Preface to the Special Issue “Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning”

Segoni, Samuele; Gariano, Stefano Luigi; Rosi, Ascanio

doi:10.3390/w13030323

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…Recently, empirical rainfall thresholds have been used to establish the early alert system of landslide occurrences on a global and regional scale [14]. The used to identify critical rainfall values that initiate landslides [17] [18]. Hence, the I-D and E-D thresholds are chosen in the current study.…”

Section: Introductionmentioning

confidence: 99%

Grid Satellite Rainfall Products Potential Application for Developing I-D and E-D Thresholds for Landslide Early Alert System over Bali Island

Aryastana

2023

U Karst

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Bali has been one of the most popular tourist destinations in Indonesia. However, on the other hand, Bali has a high risk of natural disaster vulnerability. The number of landslides in Bali took the first position compared to other natural disasters. Currently, remote sensing platforms can present Grid Satellite Rainfall Products (GSRPs), which provide rainfall information that can identify rainfall conditions for landslide events. This study aims to analyze the potential GSRPs application of Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), and Global Satellite Mapping of Precipitation (GSMaP) in determining the mean rainfall intensities and duration (I-D); accumulated rainfall and duration (E-D) thresholds for landslide occurrences over Bali Island. The method used to develop I-D and E-D thresholds is the power-law equation and frequentist sampling method in various probability levels (5%, 10%, 20%, 30%, 40%, and 50%). The result shows that I-D and E-D thresholds established by GSRPs are generally lower than the threshold defined by rain gauge observations. Among the three GSRPs, IMERG is performing the best in establishing the I-D and E-D thresholds for landslide phenomena. The level of potential that IMERG can use in developing the I-D and E-D thresholds is 59.16% and 84.06%, respectively. The E-D threshold derived from the IMERG product can be used to establish the landslide early alert system over Bali Island because it has a high spatial-temporal resolution, word-wide coverage, and near-real-time observation.

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Section: Introductionmentioning

confidence: 99%

Grid Satellite Rainfall Products Potential Application for Developing I-D and E-D Thresholds for Landslide Early Alert System over Bali Island

Aryastana

2023

U Karst

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“…With the acceleration of human engineering activities and the intensification of global climate change, the number of landslide disasters is increasing yearly. Landslides are frequent and widespread destructive processes, causing casualties and damage worldwide [3]. China is one of the countries most seriously affected by landslide disasters due to its vast territory, large north-south span, high terrain in the west, low terrain in the east, tropical, subtropical and temperate heat zones and widespread mountains and hills [4].…”

Section: Introductionmentioning

confidence: 99%

Advance Landslide Prediction and Warning Model Based on Stacking Fusion Algorithm

Lin

Sun

2023

Mathematics

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In landslide disaster warning, a variety of monitoring and warning methods are commonly adopted. However, most monitoring and warning methods cannot provide information in advance, and serious losses are often caused when landslides occur. To advance the warning time before a landslide, an innovative advance landslide prediction and warning model based on a stacking fusion algorithm using Baishuihe landslide data is proposed in this paper. The Baishuihe landslide area is characterized by unique soil and is in the Three Gorges region of China, with a subtropical monsoon climate. Based on Baishuihe historical data and real-time monitoring of the landslide state, four warning level thresholds and trigger conditions for each warning level are established. The model effectively integrates the results of multiple prediction and warning submodels to provide predictions and advance warnings through the fusion of two stacking learning layers. The possibility that a risk priority strategy can be used as a substitute for the stacking model is also discussed. Finally, an experimental simulation verifies that the proposed improved model can not only provide advance landslide warning but also effectively reduce the frequency of false warnings and mitigate the issues of traditional single models. The stacking model can effectively support disaster prevention and reduction and provide a scientific basis for land use management.

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Two-dimensional deformation monitoring for spatiotemporal evolution and failure mode of Lashagou landslide group, Northwest China

et al. 2022

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Preface to the Special Issue “Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning”

Abstract: Landslides are frequent and widespread destructive processes causing casualties and damage worldwide [...]

Cited by 4 publications

References 42 publications

Grid Satellite Rainfall Products Potential Application for Developing I-D and E-D Thresholds for Landslide Early Alert System over Bali Island

Grid Satellite Rainfall Products Potential Application for Developing I-D and E-D Thresholds for Landslide Early Alert System over Bali Island

Advance Landslide Prediction and Warning Model Based on Stacking Fusion Algorithm

Two-dimensional deformation monitoring for spatiotemporal evolution and failure mode of Lashagou landslide group, Northwest China

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