03:32:22Z Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning Segoni, Samuele Gariano, Stefano Luigi Rosi, Ascanio loess landslide DAN-W numerical simulation dynamic analysis rainfall thresholds Bhutan shallow landslides landslides Idukki early warning system landslide hazard antecedent rainfall threshold landslide susceptibility satellite-derived rainfall TRMM Multisatellite Precipitation Analysis 3B42 (TMPA) tropical Africa rainfall thresholds physicallybased model hydrological monitoring soil water index large-scale landslide SWI–D threshold shallow landslide temporal probability landslide and debris flow China quantile regression Wayanad early warning GIS rainfall intensity optimization rainfall thresholds calculation mean annual rainfall lithology Slovenia n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Landslides are destructive processes causing casualties and damage worldwide. The majority of the landslides are triggered by intense and/or prolonged rainfall. Therefore, the prediction of the occurrence of rainfall-induced landslides is an important scientific and social issue. To mitigate the risk posed by rainfall-induced landslides, landslide early warning systems (LEWS) can be built and applied at different scales as effective non-structural mitigation measures. Usually, the core of a LEWS is constituted of a mathematical model that predicts landslide occurrence in the monitored areas. In recent decades, rainfall thresholds have become a widespread and well established technique for the prediction of rainfall-induced landslides, and for the setting up of prototype or operational LEWS. A rainfall threshold expresses, with a mathematic law, the rainfall amount that, when reached or exceeded, is likely to trigger one or more landslides. Rainfall thresholds can be defined with relatively few parameters and are very straightforward to operate, because their application within LEWS is usually based only on the comparison of monitored and/or forecasted rainfall. This Special Issue collects contributions on the recent research advances or well-documented applications of rainfall thresholds, as well as other innovative methods for landslide prediction and early warning. Contributions regarding the description of a LEWS or single components of LEWS (e.g., monitoring approaches, forecasting models, communication strategies, and emergency management) are also welcome. 2022-01-11T13:32:44Z 2022-01-11T13:32:44Z 2021 book ONIX_20220111_9783036509303_203 9783036509303 9783036509310 https://directory.doabooks.org/handle/20.500.12854/76467 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/3903 https://mdpi.com/books/pdfview/book/3903 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0931-0 10.3390/books978-3-0365-0931-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036509303 9783036509310 222 Basel, Switzerland open access
spellingShingle loess landslide
DAN-W
numerical simulation
dynamic analysis
rainfall thresholds
Bhutan
shallow landslides
landslides
Idukki
early warning system
landslide hazard
antecedent rainfall threshold
landslide susceptibility
satellite-derived rainfall
TRMM Multisatellite Precipitation Analysis 3B42 (TMPA)
tropical Africa
rainfall
thresholds
physicallybased model
hydrological monitoring
soil water index
large-scale landslide
SWI–D threshold
shallow landslide
temporal probability
landslide and debris flow
China
quantile regression
Wayanad
early warning
GIS
rainfall intensity
optimization
rainfall thresholds calculation
mean annual rainfall
lithology
Slovenia
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title_full Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title_fullStr Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title_full_unstemmed Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title_short Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning
title_sort rainfall thresholds and other approaches for landslide prediction and early warning
topic loess landslide
DAN-W
numerical simulation
dynamic analysis
rainfall thresholds
Bhutan
shallow landslides
landslides
Idukki
early warning system
landslide hazard
antecedent rainfall threshold
landslide susceptibility
satellite-derived rainfall
TRMM Multisatellite Precipitation Analysis 3B42 (TMPA)
tropical Africa
rainfall
thresholds
physicallybased model
hydrological monitoring
soil water index
large-scale landslide
SWI–D threshold
shallow landslide
temporal probability
landslide and debris flow
China
quantile regression
Wayanad
early warning
GIS
rainfall intensity
optimization
rainfall thresholds calculation
mean annual rainfall
lithology
Slovenia
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
topic_facet loess landslide
DAN-W
numerical simulation
dynamic analysis
rainfall thresholds
Bhutan
shallow landslides
landslides
Idukki
early warning system
landslide hazard
antecedent rainfall threshold
landslide susceptibility
satellite-derived rainfall
TRMM Multisatellite Precipitation Analysis 3B42 (TMPA)
tropical Africa
rainfall
thresholds
physicallybased model
hydrological monitoring
soil water index
large-scale landslide
SWI–D threshold
shallow landslide
temporal probability
landslide and debris flow
China
quantile regression
Wayanad
early warning
GIS
rainfall intensity
optimization
rainfall thresholds calculation
mean annual rainfall
lithology
Slovenia
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
url ONIX_20220111_9783036509303_203