Rainfall-Induced Landslides Hazard

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Water Resources and Risk Management".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 19215

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Special Issue Editor

Department of Civil Engineering, University of Granada, 18071 Granada, Spain
Interests: hazards and sustainability; landslide dynamics, mechanisms, and processes; remote sensing and GIS techniques; landslide and erosion hazard assessment and mapping; numerical and empirical methods; early warning; remedial and preventive measures
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Special Issue Information

Dear Colleagues,

Landslides can cause human injury, loss of life and economic devastation, and destroy construction works and cultural and natural heritage. The level of risk as a consequence of landslides depends on the hazard associated; that is, on the recurrence or temporal probability with which one or more landslides processes-related affect a terrain unit. That is why the knowledge of the frequency with which these processes occur, or with which important activity changes arise, together with the different types of landslides and their sizes or intensity classes provide valuable information to predict the transient behavior linked to the destructiveness of these natural events. Landslides are frequently triggered by hydro-meteorological phenomena, mainly as a consequence of intensive rainfall which have led to losses of millions of dollars and thousands of fatalities. In recent decades, there has been significant improvement in landslide observation, hazard assessment modeling using numerical and analytical methods. These developments offer new displays for modeling landslide hazard, leading to new insights into their functioning and new approaches to process modeling to obtain better prediction.

This Special Issue is devoted to the collection of the latest developments and applications of these numerical and analytical methods to improve our understanding of rainfall-induced landslide models. We invite scholars working in this field to consider submitting their latest results including, but not limiting to:

  • Landslide dynamics, mechanisms and processes
  • Landslide activity
  • Remote sensing and GIS techniques
  • Rainfall-triggered landslides
  • Partial duration series
  • Numerical models
  • Empirical methods
  • Landslide-hazard mapping
  • Model validation
  • Early warning
  • Remedial or preventive measures

Prof. Dr. Clemente Irigaray
Guest Editor

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Keywords

  • Landslide dynamics, mechanisms and processes
  • Landslide activity
  • Remote sensing and GIS techniques
  • Rainfall-triggered landslides
  • Partial duration series
  • Numerical models
  • Empirical methods
  • Landslide-hazard mapping
  • Model validation
  • Early warning
  • Remedial or preventive measures

Published Papers (6 papers)

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26 pages, 3013 KiB  
Article
Rainfall-Induced Landslides and Erosion Processes in the Road Network of the Jaén Province (Southern Spain)
by Ramón Carpena, Joaquín Tovar-Pescador, Mario Sánchez-Gómez, Julio Calero, Israel Mellado, Francisco Moya and Tomás Fernández
Hydrology 2021, 8(3), 100; https://doi.org/10.3390/hydrology8030100 - 05 Jul 2021
Cited by 3 | Viewed by 2496
Abstract
Rainfall thresholds are one of the most widely applied methods for indirectly estimating landslide return periods, which are subsequently used in hazard analyses. In this study, the starting point is an incidence database of landslides and erosive processes affecting the road network of [...] Read more.
Rainfall thresholds are one of the most widely applied methods for indirectly estimating landslide return periods, which are subsequently used in hazard analyses. In this study, the starting point is an incidence database of landslides and erosive processes affecting the road network of the province of Jaén (southern Spain), in which the positions and dates of civil repair works can be found. Meanwhile, the use of a daily rainfall database in a dense grid (1 km) allowed for the estimation of the rainfall series at each incidence point with high precision. Considering the news in the local media and applying spatial proximity, temporal proximity, and maximum return period criteria, rainfall events of various duration (1 to 90 days) could be associated approximately with each point. Then, the rainfall thresholds and their return periods were estimated. A linear equation was adjusted for the rainfall duration threshold (E = 6.408 D + 74.829), and a power-law curve was adjusted for the intensity–duration pair (I = 47.961 D−0.458). Non-significant differences were observed between the thresholds and the return periods for the lower and higher magnitude incidences, but the durations for the former were lower (1–13 days), compared to those of the latter (7–22 days). From the equations, rainfall events of different durations could be estimated for use in hazard analysis, as well as for the future development of warning systems. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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14 pages, 5585 KiB  
Article
Statistical Analysis of Landslide Susceptibility, Macerata Province (Central Italy)
by Matteo Gentilucci, Marco Materazzi and Gilberto Pambianchi
Hydrology 2021, 8(1), 5; https://doi.org/10.3390/hydrology8010005 - 07 Jan 2021
Cited by 5 | Viewed by 2147
Abstract
Every year, institutions spend a large amount of resources to solve emergencies generated by hydrogeological instability. The identification of areas potentially subject to hydrogeological risks could allow for more effective prevention. Therefore, the main aim of this research was to assess the susceptibility [...] Read more.
Every year, institutions spend a large amount of resources to solve emergencies generated by hydrogeological instability. The identification of areas potentially subject to hydrogeological risks could allow for more effective prevention. Therefore, the main aim of this research was to assess the susceptibility of territories where no instability phenomena have ever been detected. In order to obtain this type of result, statistical assessments of the problem cannot be ignored. In this case, it was chosen to analyse the susceptibility to landslide using a flexible method that is attracting great interest in the international scientific community, namely the Weight of Evidence (WoE). This model-building procedure, for calculating landslide susceptibility, used Geographic Information Systems (GIS) software by means of mathematical operations between rasters and took into account parameters such as geology, acclivity, land use, average annual precipitation and extreme precipitation events. Thus, this innovative research links landslide susceptibility with triggering factors such as extreme precipitation. The resulting map showed a low weight of precipitation in identifying the areas most susceptible to landslides, although all the parameters included contributed to a more accurate estimate, which is necessary to preserve human life, buildings, heritage and any productive activity. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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24 pages, 4134 KiB  
Article
Characteristics of Rainfall Events Triggering Landslides in Two Climatologically Different Areas: Southern Ecuador and Southern Spain
by José Antonio Palenzuela Baena, John Soto Luzuriaga and Clemente Irigaray Fernández
Hydrology 2020, 7(3), 45; https://doi.org/10.3390/hydrology7030045 - 21 Jul 2020
Cited by 5 | Viewed by 2821
Abstract
In the research field on landslide hazard assessment for natural risk prediction and mitigation, it is necessary to know the characteristics of the triggering factors, such as rainfall and earthquakes, as well as possible. This work aims to generate and compare the basic [...] Read more.
In the research field on landslide hazard assessment for natural risk prediction and mitigation, it is necessary to know the characteristics of the triggering factors, such as rainfall and earthquakes, as well as possible. This work aims to generate and compare the basic information on rainfall events triggering landslides in two areas with different climate and geological settings: the Loja Basin in southern Ecuador and the southern part of the province of Granada in Spain. In addition, this paper gives preliminary insights on the correlation between these rainfall events and major climate cycles affecting each of these study areas. To achieve these objectives, the information on previous studies on these areas was compiled and supplemented to obtain and compare Critical Rainfall Threshold (CRT). Additionally, a seven-month series of accumulated rainfall and mean climate indices were calculated from daily rainfall and monthly climate, respectively. This enabled the correlation between both rainfall and climate cycles. For both study areas, the CRT functions were fitted including the confidence and prediction bounds, and their statistical significance was also assessed. However, to overcome the major difficulties to characterize each landslide event, the rainfall events associated with every landslide are deduced from the spikes showing uncommon return periods cumulative rainfall. Thus, the method used, which has been developed by the authors in previous research, avoids the need to preselect specific rainfall durations for each type of landslide. The information extracted from the findings of this work show that for the wetter area of Ecuador, CRT presents a lower scale factor indicating that lower values of accumulated rainfall are needed to trigger a landslide in this area. This is most likely attributed to the high soil saturation. The separate analysis of the landslide types in the case of southern Granada show very low statistical significance for translational slides, as a low number of data could be identified. However, better fit was obtained for rock falls, complex slides, and the global fit considering all landslide types with R2 values close to one. In the case of the Loja Basin, the ENSO (El Niño Southern Oscillation) cycle shows a moderate positive correlation with accumulated rainfall in the wettest period, while for the case of the south of the province of Granada, a positive correlation was found between the NAO (North Atlantic Oscillation) and the WeMO (Western Mediterranean Oscillation) climate time series and the accumulated rainfall. This correlation is highlighted when the aggregation (NAO + WeMO) of both climate indices is considered, reaching a Pearson coefficient of –0.55, and exceeding the average of the negative values of this combined index with significant rates in the hydrological years showing a higher number of documented landslides. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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28 pages, 6074 KiB  
Article
Comparing Forward Conditional Analysis and Forward Logistic Regression Methods in a Landslide Susceptibility Assessment: A Case Study in Sicily
by Dario Costanzo and Clemente Irigaray
Hydrology 2020, 7(3), 37; https://doi.org/10.3390/hydrology7030037 - 10 Jul 2020
Cited by 2 | Viewed by 2334
Abstract
Forward logistic regression and conditional analysis have been compared to assess landslide susceptibility across the whole territory of the Sicilian region (about 25,000 km2) using previously existing data and a nested tiered approach. These approaches were aimed at singling out a [...] Read more.
Forward logistic regression and conditional analysis have been compared to assess landslide susceptibility across the whole territory of the Sicilian region (about 25,000 km2) using previously existing data and a nested tiered approach. These approaches were aimed at singling out a statistical correlation between the spatial distribution of landslides that have affected the Sicilian region in the past, and a set of controlling factors: outcropping lithology, rainfall, landform classification, soil use, and steepness. The landslide inventory used the proposal of building the models like the official one obtained in the PAI (hydro geologic asset plan) project, amounting to more than 33,000 events. The 11 types featured in PAI were grouped into 4 macro-typologies, depending on the inherent conditions believed to generate various kinds of failures and their kinematic evolution. The study has confirmed that it is possible to carry out a regional landslide susceptibility assessment based solely on existing data (i.e., factor maps and the landslide archive), saving a considerable amount of time and money. For scarp landslides, where the selected factors (steepness, landform classification, and lithology) are more discriminate, models show excellent performance: areas under receiver operating characteristic (ROC) (AUCs) average > 0.9, while hillslope landslide results are highly satisfactory (average AUCs of about 0.8). The stochastic approach makes it possible to classify the Sicilian territory depending on its propensity to landslides in order to identify those municipalities which are most susceptible at this level of study, and are potentially worthy of more specific studies, as required by European-level protocols. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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14 pages, 5517 KiB  
Article
Estimation of Actual Evapotranspiration Using the Remote Sensing Method and SEBAL Algorithm: A Case Study in Ein Khosh Plain, Iran
by Amir Ghaderi, Mehdi Dasineh, Maryam Shokri and John Abraham
Hydrology 2020, 7(2), 36; https://doi.org/10.3390/hydrology7020036 - 25 Jun 2020
Cited by 18 | Viewed by 3758
Abstract
The aim of this study was to estimate evapotranspiration (ET) using remote sensing and the Surface Energy Balance Algorithm for Land (SEBAL) in the Ilam province, Iran. Landsat 8 satellite images were used to calculate ET during the cultivation and harvesting of wheat [...] Read more.
The aim of this study was to estimate evapotranspiration (ET) using remote sensing and the Surface Energy Balance Algorithm for Land (SEBAL) in the Ilam province, Iran. Landsat 8 satellite images were used to calculate ET during the cultivation and harvesting of wheat crops. The evaluation using SEBAL, along with the FAO-Penman–Monteith method, showed that SEBAL has a sufficient accuracy for estimating ET. The values of the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), and correlation coefficient were 0.466, 2.9%, 0.222 mm/day, and 0.97, respectively. Satellite images showed that rainfall, except for the last month of cultivation, provided the necessary water requirements and there was no requirement for the use of other water resources for irrigation, with the exception of late May and early June. The maximum ET on the Ein Khosh Plain occurred in March. The irrigation requirements showed that the Ein Khosh Plain in March, which witnessed the highest ET, did not experience any deficiency of rainfall that month. However, during April and May, with maxima of 50 and 70 mm, respectively, water was needed for irrigation. During the plant growth periods, the greatest and least amount of water required were 231.23 and 19.47 mm/hr, respectively. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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11 pages, 4005 KiB  
Technical Note
Determination of the Probabilities of Landslide Events—A Case Study of Bhutan
by Raju Sarkar and Kelzang Dorji
Hydrology 2019, 6(2), 52; https://doi.org/10.3390/hydrology6020052 - 16 Jun 2019
Cited by 21 | Viewed by 4505
Abstract
Landslides have been and are prominent and devastating natural disasters in Bhutan due to its orography and intense monsoonal rainfall. The damage caused by landslides is huge, causing significant loss of lives, damage to infrastructure and loss of agricultural land. Several methods have [...] Read more.
Landslides have been and are prominent and devastating natural disasters in Bhutan due to its orography and intense monsoonal rainfall. The damage caused by landslides is huge, causing significant loss of lives, damage to infrastructure and loss of agricultural land. Several methods have been developed to understand the relationship between rainfall and landslide incidences. The most common method to understand the relationship is by defining thresholds using empirical methods which are expressed in either intensity-duration or event rainfall-duration terms. However, such thresholds determine the results in a binary form which may not be useful for landslide cases. Apart from defining thresholds, it is significant to validate the results. The article attempts to address both these issues by adopting a probabilistic approach and validating the results. The region of interest is the Chukha region located along the Phuentsholing-Thimphu Highway, which is a significant trade route between neighbouring countries and the national capital Thimphu. In the present study, probabilities are determined by Bayes’ theorem considering rainfall and landslide data from 2004 to 2014. Singular (rainfall intensity, rainfall duration and event rainfall) along with a combination (rainfall intensity and rainfall duration) of precipitation parameters were considered to determine the probabilities for landslide events. A sensitivity analysis was performed to verify the determined probabilities. The results depict that a combination of rainfall parameters is a better indicator to forecast landslides as compared to single rainfall parameter. Finally, the probabilities are validated using landslide records for 2015 using a threat score. The validation signifies that the probabilities can be used as the first line of action for an operational landslide warning system. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides Hazard)
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