Topic Editors

Department of Pure and Applied Sciences, University of Urbino "Carlo Bo”, 61029 Urbino PU, Italy
Department of Mathematics and Geosciences, University of Trieste, 34127 Trieste TS, Italy
Department of Pure and Applied Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy

Natural Hazards and Disaster Risks Reduction

Abstract submission deadline
closed (30 April 2023)
Manuscript submission deadline
closed (30 June 2023)
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Topic Information

Dear Colleagues,

The physical forces governing the Earth system can give rise to abrupt and severe natural events as a violent expression of ordinary environmental processes. Their impact is unevenly distributed on the land surface because of complex continental, regional, and local natural processes that overlap with anthropogenic forcing. The derived climate variations can directly or indirectly exacerbate most of the occurrences at different spatial and temporal scales. When such phenomena interact directly with inhabited areas and society, different risk scenarios can develop, characterised by a continuous and persistent dynamic or by a rapid mutability. From this perspective, natural hazards create a potential disaster that could impact anthropic activities, either through loss of life or injury, or through economic loss. The degree of safety in a community is the result of differential exposures to these events and of the level of preparation for them based on awareness and perception. The social development and spatial growth of human activities by consuming soil and natural resources has further contributed to creating vulnerability, increasing the challenges of conscious societies to cope with severe natural processes and their effects. The protection of territory is a key element in the UN 2030 Agenda’s the action strategy for sustainable development. The risk reduction is one of the guiding criteria of the 2015–2030 Sendai Framework’s sustainability policy.

This Topic collects original papers and inherent studies of different types of natural hazards (extreme climate and weather-related events and geological occurrences such as floods, landslides, subsidence, volcanic eruptions, earthquakes, etc.), vulnerability domains, exposure to disaster risk, but also manuscripts whose contents can help to mitigate risks. Among them, technical interventions and operational methodologies oriented to risk reduction strategies such as plans, protocols, working procedures, early warning systems, and any other innovations in the sector or elements that combine modern concepts with consolidated realities of the past should be included. State-of-the-art techniques are encouraged in the following three operating areas: spaceborne, aerial, and terrestrial activities. Numerical and experimental investigations for basic or application research and representative case studies are welcome too. Interdisciplinary and multidisciplinary approaches are considered added values to contribute to progress in the field of responsible and sustainable risk mitigation.

Dr. Stefano Morelli
Dr. Veronica Pazzi
Dr. Mirko Francioni
Topic Editors

Keywords

  • landslides
  • earthquakes
  • floods
  • remote sensing
  • modelling
  • geophysical techniques
  • climate change
  • new technologies
  • resilience

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
GeoHazards
geohazards
- - 2020 20.7 Days CHF 1000
Land
land
3.9 3.7 2012 14.8 Days CHF 2600
Remote Sensing
remotesensing
5.0 7.9 2009 23 Days CHF 2700
Sustainability
sustainability
3.9 5.8 2009 18.8 Days CHF 2400
Water
water
3.4 5.5 2009 16.5 Days CHF 2600

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Published Papers (85 papers)

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16 pages, 7349 KiB  
Article
Assessment of a Machine Learning Algorithm Using Web Images for Flood Detection and Water Level Estimates
by Marco Tedesco and Jacek Radzikowski
GeoHazards 2023, 4(4), 437-452; https://doi.org/10.3390/geohazards4040025 - 06 Nov 2023
Cited by 1 | Viewed by 1575
Abstract
Improving our skills to monitor flooding events is crucial for protecting populations and infrastructures and for planning mitigation and adaptation strategies. Despite recent advancements, hydrological models and remote sensing tools are not always useful for mapping flooding at the required spatial and temporal [...] Read more.
Improving our skills to monitor flooding events is crucial for protecting populations and infrastructures and for planning mitigation and adaptation strategies. Despite recent advancements, hydrological models and remote sensing tools are not always useful for mapping flooding at the required spatial and temporal resolutions because of intrinsic model limitations and remote sensing data. In this regard, images collected by web cameras can be used to provide estimates of water levels during flooding or the presence/absence of water within a scene. Here, we report the results of an assessment of an algorithm which uses web camera images to estimate water levels and detect the presence of water during flooding events. The core of the algorithm is based on a combination of deep convolutional neural networks (D-CNNs) and image segmentation. We assessed the outputs of the algorithm in two ways: first, we compared estimates of time series of water levels obtained from the algorithm with those measured by collocated tide gauges and second, we performed a qualitative assessment of the algorithm to detect the presence of flooding from images obtained from the web under different illumination and weather conditions and with low spatial or spectral resolutions. The comparison between measured and camera-estimated water levels pointed to a coefficient of determination R2 of 0.84–0.87, a maximum absolute bias of 2.44–3.04 cm and a slope ranging between 1.089 and 1.103 in the two cases here considered. Our analysis of the histogram of the differences between gauge-measured and camera-estimated water levels indicated mean differences of −1.18 cm and 5.35 cm for the two gauges, respectively, with standard deviations ranging between 4.94 and 12.03 cm. Our analysis of the performances of the algorithm to detect water from images obtained from the web and containing scenes of areas before and after a flooding event shows that the accuracy of the algorithm exceeded ~90%, with the Intersection over Union (IoU) and the boundary F1 score (both used to assess the output of segmentation analysis) exceeding ~80% (IoU) and 70% (BF1). Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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34 pages, 29359 KiB  
Article
Geo-Environment Vulnerability Assessment of Multiple Geohazards Using VWT-AHP: A Case Study of the Pearl River Delta, China
by Peng Huang, Xiaoyu Wu, Chuanming Ma and Aiguo Zhou
Remote Sens. 2023, 15(20), 5007; https://doi.org/10.3390/rs15205007 - 18 Oct 2023
Viewed by 940
Abstract
Geohazards pose significant risks to communities and infrastructure, emphasizing the need for accurate susceptibility assessments to guide land-use planning and hazard management. This study presents a comprehensive method that combines Variable Weight Theory (VWT) with Analytic Hierarchy Process (AHP) to assess geo-environment vulnerability [...] Read more.
Geohazards pose significant risks to communities and infrastructure, emphasizing the need for accurate susceptibility assessments to guide land-use planning and hazard management. This study presents a comprehensive method that combines Variable Weight Theory (VWT) with Analytic Hierarchy Process (AHP) to assess geo-environment vulnerability based on susceptibility to various geohazards. The method was applied to the Pearl River Delta in China, resulting in the classification of areas into high vulnerability (5961.85 km2), medium vulnerability (19,227.93 km2), low vulnerability (14,892.02 km2), and stable areas (1616.19 km2). The findings demonstrate improved accuracy and reliability compared to using AHP alone. ROC curve analysis confirms the enhanced performance of the integrated method, highlighting its effectiveness in discerning susceptibility levels and making informed decisions in hazard preparedness and risk reduction. Additionally, this study assessed the risks posed by geohazards to critical infrastructures, roads, and artificial surfaces, while discussing prevention strategies. However, this study acknowledges certain limitations, including the subjective determination of its judgment matrix and data constraints. Future research could explore the integration of alternative methods to enhance the objectivity of factor weighting. In practical applications, this study contributes to the understanding of geo-environment vulnerability assessments, providing insight into the intricate interplay among geological processes, human activities, and disaster resilience. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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13 pages, 1890 KiB  
Article
Is Sea Level Rise a Known Threat? A Discussion Based on an Online Survey
by Stefano Solarino, Elena Eva, Marco Anzidei, Gemma Musacchio and Maddalena De Lucia
GeoHazards 2023, 4(4), 367-379; https://doi.org/10.3390/geohazards4040021 - 03 Oct 2023
Cited by 1 | Viewed by 1553
Abstract
Since the last century, global warming has been triggering sea level rise at an unprecedented rate. In the worst case climate scenario, sea level could rise by up to 1.1 m above the current level, causing coastal inundation and cascading effects, thus affecting [...] Read more.
Since the last century, global warming has been triggering sea level rise at an unprecedented rate. In the worst case climate scenario, sea level could rise by up to 1.1 m above the current level, causing coastal inundation and cascading effects, thus affecting about one billion people around the world. Though widespread and threatening, the phenomenon is not well known to citizens as it is often overshadowed by other effects of global warming. Here, we show the results of an online survey carried out in 2020–2021 to understand the level of citizens’ knowledge on sea level rise including causes, effects, exacerbation in response to land subsidence and best practice towards mitigation and adaptation. The most important result of the survey is that citizens believe that it is up to governments to take action to cope with the effects of rising sea levels or mitigate the rise itself. This occurs despite the survey showing that they actually know what individuals can do and that a failure to act poses a threat to society. Gaps and preconceptions need to be eradicated by strengthening the collaboration between scientists and schools to improve knowledge, empowering our society. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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49 pages, 52986 KiB  
Article
Investigation of Landslide Susceptibility Decision Mechanisms in Different Ensemble-Based Machine Learning Models with Various Types of Factor Data
by Jiakai Lu, Chao Ren, Weiting Yue, Ying Zhou, Xiaoqin Xue, Yuanyuan Liu and Cong Ding
Sustainability 2023, 15(18), 13563; https://doi.org/10.3390/su151813563 - 11 Sep 2023
Cited by 2 | Viewed by 945
Abstract
Machine learning (ML)-based methods of landslide susceptibility assessment primarily focus on two dimensions: accuracy and complexity. The complexity is not only influenced by specific model frameworks but also by the type and complexity of the modeling data. Therefore, considering the impact of factor [...] Read more.
Machine learning (ML)-based methods of landslide susceptibility assessment primarily focus on two dimensions: accuracy and complexity. The complexity is not only influenced by specific model frameworks but also by the type and complexity of the modeling data. Therefore, considering the impact of factor data types on the model’s decision-making mechanism holds significant importance in assessing regional landslide characteristics and conducting landslide risk warnings given the achievement of good predictive performance for landslide susceptibility using excellent ML methods. The decision-making mechanism of landslide susceptibility models coupled with different types of factor data in machine learning methods was explained in this study by utilizing the Shapley Additive exPlanations (SHAP) method. Furthermore, a comparative analysis was carried out to examine the differential effects of diverse data types for identical factors on model predictions. The study area selected was Cenxi, Guangxi, where a geographic spatial database was constructed by combining 23 landslide conditioning factors with 214 landslide samples from the region. Initially, the factors were standardized using five conditional probability models, frequency ratio (FR), information value (IV), certainty factor (CF), evidential belief function (EBF), and weights of evidence (WOE), based on the spatial arrangement of landslides. This led to the formation of six types of factor databases using the initial data. Subsequently, two ensemble-based ML methods, random forest (RF) and XGBoost, were utilized to build models for predicting landslide susceptibility. Various evaluation metrics were employed to compare the predictive capabilities of different models and determined the optimal model. Simultaneously, the analysis was conducted using the interpretable SHAP method for intrinsic decision-making mechanisms of different ensemble-based ML models, with a specific focus on explaining and comparing the differential impacts of different types of factor data on prediction results. The results of the study illustrated that the XGBoost-CF model constructed with CF values of factors not only exhibited the best predictive accuracy and stability but also yielded more reasonable results for landslide susceptibility zoning, and was thus identified as the optimal model. The global interpretation results revealed that slope was the most crucial factor influencing landslides, and its interaction with other factors in the study area collectively contributed to landslide occurrences. The differences in the internal decision-making mechanisms of models based on different data types for the same factors primarily manifested in the extent of influence on prediction results and the dependency of factors, providing an explanation for the performance of standardized data in ML models and the reasons behind the higher predictive performance of coupled models based on conditional probability models and ML methods. Through comprehensive analysis of the local interpretation results from different models analyzing the same sample with different sample characteristics, the reasons for model prediction errors can be summarized, thereby providing a reference framework for constructing more accurate and rational landslide susceptibility models and facilitating landslide warning and management. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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23 pages, 10410 KiB  
Article
Subgrid Model of Fluid Force Acting on Buildings for Three-Dimensional Flood Inundation Simulations
by Riku Kubota, Jin Kashiwada and Yasuo Nihei
Water 2023, 15(17), 3166; https://doi.org/10.3390/w15173166 - 04 Sep 2023
Cited by 1 | Viewed by 1092
Abstract
In recent years, large-scale heavy rainfall disasters have occurred frequently in several parts of the world. Therefore, a quantitative approach to understanding how buildings are damaged during floods is necessary to develop appropriate flood-resistant technologies. In flood inundation simulations for the quantitative evaluation [...] Read more.
In recent years, large-scale heavy rainfall disasters have occurred frequently in several parts of the world. Therefore, a quantitative approach to understanding how buildings are damaged during floods is necessary to develop appropriate flood-resistant technologies. In flood inundation simulations for the quantitative evaluation of a building’s resistance to flooding, a subgrid model is necessary to appropriately evaluate the resistance of buildings smaller than the grid size at a medium grid resolution. In this study, a new subgrid (SG) 3D inundation model is constructed to evaluate the fluid force acting on buildings and assess the damage to individual buildings during flood inundation. The proposed method does not increase the computational load. The model is incorporated into a 2D and 3D hybrid model with high computational efficiency to construct a 3D river and inundation flow model. Its validity and effectiveness are evaluated through comparisons with field observations and the conventional equivalent roughness model. Considering horizontal and vertical velocity distributions, the proposed model showed statistically significant improvements in performance in terms of building loss indices such as velocity and fluid force. These results suggest that the SG model can effectively evaluate the fluid force acting on buildings, including the vertical distribution of flow velocities. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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17 pages, 2560 KiB  
Article
Research on a Scheduling Model for Social Emergency Resource Sharing Based on Emergency Contribution Index
by Wenqi Cui, Xinwu Chen, Boyu Liu, Qian Hu, Miaomiao Ma, Xing Xu, Zhanyun Feng, Jiale Chen and Wei Cui
Sustainability 2023, 15(17), 13029; https://doi.org/10.3390/su151713029 - 29 Aug 2023
Viewed by 549
Abstract
A large number of massive repair machines are urgently necessary for a post-disaster rescue. These machines also need to be operated by professionals, and the demands require the participation of different industries in the whole society since they cannot be met via the [...] Read more.
A large number of massive repair machines are urgently necessary for a post-disaster rescue. These machines also need to be operated by professionals, and the demands require the participation of different industries in the whole society since they cannot be met via the national emergency resource storage system. Therefore, the support of extensive emergency resources from different industries across the entire society is needed in the rescue process, that is, social emergency resource sharing. To achieve this sharing, an emergency resource scheduling model should have the ability to allocate resources from the whole society. However, traditional emergency scheduling models have not considered the suppliers’ willingness to take part in the scheduling activities and their abilities to supply the resources. To solve the above issues, this paper designs a scheduling model for social emergency resource sharing based on an emergency contribution index (SSERS). The emergency contribution index (ECI) can be used to find the enterprises that not only have the ability to provide efficient emergency resources on time but also have the willingness to participate in emergency rescue. The results show that our model effectively optimizes the basic models to some extent and achieves social emergency resource sharing. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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15 pages, 2535 KiB  
Article
Protecting Built Heritage against Flood: Mapping Value Density on Flood Hazard Maps
by Agnes W. Brokerhof, Renate van Leijen and Berry Gersonius
Water 2023, 15(16), 2950; https://doi.org/10.3390/w15162950 - 16 Aug 2023
Viewed by 986
Abstract
This paper describes the development and trial of a method (Quick Flood Risk Scan method) to determine the vulnerable value of monuments for flood risk assessment. It was developed in the context of the European Flood Directive for the Dutch Flood Risk Management [...] Read more.
This paper describes the development and trial of a method (Quick Flood Risk Scan method) to determine the vulnerable value of monuments for flood risk assessment. It was developed in the context of the European Flood Directive for the Dutch Flood Risk Management Plan. The assessment method enables differentiation of cultural heritage by cultural value and vulnerability to water from rainfall or flooding. With this method, hazard or exposure maps can be turned into risk maps showing the potential loss of cultural value in case of flooding with a particular probability. The Quick Flood Risk Scan method has been tested and validated in the City of Dordrecht, the Netherlands. This application was facilitated by an Open Lab of the SHELTER project. The trial in Dordrecht showed the potential of a simple method to prioritize monuments without calculations. The Quick Flood Risk Scan method enables even the non-expert assessor to make a preliminary qualitative assessment that can be followed by further analysis of a relevant selection of assets. It is useful as a low tier that feeds into higher tiers of a multi-level framework. The non-expert assessor may be a policy maker, an owner of a heritage asset, or an inhabitant. Nonetheless, the trial also raised several questions, ranging from where in a building valuable heritage is located and what the role of the building owner is to how policy makers implement the method and its outcomes. These questions provide relevant input for fine-tuning the method. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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18 pages, 3655 KiB  
Article
The Hydraulic and Boundary Characteristics of a Dike Breach Based on Cluster Analysis
by Mingxiao Liu, Yaru Luo, Chi Qiao, Zezhong Wang, Hongfu Ma and Dongpo Sun
Water 2023, 15(16), 2908; https://doi.org/10.3390/w15162908 - 11 Aug 2023
Viewed by 840
Abstract
It is important to determine the hydraulic boundary eigenvalues of typical embankment breaches before carrying out research on their occurrence mechanisms and assessing their repair technology. However, it is difficult to obtain the hydraulic boundary conditions of the typical levee breaches accurately with [...] Read more.
It is important to determine the hydraulic boundary eigenvalues of typical embankment breaches before carrying out research on their occurrence mechanisms and assessing their repair technology. However, it is difficult to obtain the hydraulic boundary conditions of the typical levee breaches accurately with minor or incomplete measured data due to the complexity and instability of the levee breach. Based on more than 100 groups of domestic and foreign test data of embankment/earth dam failures, the correlation between the hydraulic boundary eigenvalues of a breach was established based on the cluster analysis approach. Additionally, the missing values were imputed after correlating and fitting. Meanwhile, the hydraulic boundary parameters and the related equations of a generalized typical breach were obtained through the statistical analysis of the probability density of the dimensionless eigenvalues of the breach. The analysis showed that the width of the breach mainly ranges in 20~100 m, while the water head of the breach is 4~12 m, and the velocity of the breach is 2~8 m/s. The distribution probabilities of all them are about 64~71%. The probability density of the width-to-depth ratio and the Froude number of the breach are both subject to normal distribution characteristics. The distribution frequency of the width-to-depth ratio of 3~8 is approximately 55%, and the Froude number of 0.4~0.8 is approximately 60%. These methods and findings might provide valuable support for the statistical research of the boundary and hydraulic characteristics of the breach, and the closure technology of breach. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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26 pages, 12658 KiB  
Article
Machine Learning Approaches for Streamflow Modeling in the Godavari Basin with CMIP6 Dataset
by Subbarayan Saravanan, Nagireddy Masthan Reddy, Quoc Bao Pham, Abdullah Alodah, Hazem Ghassan Abdo, Hussein Almohamad and Ahmed Abdullah Al Dughairi
Sustainability 2023, 15(16), 12295; https://doi.org/10.3390/su151612295 - 11 Aug 2023
Cited by 2 | Viewed by 1300
Abstract
Accurate streamflow modeling is crucial for effective water resource management. This study used five machine learning models (support vector regressor (SVR), random forest (RF), M5-pruned model (M5P), multilayer perceptron (MLP), and linear regression (LR)) to simulate one-day-ahead streamflow in the Pranhita subbasin (Godavari [...] Read more.
Accurate streamflow modeling is crucial for effective water resource management. This study used five machine learning models (support vector regressor (SVR), random forest (RF), M5-pruned model (M5P), multilayer perceptron (MLP), and linear regression (LR)) to simulate one-day-ahead streamflow in the Pranhita subbasin (Godavari basin), India, from 1993 to 2014. Input parameters were selected using correlation and pairwise correlation attribution evaluation methods, incorporating a two-day lag of streamflow, maximum and minimum temperatures, and various precipitation datasets (including Indian Meteorological Department (IMD), EC-Earth3, EC-Earth3-Veg, MIROC6, MRI-ESM2-0, and GFDL-ESM4). Bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets were utilized in the modeling process. Model performance was evaluated using Pearson correlation (R), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE), and coefficient of determination (R2). IMD outperformed all CMIP6 datasets in streamflow modeling, while RF demonstrated the best performance among the developed models for both CMIP6 and IMD datasets. During the training phase, RF exhibited NSE, R, R2, and RMSE values of 0.95, 0.979, 0.937, and 30.805 m3/s, respectively, using IMD gridded precipitation as input. In the testing phase, the corresponding values were 0.681, 0.91, 0.828, and 41.237 m3/s. The results highlight the significance of advanced machine learning models in streamflow modeling applications, providing valuable insights for water resource management and decision making. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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17 pages, 6912 KiB  
Article
Experimental Research on Backward Erosion Piping Progression
by Jaromir Riha and Lubomir Petrula
Water 2023, 15(15), 2749; https://doi.org/10.3390/w15152749 - 29 Jul 2023
Cited by 2 | Viewed by 958
Abstract
Internal erosion is caused by seepage body forces acting on the soil particles. One of the most dangerous modes of internal erosion at hydraulic structures is backward erosion piping, which usually initiates at the downstream end of a seepage path, e.g., at the [...] Read more.
Internal erosion is caused by seepage body forces acting on the soil particles. One of the most dangerous modes of internal erosion at hydraulic structures is backward erosion piping, which usually initiates at the downstream end of a seepage path, e.g., at the downstream toe of the dam. The progress of backward erosion and the development of erosion pipes were tested in a newly developed laboratory device for three types of sand with grain sizes of 0/2, 0.25/2, and 0.25/1. The piezometric head along the gradually developing seepage “pipe” was observed by seventeen piezometers and seven pressure sensors. The seepage amount was measured by the volumetric method. The critical hydraulic gradient was determined and related to the soil porosity. The progression of the seepage path and relevant characteristics such as the piezometric and pressure heads and the amount of trapped sediment were observed by two synchronous cameras. Based on the analysis of the results of 42 tests, a new empirical formula for the backward erosion rate was proposed. The characteristics of lateral erosion were evaluated and compared with the available literature, which provided reasonably good agreement. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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16 pages, 9980 KiB  
Article
Experimental Investigation of Levee Erosion during Overflow and Infiltration with Varied Hydraulic Conductivities of Levee and Foundation Properties in Saturated Conditions
by Liaqat Ali and Norio Tanaka
GeoHazards 2023, 4(3), 286-301; https://doi.org/10.3390/geohazards4030016 - 25 Jul 2023
Viewed by 1197
Abstract
This study investigated erosion during infiltration and overflow events and considered different grain sizes and hydraulic conductivity properties; four experimental cases were conducted under saturated conditions. The importance of understanding flow regimes during overflow experiments including their distinct flow characteristics, shear stresses, and [...] Read more.
This study investigated erosion during infiltration and overflow events and considered different grain sizes and hydraulic conductivity properties; four experimental cases were conducted under saturated conditions. The importance of understanding flow regimes during overflow experiments including their distinct flow characteristics, shear stresses, and erosion mechanisms in assessing the potential for levee failure are discussed. The failure mechanism of levee slopes during infiltration experiments involves progressive collapse due to piping followed by increased liquefaction and loss of shear stress, with the failure progression dependent on the permeability of the foundation material and shear strength. The infiltration experiments illustrate that the rate of failure varied based on the permeability of the foundation material. In the case of IO-E7-F5, where the levee had No. 7 sand in the embankment and No. 5 sand in the foundation (lower permeability), the failure was slower and limited. It took around 90 min for 65% of the downstream slope to fail, allowing more time for response measures. On the other hand, in the case of IO-E8-F4, with No. 8 sand in the embankment and No. 4 sand in the foundation (higher hydraulic conductivity), the failure was rapid and extensive. The whole downstream slope failed within just 18 min, and the collapse extended to 75% of the levee crest. These findings emphasize the need for proactive measures to strengthen vulnerable sections of levees and reduce the risk of extensive failure. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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25 pages, 14144 KiB  
Article
Geographic-Information-System-Based Risk Assessment of Flooding in Changchun Urban Rail Transit System
by Gexu Liu, Yichen Zhang, Jiquan Zhang, Qiuling Lang, Yanan Chen, Ziyang Wan and Huanan Liu
Remote Sens. 2023, 15(14), 3533; https://doi.org/10.3390/rs15143533 - 13 Jul 2023
Cited by 4 | Viewed by 1193
Abstract
The frequent occurrence of urban flooding in recent years has resulted in significant damage to ground-level infrastructure and poses a substantial threat to the metro system. As the central city’s core transportation network for public transit, this threat can have unpredictable consequences on [...] Read more.
The frequent occurrence of urban flooding in recent years has resulted in significant damage to ground-level infrastructure and poses a substantial threat to the metro system. As the central city’s core transportation network for public transit, this threat can have unpredictable consequences on travel convenience and public safety. Therefore, assessing the risk of urban flooding in the metro system is of utmost importance. This study is the first of its kind to employ comprehensive natural disaster risk assessment theory, establishing an assessment database with 22 indicators. We propose a GIS-based method combined with the analytical hierarchy process (AHP) and an improved entropy weight method to comprehensively evaluate the urban flood risk in Changchun City’s metro systems in China. This study includes a total of nine metro lines, including those that are currently operational as well as those that are in the planning and construction phases, situated in six urban areas of Changchun City. In this study, we utilize the regional risk level within the 500 m buffer zone of the metro lines to represent the flood risk of the metro system. The proposed method assesses the flood risk of Changchun’s rail transit system. The results reveal that over 30% of Changchun’s metro lines are located in high-risk flood areas, mainly concentrated in the densely populated and economically prosperous western part of the central city. To validate the risk assessment, we vectorized the inundation points and overlaid them with the regional flood risk assessment results, achieving a model accuracy of over 90%. As no large-scale flood events have occurred in the Changchun rail transit system, we employed receiver operating characteristic (ROC) curves to verify the accuracy of the flood risk assessment model, resulting in an accuracy rate of 91%. These findings indicate that the present study is highly reliable and can provide decision makers with a scientific basis for mitigating future flood disasters. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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34 pages, 10093 KiB  
Article
Enhanced Absence Sampling Technique for Data-Driven Landslide Susceptibility Mapping: A Case Study in Songyang County, China
by Zijin Fu, Fawu Wang, Jie Dou, Kounghoon Nam and Hao Ma
Remote Sens. 2023, 15(13), 3345; https://doi.org/10.3390/rs15133345 - 30 Jun 2023
Cited by 6 | Viewed by 1123
Abstract
Accurate prediction of landslide susceptibility relies on effectively handling absence samples in data-driven models. This study investigates the influence of different absence sampling methods, including buffer control sampling (BCS), controlled target space exteriorization sampling (CTSES), information value (IV), and mini-batch k-medoids (MBKM), on [...] Read more.
Accurate prediction of landslide susceptibility relies on effectively handling absence samples in data-driven models. This study investigates the influence of different absence sampling methods, including buffer control sampling (BCS), controlled target space exteriorization sampling (CTSES), information value (IV), and mini-batch k-medoids (MBKM), on landslide susceptibility mapping in Songyang County, China, using support vector machines and random forest algorithms. Various evaluation metrics are employed to compare the efficacy of these sampling methods for susceptibility zoning. The results demonstrate that CTSES, IV, and MBKM methods exhibit an expansion of the high susceptibility region (maximum susceptibility mean value reaching 0.87) and divergence in the susceptibility index when extreme absence samples are present, with MBKM showing a comparative advantage (lower susceptibility mean value) compared to the IV model. Building on the strengths of different sampling methods, a novel integrative sampling approach that incorporates multiple existing methods is proposed. The integrative sampling can mitigate negative effects caused by extreme absence samples (susceptibility mean value is approximately 0.5 in the same extreme samples and presence-absence ratio) and obtain significantly better prediction results (AUC = 0.92, KC = 0.73, POA = 2.46 in the best model). Additionally, the mean level of susceptibility is heavily influenced by the proportion of absent samples. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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19 pages, 19655 KiB  
Article
Agricultural Drought Risk Assessment Based on a Comprehensive Model Using Geospatial Techniques in Songnen Plain, China
by Fengjie Gao, Si Zhang, Rui Yu, Yafang Zhao, Yuxin Chen and Ying Zhang
Land 2023, 12(6), 1184; https://doi.org/10.3390/land12061184 - 05 Jun 2023
Viewed by 1570
Abstract
Drought is a damaging and costly natural disaster that will become more serious in the context of global climate change in the future. Constructing a reliable drought risk assessment model and presenting its spatial pattern could be significant for agricultural production. However, agricultural [...] Read more.
Drought is a damaging and costly natural disaster that will become more serious in the context of global climate change in the future. Constructing a reliable drought risk assessment model and presenting its spatial pattern could be significant for agricultural production. However, agricultural drought risk mapping scientifically still needs more effort. Considering the whole process of drought occurrence, this study developed a comprehensive agricultural drought risk assessment model that involved all risk components (exposure, hazard, vulnerability and mitigation capacity) and their associated criteria using geospatial techniques and fuzzy logic. The comprehensive model was applied in Songnen Plain to justify its applicability. ROC and AUC techniques were applied to evaluate its efficiency, and the prediction rate was 88.6%. The similar spatial distribution of water resources further verified the model’s reliability. The southwestern Songnen Plain is a very-high-risk (14.44%) region, determined by a high vulnerability, very high hazardousness and very low mitigation capacity, and is the region that should be paid the most attention to; the central part is a cross-risk region of high risk (24.68%) and moderate risk (27.28%) with a serious disturbance of human agricultural activities; the northeastern part is a dry grain production base with a relatively optimal agricultural production condition of very low risk (22.12%) and low risk (11.48%). Different drought mitigation strategies should be adopted in different regions due to different drought causes. The findings suggest that the proposed model is highly effective in mapping comprehensive drought risk for formulating strong drought mitigation strategies and could be used in other drought-prone areas. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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17 pages, 3781 KiB  
Article
Spatial and Temporal Change in Meteorological Drought in Gansu Province from 1969 to 2018 Based on REOF
by Yuxuan Wang, Fan Deng, Yongxiang Cai and Yi Zhao
Sustainability 2023, 15(11), 9014; https://doi.org/10.3390/su15119014 - 02 Jun 2023
Cited by 1 | Viewed by 916
Abstract
Meteorological drought is one of the most serious natural disasters, and its impact in arid and semi-arid areas is significant. In order to explore the temporal and spatial distribution of meteorological disasters in Gansu Province, we first calculated the standardized precipitation evapotranspiration index [...] Read more.
Meteorological drought is one of the most serious natural disasters, and its impact in arid and semi-arid areas is significant. In order to explore the temporal and spatial distribution of meteorological disasters in Gansu Province, we first calculated the standardized precipitation evapotranspiration index (SPEI) based on the monthly meteorological data from 1969 to 2018 and extracted the drought events through the theory of runs. Then, REOF rotation orthogonal decomposition was performed to divide the study area into five climatic subregions. With each subregion as the basic unit, the variation characteristics and evolution trends of drought events at different time scales were compared based on the B-G segmentation algorithm (BG-algorithm). Finally, a correlation analysis was conducted to explore the driving factors of drought events in each subregion. The main conclusions are as follows: (1) The cumulative duration of drought in the study area showed a slight increase trend (0.475 day/decade) and a 19-year main cycle. The drought intensity showed a trend of first easing and then intensifying, especially after 2000; the drought intensified significantly and showed a spatial trend of decreasing drought in the northwest and worsening drought in the southeast. (2) The cumulative contribution rate of the first five modes of REOF decomposition was 64.46%, and the study was divided into five arid subregions: the Hexi region, middle Hedong region, eastern Hedong region, Wushaoling region and western Hedong region. (3) The meteorological drought in the Hexi region has eased significantly since 1988. In the eastern, central and western parts of the Yellow River, drought intensification was observed to have occurred in different degrees (0.12/decade, 0.129/decade, and 0.072/decade). The meteorological drought in the Wuelyaling region has alleviated significantly with a watershed region formed between drought alleviation and drought intensification. (4) Seasonally, the eastern Hedong region showed a significant trend of drought in spring, but the opposite in autumn. The trend of climate drying was obvious in the spring and summer, rather than in autumn and winter. The spring drought trend is the most obvious in the middle of the Hedong region. (5) The meteorological drought in the study area was affected by local climatic factors and circulation factors, but there were significant differences in the responses of different arid subregions to these factors. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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22 pages, 15235 KiB  
Article
Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization
by Junjie Ji, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang and Shiting Liu
Land 2023, 12(6), 1125; https://doi.org/10.3390/land12061125 - 25 May 2023
Cited by 6 | Viewed by 1366
Abstract
Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative samples used for machine learning. Recurrent neural network (RNN) has a memory [...] Read more.
Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative samples used for machine learning. Recurrent neural network (RNN) has a memory function, so when using an RNN for landslide susceptibility mapping purposes, the input order of the landslide-influencing factors affects the resulting quality of the model. The information value analysis calculates the landslide-influencing factors, determines the input order of data based on the importance of any specific factor in determining the landslide susceptibility, and improves the prediction potential of recurrent neural networks. The simple recurrent unit (SRU), a newly proposed variant of the recurrent neural network, is characterized by possessing a faster processing speed and currently has less application history in landslide susceptibility mapping. This study used recurrent neural networks optimized by information value analysis for landslide susceptibility mapping in Xinhui District, Jiangmen City, Guangdong Province, China. Four models were constructed: the RNN model with optimized negative sample selection, the SRU model with optimized negative sample selection, the RNN model, and the SRU model. The results show that the RNN model with optimized negative sample selection has the best performance in terms of AUC value (0.9280), followed by the SRU model with optimized negative sample selection (0.9057), the RNN model (0.7277), and the SRU model (0.6355). In addition, several objective measures of accuracy (0.8598), recall (0.8302), F1 score (0.8544), Matthews correlation coefficient (0.7206), and the receiver operating characteristic also show that the RNN model performs the best. Therefore, the information value analysis can be used to optimize negative sample selection in landslide sensitivity mapping in order to improve the model’s performance; second, SRU is a weaker method than RNN in terms of model performance. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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25 pages, 6644 KiB  
Article
The 100-Year Series of Weather-Related Fatalities in the Czech Republic: Interactions of Climate, Environment, and Society
by Rudolf Brázdil, Kateřina Chromá, Lukáš Dolák, Pavel Zahradníček, Jan Řehoř, Petr Dobrovolný and Ladislava Řezníčková
Water 2023, 15(10), 1965; https://doi.org/10.3390/w15101965 - 22 May 2023
Cited by 1 | Viewed by 1490
Abstract
The paper investigates weather-related fatalities over the territory of the Czech Republic in the 100-year period from 1921 to 2020. The unique database, created from documentary evidence (particularly newspapers), includes, for each deadly event, information about the weather event, the fatality itself, and [...] Read more.
The paper investigates weather-related fatalities over the territory of the Czech Republic in the 100-year period from 1921 to 2020. The unique database, created from documentary evidence (particularly newspapers), includes, for each deadly event, information about the weather event, the fatality itself, and related circumstances. A total of 2729 fatalities were detected during the 100-year period and were associated with various weather categories including frost (38%), convective storms (19%), floods (17%), fog (11%), snow and glaze ice (8%), windstorms (5%), and other inclement weather (2%). A detailed analysis was performed for each individual category. Fatalities occurred throughout the country, with a main maximum in winter (January) and a secondary maximum in summer (July), corresponding to the occurrence of extreme weather. Deaths were mainly interpreted as direct, caused by freezing to death/hypothermia or drowning, and occurred in the afternoon and at night in open countryside or on rivers and water bodies. Males outnumbered females, and adults outnumbered children and the elderly. Hazardous behavior was more frequent than non-hazardous behavior among victims. The information on fatalities and the structure of their characteristics strongly reflects historical milestones of the country, political and socioeconomic changes, as well as changes in lifestyle. Although important weather effects were observed on the deadliest events, the character of the data did not allow for clear evidence of the effects of long-term climate variability. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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24 pages, 6325 KiB  
Article
Dynamic Response Law and Failure Mechanism of Slope with Weak Interlayer under Combined Action of Reservoir Water and Seismic Force
by Wenpeng Ning and Hua Tang
Water 2023, 15(10), 1956; https://doi.org/10.3390/w15101956 - 21 May 2023
Cited by 1 | Viewed by 1554
Abstract
The southwestern region of China is close to the Eurasian earthquake zone. Many engineering areas in southwestern China are affected by earthquakes and are close to the epicenter of earthquakes that occur in this region. During earthquakes, slopes with weak interlayers are more [...] Read more.
The southwestern region of China is close to the Eurasian earthquake zone. Many engineering areas in southwestern China are affected by earthquakes and are close to the epicenter of earthquakes that occur in this region. During earthquakes, slopes with weak interlayers are more likely to cause large-scale landslides. In response to the low stability of slopes with weak interlayers in reservoir dam areas, the dynamic response law and failure mechanism of weak interlayered slopes under the combined action of reservoir water and seismic forces were studied through shaking table model tests and finite element numerical simulation software. The height of the water level and the size of the seismic waves were changed during these tests. The research results indicate that seismic waves are influenced by weak interlayers and are repeatedly superimposed between the weak interlayers and the slope surface, resulting in an acceleration amplification effect that increases by approximately 1.8 times compared to homogeneous slopes. Vertical earthquakes have a significant impact on the dynamic response of slopes, and their peak acceleration amplification coefficient can reach 0.83 times the horizontal peak acceleration. The stability of weak interlayers during earthquakes is the worst within the range of the direct action of reservoir water. The failure mode of a slope is as follows: earthquake action causes cracking in the upper part of the slope, and as the earthquake increases in intensity, and the infiltration of reservoir water intensifies, the cracks expand. The soft and muddy interlayer in the front section of the slope forms a sliding surface, and ultimately, the sliding failure forms an accumulation body at the foot of the slope. In reservoir dam areas, the stability of a slope is closely related to the engineering safety of the reservoir dam. Therefore, when a strong earthquake and the water level in a reservoir jointly affect a weak-interlayer slope, the slope is in the stage of plastic deformation and instability. The stability of the slope may be overestimated, and the slope is likely vulnerable to sliding instability, which needs to be monitored and treated. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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22 pages, 3837 KiB  
Article
Toward a Real-Time Analysis of Column Height by Visible Cameras: An Example from Mt. Etna, in Italy
by Alvaro Aravena, Giuseppe Carparelli, Raffaello Cioni, Michele Prestifilippo and Simona Scollo
Remote Sens. 2023, 15(10), 2595; https://doi.org/10.3390/rs15102595 - 16 May 2023
Viewed by 1329
Abstract
Volcanic plume height is one the most important features of explosive activity; thus, it is a parameter of interest for volcanic monitoring that can be retrieved using different remote sensing techniques. Among them, calibrated visible cameras have demonstrated to be a promising alternative [...] Read more.
Volcanic plume height is one the most important features of explosive activity; thus, it is a parameter of interest for volcanic monitoring that can be retrieved using different remote sensing techniques. Among them, calibrated visible cameras have demonstrated to be a promising alternative during daylight hours, mainly due to their low cost and low uncertainty in the results. However, currently these measurements are generally not fully automatic. In this paper, we present a new, interactive, open-source MATLAB tool, named ‘Plume Height Analyzer’ (PHA), which is able to analyze images and videos of explosive eruptions derived from visible cameras, with the objective of automatically identifying the temporal evolution of eruption columns. PHA is a self-customizing tool, i.e., before operational use, the user must perform an iterative calibration procedure based on the analysis of images of previous eruptions of the volcanic system of interest, under different eruptive, atmospheric and illumination conditions. The images used for the calibration step allow the computation of ad hoc expressions to set the model parameters used to recognize the volcanic plume in new images, which are controlled by their individual characteristics. Thereby, the number of frames used in the calibration procedure will control the goodness of the model to analyze new videos/images and the range of eruption, atmospheric, and illumination conditions for which the program will return reliable results. This also allows improvement of the performance of the program as new data become available for the calibration, for which PHA includes ad hoc routines. PHA has been tested on a wide set of videos from recent explosive activity at Mt. Etna, in Italy, and may represent a first approximation toward a real-time analysis of column height using visible cameras on erupting volcanoes. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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16 pages, 24299 KiB  
Article
PSI Spatially Constrained Clustering: The Sibari and Metaponto Coastal Plains
by Nicola Amoroso, Roberto Cilli, Davide Oscar Nitti, Raffaele Nutricato, Muzaffer Can Iban, Tommaso Maggipinto, Sabina Tangaro, Alfonso Monaco and Roberto Bellotti
Remote Sens. 2023, 15(10), 2560; https://doi.org/10.3390/rs15102560 - 14 May 2023
Cited by 3 | Viewed by 1352
Abstract
PSI data are extremely useful for monitoring on-ground displacements. In many cases, clustering algorithms are adopted to highlight the presence of homogeneous patterns; however, clustering algorithms can fail to consider spatial constraints and be poorly specific in revealing patterns at lower scales or [...] Read more.
PSI data are extremely useful for monitoring on-ground displacements. In many cases, clustering algorithms are adopted to highlight the presence of homogeneous patterns; however, clustering algorithms can fail to consider spatial constraints and be poorly specific in revealing patterns at lower scales or possible anomalies. Hence, we proposed a novel framework which combines a spatially-constrained clustering algorithm (SKATER) with a hypothesis testing procedure which evaluates and establishes the presence of significant local spatial correlations, namely the LISA method. The designed workflow ensures the retrieval of homogeneous clusters and a reliable anomaly detection; to validate this workflow, we collected Sentinel-1 time series from the Sibari and Metaponto coastal plains in Italy, ranging from 2015 to 2021. This particular study area is interesting due to the presence of important industrial and agricultural settlements. The proposed workflow effectively outlines the presence of both subsidence and uplifting that deserve to be focused and continuous monitoring, both for environmental and infrastructural purposes. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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20 pages, 54462 KiB  
Technical Note
Study on the Source of Debris Flow in the Northern Scenic Spot of Changbai Mountain Based on Multi-Source Data
by Jiahao Yan, Yichen Zhang, Jiquan Zhang, Yanan Chen and Zhen Zhang
Remote Sens. 2023, 15(9), 2473; https://doi.org/10.3390/rs15092473 - 08 May 2023
Viewed by 1205
Abstract
The northern scenic area of Changbai Mountain is a high-incidence area of debris flow disasters, which seriously threaten the safety of tourist’s lives and property. Monitoring debris flow and providing early warning is critical for timely avoidance. Monitoring the change of debris flow [...] Read more.
The northern scenic area of Changbai Mountain is a high-incidence area of debris flow disasters, which seriously threaten the safety of tourist’s lives and property. Monitoring debris flow and providing early warning is critical for timely avoidance. Monitoring the change of debris flow source is an effective way to predict debris flow, and the change of source can be reflected in the settlement deformation of the study area. The offset tracking technique (OT) is insensitive to the coherence of SAR images and can resist the decoherence of D-InSAR and SBSA-InSAR to a certain extent. It is a technical means for monitoring large gradient deformation. It has been widely used in the field of seismic activity, glaciers and landslides in recent years, but few scholars have applied this technique in the field of debris flow. In this paper, we use OT techniques in combination with field surveys, Google imagery and Sentinel-1 data to monitor surface deformation in the northern scenic area of Changbai Mountain in 2017 and use D-InSAR techniques to compare and complement the OT monitoring results. The results of this study show that for monitoring surface deformation in the study area after a mudslide, it is better to use both methods to determine the surface deformation in the study area rather than one, and that both methods have their own advantages and disadvantages and yet can complement each other. Finally, we have predicted the development trend of mudflows in the study area by combining the calculated single mudflow solids washout, which will help to improve the long-term monitoring and warning capability of mudflows in the study area. The study also enriches the application of offset-tracking technology and D-InSAR in the field of geohazard monitoring and provides new ideas and methods for the study of mudflow material source changes. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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21 pages, 22272 KiB  
Article
2D Numerical Simulation of Floods in Ebro River and Analysis of Boundary Conditions to Model the Mequinenza Reservoir Dam
by Pablo Vallés, Isabel Echeverribar, Juan Mairal, Sergio Martínez-Aranda, Javier Fernández-Pato and Pilar García-Navarro
GeoHazards 2023, 4(2), 136-156; https://doi.org/10.3390/geohazards4020009 - 27 Apr 2023
Cited by 3 | Viewed by 2211
Abstract
The computational simulation of rivers is a useful tool that can be applied in a wide range of situations from providing real time alerts to the design of future mitigation plans. However, for all the applications, there are two important requirements when modeling [...] Read more.
The computational simulation of rivers is a useful tool that can be applied in a wide range of situations from providing real time alerts to the design of future mitigation plans. However, for all the applications, there are two important requirements when modeling river behavior: accuracy and reasonable computational times. This target has led to recent developments in numerical models based on the full two-dimensional (2D) shallow water equations (SWE). This work presents a GPU accelerated 2D SW model for the simulation of flood events in real time. It is based on a well-balanced explicit first-order finite volume scheme able to run over dry beds without the numerical instabilities that are likely to occur when used in complex topography. The model is applied to reproduce a real event in the reach of the Ebro River (Spain) with a downstream reservoir, in which a study of the most appropriate boundary condition (BC) for modeling of the dam is assessed (time-dependent level condition and weir condition). The whole creation of the model is detailed in terms of mesh optimization and validation. The simulation results are compared with field data over the flood duration (up to 20 days), allowing an analysis of the performance and time saved by different GPU devices and with the different BCs. The high values of fit between observed and simulated results, as well as the computational times achieved, are encouraging to propose the use of the model as a forecasting system. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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28 pages, 10105 KiB  
Article
Permafrost Stability Mapping on the Tibetan Plateau by Integrating Time-Series InSAR and the Random Forest Method
by Fumeng Zhao, Wenping Gong, Tianhe Ren, Jun Chen, Huiming Tang and Tianzheng Li
Remote Sens. 2023, 15(9), 2294; https://doi.org/10.3390/rs15092294 - 27 Apr 2023
Viewed by 1465
Abstract
The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic [...] Read more.
The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic aperture radar (InSAR) is often adopted for measuring the ground deformation rate of the permafrost area, the effectiveness of which is, however, degraded in areas with geometric distortions in synthetic aperture radar (SAR) images. In this study, a method that integrates InSAR and the random forest method is proposed for an improved permafrost stability mapping on the Tibetan Plateau; to demonstrate the application of the proposed method, the permafrost stability mapping in a small area located in the central region of the Tibetan Plateau is studied. First, the ground deformation rate in the concerned area is studied with InSAR, in which 67 Sentinel-1 scenes taken in the period from 2014 to 2020 are collected and analyzed. Second, the relationship between the environmental factors (i.e., topography, land cover, land surface temperature, and distance to road) and the permafrost stability is mapped with the random forest method based on the high-quality data extracted from the initial InSAR analysis. Third, the permafrost stability in the whole study area is mapped with the trained random forest model, and the issue of data scarcity in areas where the terrain visibility of SAR images is poor or InSAR results are not available in permafrost stability mapping can be overcome. Comparative analyses demonstrate that the integration of the InSAR and the random forest method yields a more effective permafrost stability mapping compared with the sole application of InSAR analysis. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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18 pages, 4952 KiB  
Article
Urban Flood Resilience Evaluation Based on GIS and Multi-Source Data: A Case Study of Changchun City
by Zhen Zhang, Jiquan Zhang, Yichen Zhang, Yanan Chen and Jiahao Yan
Remote Sens. 2023, 15(7), 1872; https://doi.org/10.3390/rs15071872 - 31 Mar 2023
Cited by 4 | Viewed by 1954
Abstract
With extreme rainfall events and rapid urbanization, urban flood disaster events are increasing dramatically. As a key flood control city in China, Changchun City suffers casualties and economic losses every year due to floods. The improvement of flood resilience has become an important [...] Read more.
With extreme rainfall events and rapid urbanization, urban flood disaster events are increasing dramatically. As a key flood control city in China, Changchun City suffers casualties and economic losses every year due to floods. The improvement of flood resilience has become an important means for cities to resist flood risks. Therefore, this paper constructs an assessment model of urban flood resilience from four aspects: infrastructure, environment, society and economy. Then, it quantifies infrastructure and environmental vulnerability based on GIS, and uses TOPSIS to quantify social and economic recoverability. Finally, based on k-means clustering of infrastructure and environmental vulnerability and social and economic recoverability, the flood resilience of Changchun City was evaluated. The results show that different factors have different effects on flood resilience, and cities with low infrastructure and environmental vulnerability and high socioeconomic recoverability are more resilient in the face of floods. In addition, cities in the same cluster have the same flood resilience characteristics. The proposed framework can be extended to other regions of China or different countries by simply modifying the indicator system according to different regions, providing experience for regional flood mitigation and improving flood resilience. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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22 pages, 6460 KiB  
Review
Understanding the Mechanisms of Earth Fissuring for Hazard Mitigation in Najran, Saudi Arabia
by Mabkhoot Alsaiari, Basil Onyekayahweh Nwafor, Maman Hermana, Al Marzouki Hassan H. M. and Mohammed Irfan
Sustainability 2023, 15(7), 6006; https://doi.org/10.3390/su15076006 - 30 Mar 2023
Viewed by 1530
Abstract
Being a fast-growing city with a high rate of urbanization and agricultural development, the city of Najran, situated in the southwest of the Kingdom of Saudi Arabia, has witnessed a series of earth fissuring events and some other geo-environmental hazards in recent times. [...] Read more.
Being a fast-growing city with a high rate of urbanization and agricultural development, the city of Najran, situated in the southwest of the Kingdom of Saudi Arabia, has witnessed a series of earth fissuring events and some other geo-environmental hazards in recent times. These fissures have posed a significant threat to inhabitants and infrastructure in the area. A few studies suggest that excessive groundwater withdrawal is responsible for fissuring activities. Because of the intensity of this geo-hazard, this article presupposes that groundwater extraction alone cannot be responsible for the magnitude of fissuring activity in the area and discusses other severe factors that could be responsible for the earth fissures. The study proposes that the cause of the problem is multifaceted and synergistic, and outlines threatening factors that can inherently trigger more fissures in the region, based on the geologic history of the area and a critical review of investigative studies conducted in the area and beyond. Predicated on the region’s structural history, some undiscovered elements that can potentially cause fissuring in the region were identified and discussed. Some of these include the pre-existence of a fault system, a crack from the bedrock ridge, the existence of paleochannels, the collapsibility of loess, the tectonic (earthquake) history of the area, and differential compaction due to heterogeneity. The use of a metaheuristic and a combined application integrating other optimization algorithms can be utilized to determine optimum hyperparameters and present their statistical importance, thereby improving accuracy and dependability in fissure prediction in Najran. Reliable models would primarily be used to monitor active fissures and identify key factors utilizing spatial information, subsidence, groundwater-related data sets, etc. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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14 pages, 9923 KiB  
Article
Spatial and Temporal Characteristics of Dust Storms and Aeolian Processes in the Southern Balkash Deserts in Kazakhstan, Central Asia
by Gulnura Issanova, Azamat Kaldybayev, Yongxiao Ge, Jilili Abuduwaili and Long Ma
Land 2023, 12(3), 668; https://doi.org/10.3390/land12030668 - 12 Mar 2023
Cited by 4 | Viewed by 2001
Abstract
Sand and dust storms are hazardous to the environment and have a significant role in desertification. Under the influence of climate change and human activities, dust storms and aeolian processes have been common phenomena in the Southern Balkash deserts in Kazakhstan, Central Asia. [...] Read more.
Sand and dust storms are hazardous to the environment and have a significant role in desertification. Under the influence of climate change and human activities, dust storms and aeolian processes have been common phenomena in the Southern Balkash deserts in Kazakhstan, Central Asia. However, knowledge gaps on spatial and temporal characteristics of dust storms and aeolian process in the Southern Balkash deserts still exist. Therefore, in present study, meteorological observations and numerous cartographic materials were used to identify the powerful sources with the highest frequency of dust storms and aeolian processes in the Southern Balkash deserts. The result showed that the Southern Balkash deserts were covered mainly by transverse parabolic sands (48%), dome dunes (24%), and transverse dome dunes (23%), where the aeolian processes occurred to a significant degree. Significant and strong degrees of aeolian processes occurred in most of the Southern Balkash deserts. The eastern part of the Taukum and the northern part of the Zhamankum and Karakum deserts were prone to aeolian processes to a substantial degree. The Moiynkum, Bestas, Saryesikatyrau, and Taukum deserts had the most frequent storms, occuring, on average, 17 to 43 days/per year. The occurrence of dust storms has been of a stable decreasing trend since the 1990s, except for 2008–2009. Aeolian dust in the Southern Balkash deserts flowed mainly from the western and southwestern to the eastern and northeastern. The results of the present study shed light on the temporal and spatial characteristics of dust storms and aeolian processes in the Southern Balkash deserts. This is of great importance in helping to monitor and predict dust storms and motion patterns of aeolian dust in this region. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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18 pages, 3762 KiB  
Article
Ground Surface Deformation Analysis Integrating InSAR and GPS Data in the Karstic Terrain of Cheria Basin, Algeria
by Loubna Hamdi, Nabil Defaflia, Abdelaziz Merghadi, Chamssedine Fehdi, Ali P. Yunus, Jie Dou, Quoc Bao Pham, Hazem Ghassan Abdo, Hussein Almohamad and Motrih Al-Mutiry
Remote Sens. 2023, 15(6), 1486; https://doi.org/10.3390/rs15061486 - 07 Mar 2023
Cited by 2 | Viewed by 2084
Abstract
Karstic terrains are usually dominated by aquifer systems and/or underground cavities. Overexploitation of groundwater in such areas often induces land subsidence and sometimes causes sinkholes. The Cheria basin in Algeria suffers from severe land subsidence issues, and this phenomenon has been increasing in [...] Read more.
Karstic terrains are usually dominated by aquifer systems and/or underground cavities. Overexploitation of groundwater in such areas often induces land subsidence and sometimes causes sinkholes. The Cheria basin in Algeria suffers from severe land subsidence issues, and this phenomenon has been increasing in recent years due to population expansion and uncontrolled groundwater exploitation. This work uses GPS data and persistent scatterer interferometry synthetic aperture radar (PS-InSAR) techniques to monitor the land subsidence rate by employing Sentinel-1 satellite data for the period from 2016 to 2022. Our results demonstrate that the Cheria basin experiences both uplift and subsidence in places, with an overall substantial change in the land surface. The total cumulative subsidence over 6 years reached a maximum of 500 mm. Comparison of land deformation between PSI and GPS showed root mean square error (RMSE) values of about 2.83 mm/year, indicating that our analyzed results are satisfactorily reproducing the actual changes. Nonetheless, these results can be used to extract the susceptible zones for vertical ground displacement and evaluate the surface deformation inventory map of the region for reducing damages (e.g., human losses, economic impact, and environmental degradation) that may occur in the future (e.g., sinkholes) and can be further utilized in perspective for a sinkhole early warning system. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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20 pages, 13155 KiB  
Article
A Scenario-Based Case Study: Using AI to Analyze Casualties from Landslides in Chittagong Metropolitan Area, Bangladesh
by Edris Alam, Fahim Sufi and Abu Reza Md. Towfiqul Islam
Sustainability 2023, 15(5), 4647; https://doi.org/10.3390/su15054647 - 06 Mar 2023
Cited by 1 | Viewed by 1779
Abstract
Understanding the complex dynamics of landslides is crucial for disaster planners to make timely and effective decisions that save lives and reduce the economic impact on society. Using the landslide inventory of the Chittagong Metropolitan Area (CMA), we have created a new artificial [...] Read more.
Understanding the complex dynamics of landslides is crucial for disaster planners to make timely and effective decisions that save lives and reduce the economic impact on society. Using the landslide inventory of the Chittagong Metropolitan Area (CMA), we have created a new artificial intelligence (AI)-based insight system for the town planners and senior disaster recovery strategists of Chittagong, Bangladesh. Our system generates dynamic AI-based insights for a range of complex scenarios created from 7 different landslide feature attributes. The users of our system can select a particular kind of scenario out of the exhaustive list of 1.054 × 1041 possible scenario sets, and our AI-based system will immediately predict how many casualties are likely to occur based on the selected kind of scenario. Moreover, an AI-based system shows how landslide attributes (e.g., rainfall, area of mass, elevation, etc.) correlate with landslide casualty by drawing detailed trend lines by performing both linear and logistic regressions. According to the literature and the best of our knowledge, our CMA scenario-based AI insight system is the first of its kind, providing the most comprehensive understanding of landslide scenarios and associated deaths and damages in the CMA. The system was deployed on a wide range of platforms including Android, iOS, and Windows systems so that it could be easily adapted for strategic disaster planners. The deployed solutions were handed down to 12 landslide strategists and disaster planners for evaluations, whereby 91.67% of users found the solution easy to use, effective, and self-explanatory while using it via mobile. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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21 pages, 9011 KiB  
Article
Numerical Investigation of the Dynamic Response of a Sand Cushion with Multiple Rockfall Impacts
by Yu Zhang, Jierui Feng, Longhuan Du, Peng Zhao, Jiao Peng, Chen Yang, Hua Fan and Liangpu Li
Sustainability 2023, 15(4), 3554; https://doi.org/10.3390/su15043554 - 15 Feb 2023
Viewed by 1227
Abstract
A shed cave structure with a sand cushion is often used as a protective structure for rockfall disasters. Because of the randomness and unpredictability of rockfall disasters, the cushions of shed caves often suffer multiple impacts from rockfalls. Aiming at the problem of [...] Read more.
A shed cave structure with a sand cushion is often used as a protective structure for rockfall disasters. Because of the randomness and unpredictability of rockfall disasters, the cushions of shed caves often suffer multiple impacts from rockfalls. Aiming at the problem of multiple impacts of rockfall, this paper uses the three-dimensional discrete element method to study the dynamic response of multiple rockfall impacts on sand cushions from different heights. Before conducting large-scale simulation studies, the input parameters in the numerical model are verified with data from laboratory experiments. Analyzing the simulation results shows that when the same point is impacted multiple times, the maximum impact force and the maximum penetration depth will increase with the number of impacts. According to the numerical results, a calculation formula of the maximum impact force that considers the number of impacts is fitted. At the same time, considering the impact response when the rockfall impacts different positions multiple times, the distance range that the subsequent impact is not affected by the previous impact is given. The significance of studying the multiple impacts of rockfalls is shown by a numerical study of rockfalls impacting a sand cushion multiple times from different heights, and it provides a reference for the design of rockfall disaster-protection structures in practical engineering. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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26 pages, 8178 KiB  
Article
A Spatial Model of Landslides with A Micro-Topography and Vegetation Approach for Sustainable Land Management in the Volcanic Area
by Heni Masruroh, Soemarno Soemarno, Syahrul Kurniawan and Amin Setyo Leksono
Sustainability 2023, 15(4), 3043; https://doi.org/10.3390/su15043043 - 07 Feb 2023
Viewed by 1823
Abstract
This study aims to produce a spatial model for sustainable land management in landslide-prone areas, based on exploring non-stationary relationships between landslide events, geomorphological and anthropogenic variables on tropical hillsides, especially in Taji Village, Jabung District, East Java Province, Indonesia. A series of [...] Read more.
This study aims to produce a spatial model for sustainable land management in landslide-prone areas, based on exploring non-stationary relationships between landslide events, geomorphological and anthropogenic variables on tropical hillsides, especially in Taji Village, Jabung District, East Java Province, Indonesia. A series of approaches combine in this research, and methods are used to construct independent and dependent variables so that GWR can analyze them to obtain the best model. Transformation of categorical data on microtopography, landform, and land cover variables was carried out. When modelled, landscape metrics can explain landslide events in the study area better than distance metrics with adj. R2 = 0.75 and AICc = 2526.38. Generally, local coefficient maps for each variable are mapped individually to reveal their relationship with landslide events, but in this study they are integrated to make it more intuitive and less confusing. From this map, it was found that most of the variables that showed the most positive relationship to the occurrence of landslides in the study area were the divergent footslopes. At the same time, the negative one was plantation land. It was concluded that the methodological approach offered and implemented in this study provides significant output results for the spatial analysis of the interaction of landslide events with geomorphological and anthropogenic variables locally, which cannot be explained in a global regression. This study produces a detailed scale landslide-prone conservation model in tropical hill areas and can be reproduced under the same geo-environmental conditions. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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16 pages, 11713 KiB  
Article
Proposal of a Disrupted Road Detection Method in a Tsunami Event Using Deep Learning and Spatial Data
by Jun Sakamoto
Sustainability 2023, 15(4), 2936; https://doi.org/10.3390/su15042936 - 06 Feb 2023
Viewed by 1197
Abstract
Tsunamis generated by undersea earthquakes can cause severe damage. It is essential to quickly assess tsunami-damaged areas to take emergency measures. In this study, I employ deep learning and develop a model using aerial photographs and road segment data. I obtained data from [...] Read more.
Tsunamis generated by undersea earthquakes can cause severe damage. It is essential to quickly assess tsunami-damaged areas to take emergency measures. In this study, I employ deep learning and develop a model using aerial photographs and road segment data. I obtained data from the aerial photographs taken after the Great East Japan Earthquake; the deep learning model used was YOLOv5. The proposed method based on YOLOv5 can determine damaged roads from aerial pictures taken after a disaster. The feature of the proposed method is to use training data from images separated by a specific range and to distinguish the presence or absence of damage related to the tsunami. The results show that the proposed method is more accurate than a comparable traditional method, which is constructed by labeling and learning the damaged areas. The highest F1 score of the traditional method was 60~78%, while the highest F1 score of the proposed method was 72~83%. The traditional method could not detect locations where it is difficult to determine the damage status from aerial photographs, such as where houses are not completely damaged. However, the proposed method was able to detect them. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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25 pages, 15121 KiB  
Article
Integrated Risk Assessment of Agricultural Drought Disasters in the Major Grain-Producing Areas of Jilin Province, China
by Jiawang Zhang, Jianguo Wang, Shengbo Chen, Mingchang Wang, Siqi Tang and Wutao Zhao
Land 2023, 12(1), 160; https://doi.org/10.3390/land12010160 - 03 Jan 2023
Cited by 3 | Viewed by 1554
Abstract
The impact of global climate change has intensified, and the frequent occurrence of meteorological disasters has posed a serious challenge to crop production. This article conducts an integrated risk assessment of agricultural drought disasters in the main grain-producing areas of Jilin Province using [...] Read more.
The impact of global climate change has intensified, and the frequent occurrence of meteorological disasters has posed a serious challenge to crop production. This article conducts an integrated risk assessment of agricultural drought disasters in the main grain-producing areas of Jilin Province using the temperature and precipitation data of the study area from 1955 to 2020, the sown area of crops, historical disaster data, regional remote sensing images, and statistical yearbook data. The agricultural drought integrated risk assessment model was built around four factors: drought hazards, vulnerability of hazard-bearing bodies, sensitivity of disaster-pregnant environments, and stability of disaster mitigation capacity. The results show that the study area has shown a trend of changing from wet to dry and then wet over the past 66 years, with the occasional occurrence of severe drought, and a decreasing trend at a rate of −0.089. (10a)−1 overall. The integrated risk of drought in the study area exhibits regional clustering, and the overall risk level has some relationship spatially with the regional geological tectonic units, with the high-risk level concentrated in the central area of Song Liao Basin and close to the geological structure of Yishu Graben and the low risk level concentrated in the marginal area of Song Liao Basin. Based on the results of the risk factor analysis, integrated risk prevention suggestions for drought in the main grain-producing areas of Jilin Province were put forward from four aspects. Fine identification and evaluation of high-risk areas of agricultural drought can provide a quantitative basis for effective drought resistance activities in relevant areas. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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21 pages, 10569 KiB  
Article
Study on the Evolution of a Flooded Tailings Pond and Its Post-Failure Effects
by Mengchao Chang, Weimin Qin, Hao Wang, Haibin Wang, Chengtang Wang and Xiuli Zhang
Water 2023, 15(1), 173; https://doi.org/10.3390/w15010173 - 31 Dec 2022
Cited by 1 | Viewed by 1823
Abstract
In order to avoid the risk of tailing pond failures and to minimize the post-failure losses, it is necessary to analyze the current operation status of tailings ponds, to explore the evolution law of their failure process, to grasp their post-failure impact range, [...] Read more.
In order to avoid the risk of tailing pond failures and to minimize the post-failure losses, it is necessary to analyze the current operation status of tailings ponds, to explore the evolution law of their failure process, to grasp their post-failure impact range, and to propose corresponding effective prevention and control measures. Based on a tailings pond in China, this paper establishes a 1:200 scale indoor model to explore the evolution law of post-failure tailings discharge in a tailings pond under flooded roof conditions; secondly, the finite element difference method and smooth particle fluid dynamics are combined to compare and analyze the post-failure impact area and to delineate the risk prevention and control area. The results of the study show that, during the dam break, the lower tailing sand in the breach is the first to slip, and after forming a steep can, the upper tailing sand in the steep can is pulled to slip, so that the erosion trench mainly develops vertically first, and then laterally. The velocity of the discharged tailing sand will quickly reach its peak value in a short period of time and then decrease to the creeping stage; the front edge of the sand flow is the first to stop moving, and the trailing edge of the tailing sand accumulation depth continues to increase until the end of the dam failure, at which point the initial bottom dam area of the discharge tailing sand flow velocity is the largest. The further the tailings are released from the initial dam, the smaller the accumulation depth and the larger the particle size, and the larger the elevation of the foundation in the same section, the smaller the accumulation depth and the larger the particle size; further, the presence of blocking materials will increase the local tailings accumulation depth. Based on the maximum flow velocity of the discharged tailings and the accumulation depth, the risk area downstream of the tailings pond is divided, so that relocation measures can be formulated. The test results can provide an important reference for the operation and management of similar tailings ponds. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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22 pages, 5818 KiB  
Article
Modelling Erosion and Floods in Volcanic Environment: The Case Study of the Island of Vulcano (Aeolian Archipelago, Italy)
by Rosanna Bonasia, Agnese Turchi, Paolo Madonia, Alessandro Fornaciai, Massimiliano Favalli, Andrea Gioia and Federico Di Traglia
Sustainability 2022, 14(24), 16549; https://doi.org/10.3390/su142416549 - 09 Dec 2022
Viewed by 1648
Abstract
The re-mobilization of volcaniclastic material poses a hazard factor which, although it decreases with time since the last eruption, remains present in the hydrographic basins of volcanic areas. Herein, we present the results of the numerical modelling of erosive phenomena of volcanic deposits, [...] Read more.
The re-mobilization of volcaniclastic material poses a hazard factor which, although it decreases with time since the last eruption, remains present in the hydrographic basins of volcanic areas. Herein, we present the results of the numerical modelling of erosive phenomena of volcanic deposits, as well as of flooding in the volcanic area. The proposed approach includes runoff estimation, land use analysis, and the application of hydraulic and erosion modelling. It exploits the Iber software, a widely used and validated model for rainfall-runoff, river flooding, and erosion and sediment transport modelling. The methodology was applied to the Island of Vulcano (Italy), known for the erosion phenomena that affect the slopes of one of its volcanic cones (La Fossa cone). The rainfall excess was calculated using a 19-year dataset of hourly precipitations, and the curve number expressed by the information on soil cover in the area, derived from the land cover and land use analysis. The erosion and flow models were performed considering different rainfall scenarios. Results show a particularly strong erosion, with thicknesses greater than 0.4 m. This is consistent with field observations, in particular with some detailed data collected both after intense events and by long-term observation. Results of the hydraulic simulations show that moderate and torrential rainfall scenarios can lead to flood levels between 0.2 and 0.6 m, which mostly affect the harbours located in the island’s inhabited area. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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26 pages, 10127 KiB  
Article
Post Evaluation of Slope Cutting on Loess Slopes under Long-Term Rainfall Based on a Model Test
by Guodong Liu, Zhijun Zhou, Shiqiang Xu and Yuanmeng Cheng
Sustainability 2022, 14(23), 15838; https://doi.org/10.3390/su142315838 - 28 Nov 2022
Viewed by 1394
Abstract
The failure of treated slopes around the world, especially in China, is occurring at a noteworthy rate, resulting in an urgent requirement for post evaluation of the treated slopes; however, there is no mature technique established for post evaluation. By using a real [...] Read more.
The failure of treated slopes around the world, especially in China, is occurring at a noteworthy rate, resulting in an urgent requirement for post evaluation of the treated slopes; however, there is no mature technique established for post evaluation. By using a real loess slope treated by slope cutting in Shaanxi Province as the prototype, indoor geotechnical tests and model tests were performed to reveal the rainwater infiltration characteristics and pressure-varying characteristics inside the slope, the results of which were used to conduct a post evaluation of the slope in situ. The results mainly showed that the effect of rainwater scouring on the slope surface weakened gradually into a steady state at the end of the first year. The rainwater upon the slope surface preferentially infiltrated the platforms with gradually reducing rates; however, the observed wetting front cannot be regarded as the border between the unsaturated and saturated loesses. The soil pressures inside the slope did not increase, but decreased during the early period of rainfall. The displacements of key points mainly occurred during the first two years and then steady periods were entered. The above results were utilized to conduct a post evaluation of the slope prototype, by which a post evaluation framework was constructed. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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20 pages, 5469 KiB  
Article
A Monitoring Method Based on Vegetation Abnormal Information Applied to the Case of Jizong Shed-Tunnel Landslide
by Qing Guo, Lianzi Tong and Hua Wang
Remote Sens. 2022, 14(22), 5640; https://doi.org/10.3390/rs14225640 - 08 Nov 2022
Cited by 1 | Viewed by 1533
Abstract
Landslides are one of the most dangerous natural disasters, which have affected national economic development and social stability. This paper proposes a method to indirectly monitor the deformation characteristics of landslides by extracting the abnormal vegetation information, especially for the inaccessible high-mountain landslides [...] Read more.
Landslides are one of the most dangerous natural disasters, which have affected national economic development and social stability. This paper proposes a method to indirectly monitor the deformation characteristics of landslides by extracting the abnormal vegetation information, especially for the inaccessible high-mountain landslides in southwestern China. This paper extracts the vegetation anomaly information in the Jizong Shed-Tunnel landslide which is located on the main traffic road to Tibet by the optical remote sensing Gaofen-1 (GF-1) data, and analyzes the temporal and spatial characteristics of the vegetation anomaly information through a time series. Then, we use the small baseline subsets interferometry synthetic aperture radar (SBAS-InSAR) technology to process Sentinel-1 data to obtain the time-series surface deformation information. Finally, we analyze and verify the results of the two methods. The results show that there is obvious vegetation coverage (VC) decline, with a maximum increasing percentage of 8.77% for the low and medium VC, and obvious surface deformation around the landslide, with the highest settlement rate of between 0 mm/year and 30 mm/year. Through the time-series analysis, we find that the change trends of the two methods are basically the same. This paper shows that the method of using abnormal vegetation information to monitor the Jizong Shed-Tunnel landslide has a certain degree of reliability and practicability. It can provide a new idea and effective supplement for landslide monitoring. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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18 pages, 7016 KiB  
Article
High-Resolution Hazard Assessment for Tropical Cyclone-Induced Wind and Precipitation: An Analytical Framework and Application
by Jiting Tang, Fuyu Hu, Yimeng Liu, Weiping Wang and Saini Yang
Sustainability 2022, 14(21), 13969; https://doi.org/10.3390/su142113969 - 27 Oct 2022
Cited by 3 | Viewed by 1520
Abstract
Intensified tropical cyclones (TCs) threaten the socioeconomic development of coastal cities. The coupling of strong wind and precipitation with the TC process usually amplifies the destructive effects of storms. Currently, an integrated analytical framework for TC hazard assessment at the city level that [...] Read more.
Intensified tropical cyclones (TCs) threaten the socioeconomic development of coastal cities. The coupling of strong wind and precipitation with the TC process usually amplifies the destructive effects of storms. Currently, an integrated analytical framework for TC hazard assessment at the city level that combines the joint statistical characteristics of multiple TC-induced hazards and local environmental features does not exist. In this study, we developed a novel hazard assessment framework with a high spatiotemporal resolution that includes a fine-tuned K-means algorithm for clustering TC tracks and a Copula model to depict the wind–precipitation joint probability distribution of different TC categories. High-resolution wind and precipitation data were used to conduct an empirical study in Shenzhen, a coastal megacity in Guangdong Province, China. The results show that the probabilities of TC-induced wind speed and precipitation exhibit significant spatial heterogeneity in Shenzhen, which can be explained by the characteristics of TC tracks and terrain environment factors. In general, the hazard intensity of TCs landing from the west side is higher than that from the east side, and the greatest TC intensity appears on the southeast coast of Shenzhen, implying that more disaster prevention efforts are needed. The proposed TC hazard assessment method provides a solid base for highly precise risk assessment at the city level. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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23 pages, 7128 KiB  
Article
Long-Term Flooding Maps Forecasting System Using Series Machine Learning and Numerical Weather Prediction System
by Ming-Jui Chang, I-Hang Huang, Chih-Tsung Hsu, Shiang-Jen Wu, Jihn-Sung Lai and Gwo-Fong Lin
Water 2022, 14(20), 3346; https://doi.org/10.3390/w14203346 - 21 Oct 2022
Cited by 2 | Viewed by 2141
Abstract
Accurate real-time forecasts of inundation depth and area during typhoon flooding is crucial to disaster emergency response. The development of an inundation forecasting model has been recognized as essential to manage disaster risk. In the past, most researchers used multiple single-point forecasts to [...] Read more.
Accurate real-time forecasts of inundation depth and area during typhoon flooding is crucial to disaster emergency response. The development of an inundation forecasting model has been recognized as essential to manage disaster risk. In the past, most researchers used multiple single-point forecasts to obtain surface flooding depth forecasts with spatial interpolation. In this study, a forecasting model (QPF-RIF) integrating a hydrodynamic model (SOBEK), support vector machine–multi-step forecast (SVM-MSF), and a self-organizing map (SOM) were proposed. The task of this model was divided into four parts: hydrodynamic simulation, point forecasting, inundation database clustering, and spatial expansion. First, the SOBEK model was used in simulating inundation hydrodynamics to construct the flooding maps database. Second, the SVM-MSF yields water level (inundation volume) forecasted with a 1 to 72 h lead time. Third, the SOM clustered the previous flooding maps database into several groups representing different flooding characteristics. Finally, a spatial expansion module produced inundation maps based on forecasting information from forecasting flood volume and flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we presented an application to the Yilan River basin in Taiwan. Our forecasting results indicated that the proposed model yields accurate flood inundation maps (less than 1 cm error) for a 1 h lead time. For long-term forecasting (46 h to 72 h ahead), the model controlled the error of the forecast results within 7 cm. In the testing events, the model forecasted an average of 83% of the flooding area in the long term. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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13 pages, 4644 KiB  
Article
Buffer Capacity of Steel Shed with Two Layer Absorbing System against the Impact of Rockfall Based on Coupled SPH-FEM Method
by Chun Liu and Hongjun Liao
Sustainability 2022, 14(20), 13680; https://doi.org/10.3390/su142013680 - 21 Oct 2022
Cited by 1 | Viewed by 1636
Abstract
This study aimed to find the optimal thickness combination of the two-layered absorbing system combinated with an expanded polystyrene (EPS) cushion and a soil layer in a steel shed under dynamic loadings. The coupled Smooth Particle Hydrodynamic method (SPH) and Finite Element Method [...] Read more.
This study aimed to find the optimal thickness combination of the two-layered absorbing system combinated with an expanded polystyrene (EPS) cushion and a soil layer in a steel shed under dynamic loadings. The coupled Smooth Particle Hydrodynamic method (SPH) and Finite Element Method (FEM) were introduced to simulate the impact of the rockfall against the steel shed with a two-layer absorbing system. By comparing the numerical results with test data, the coupled numerical model was well validated. Through the verified numerical model, a series of numerical experiments were carried out to find the optimal combination for the two-layered absorbing system. The values of the EPS layer thickness as a percentage of the total thickness were set as 0% (P1), 20% (P2), 40% (P3), 60% (P4), 80% (P5), and 100% (P6). The results show that the coupled FEM–SPH method was an effective method to simulate rockfall impacting the steel rock shed; P4 (0.6 m thickness EPS cushion and 0.9 m thickness soil layer) was the most efficient combination, which can significantly reduce the structural displacement response by 43%. A two-layered absorbing system can effectively absorb about 90% of the total energy. The obtained results yield scientifically sound guidelines for further research on the design of steel sheds against rockfall. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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16 pages, 736 KiB  
Article
A Case Study of the “7-20” Extreme Rainfall and Flooding Event in Zhengzhou, Henan Province, China from the Perspective of Fragmentation
by Zhouying Chen, Feng Kong and Meng Zhang
Water 2022, 14(19), 2970; https://doi.org/10.3390/w14192970 - 22 Sep 2022
Cited by 11 | Viewed by 2930
Abstract
Disaster crisis management is the last defensive line in the face of extreme rainstorm disasters. However, fragmentation undermines the effectiveness of disaster crisis management, and the “7-20” extreme rainfall flooding disaster in Zhengzhou, Henan province, China in 2021 revealed a series of fragmentation [...] Read more.
Disaster crisis management is the last defensive line in the face of extreme rainstorm disasters. However, fragmentation undermines the effectiveness of disaster crisis management, and the “7-20” extreme rainfall flooding disaster in Zhengzhou, Henan province, China in 2021 revealed a series of fragmentation problems. The effectiveness of China’s emergency storm flooding management must be seriously considered. We used the “7-20” extreme rainfall event in Zhengzhou, Henan province in China as a case study to perform an inductive, qualitative investigation to understand what fragmentation is and how fragmentation reduces efficacy. Most of the data used for this research were gathered from Chinese official records and online news articles. This study first highlights pertinent studies that have been performed and then presents a comprehensive theoretical framework of fragmentation in catastrophe crisis management, which consists of five aspects: fragmented emergency legislation, emergency organization, information, perception, and services. Second, we have deduced which human responses in the “7-20” event represent the fragmentation issues, and we have examined the detrimental effects of fragmentation in flood crisis management. Finally, suggestions are made for China to increase the effectiveness of disaster crisis management, including encouraging regulatory convergence, matching emergency responsibility and authority, establishing an information-sharing platform, bolstering emergency education and raising risk perception, and changing the dualistic system in disaster crisis management. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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24 pages, 55551 KiB  
Article
Numerical Analysis of an Explicit Smoothed Particle Finite Element Method on Shallow Vegetated Slope Stability with Different Root Architectures
by Xichun Jia, Wei Zhang, Xinghan Wang, Yuhao Jin and Peitong Cong
Sustainability 2022, 14(18), 11272; https://doi.org/10.3390/su141811272 - 08 Sep 2022
Cited by 6 | Viewed by 1921
Abstract
Planting vegetation is an environmentally friendly method for reducing landslides. Current vegetated slope analysis fails to consider the influence of different root architectures, and the accuracy and effectiveness of the numerical simulations need to be improved. In this study, an explicit smoothed particle [...] Read more.
Planting vegetation is an environmentally friendly method for reducing landslides. Current vegetated slope analysis fails to consider the influence of different root architectures, and the accuracy and effectiveness of the numerical simulations need to be improved. In this study, an explicit smoothed particle finite element method (eSPFEM) was used to evaluate slope stability under the influence of vegetation roots. The Mohr–Coulomb constitutive model was extended by incorporating apparent root cohesion into the shear strength of the soil. The slope factors of safety (FOS) of four root architectures (uniform, triangular, parabolic, and exponential) for various planting distances, root depths, slope angles, and planting locations were calculated using the shear strength reduction technique with a kinetic energy-based criterion. The results indicated that the higher the planting density, the stronger the reinforcement effect of the roots on the slope. With increasing root depth, the FOS value first decreased and then increased. The FOS value decreased with an increase in slope angle. Planting on the entire ground surface had the best improvement effect on the slope stability, followed by planting vegetation with a uniform root architecture in the upper slope region or planting vegetation with triangular or exponential root architecture on the slope’s toe. Our findings are expected to deepen our understanding of the contributions of different root architectures to vegetated slope protection and guide the selection of vegetation species and planting locations. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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24 pages, 5318 KiB  
Article
Comparing Root Cohesion Estimates from Three Models at a Shallow Landslide in the Oregon Coast Range
by Collin Cronkite-Ratcliff, Kevin M. Schmidt and Charlotte Wirion
GeoHazards 2022, 3(3), 428-451; https://doi.org/10.3390/geohazards3030022 - 01 Sep 2022
Viewed by 2078
Abstract
Although accurate root cohesion model estimates are essential to quantify the effect of vegetation roots on shallow slope stability, few means exist to independently validate such model outputs. One validation approach for cohesion estimates is back-calculation of apparent root cohesion at a landslide [...] Read more.
Although accurate root cohesion model estimates are essential to quantify the effect of vegetation roots on shallow slope stability, few means exist to independently validate such model outputs. One validation approach for cohesion estimates is back-calculation of apparent root cohesion at a landslide site with well-documented failure conditions. The catchment named CB1, near Coos Bay, Oregon, USA, which experienced a shallow landslide in 1996, is a prime locality for cohesion model validation, as an abundance of data and observations from the site generated broad insights related to hillslope hydrology and slope stability. However, previously published root cohesion values at CB1 used the Wu and Waldron model (WWM), which assumes simultaneous root failure and therefore likely overestimates root cohesion. Reassessing published cohesion estimates from this site is warranted, as more recently developed models include the fiber bundle model (FBM), which simulates progressive failure with load redistribution, and the root bundle model-Weibull (RBMw), which accounts for differential strain loading. We applied the WWM, FBM, and RBMw at CB1 using post-failure root data from five vegetation species. At CB1, the FBM and RBMw predict values that are less than 30% of the WWM-estimated values. All three models show that root cohesion has substantial spatial heterogeneity. Most parts of the landslide scarp have little root cohesion, with areas of high cohesion concentrated near plant roots. These findings underscore the importance of using physically realistic models and considering lateral and vertical spatial heterogeneity of root cohesion in shallow landslide initiation and provide a necessary step towards independently assessing root cohesion model validity. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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23 pages, 1214 KiB  
Article
Breaking the Negative Feedback Loop of Disaster, Conflict, and Fragility: Analyzing Development Aid by Japan and South Korea
by Suyeon Lee and Huck-ju Kwon
Sustainability 2022, 14(16), 10003; https://doi.org/10.3390/su141610003 - 12 Aug 2022
Cited by 3 | Viewed by 1747
Abstract
Disaster risk reduction (DRR) has become an important element of donor policy, because numerous governments have expressed their commitment to helping countries vulnerable to natural hazards by mainstreaming DRR into their development programs. Meanwhile, countries that are considered fragile, as well as conflict-affected [...] Read more.
Disaster risk reduction (DRR) has become an important element of donor policy, because numerous governments have expressed their commitment to helping countries vulnerable to natural hazards by mainstreaming DRR into their development programs. Meanwhile, countries that are considered fragile, as well as conflict-affected states, have faced a high risk of disasters brought on by natural hazards. However, there has been little research that addresses the complex relationship between disasters, conflict, and fragility in the context of development cooperation. Against this backdrop, this study analyzed the determinants of DRR aid allocation from Japan and South Korea—two East Asian countries that have shown a strong commitment to disaster resilience and peacebuilding—to investigate whether they are responsive to countries experiencing the combined risks of disasters and conflicts and/or fragility. Despite the vulnerable countries being in the most need, the study found that both Japan and Korea’s aid allocation has not been influenced much by the concurrence of disasters and conflict. Rather, it has been more driven by the level of a country’s climate vulnerability than the level of a country’s fragility. This suggests that developing countries facing multiple risks and challenges are at a major disadvantage in terms of the responsiveness of donors toward their needs and vulnerability. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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18 pages, 5687 KiB  
Article
The Effect of Land Use and Land Cover Changes on Flood Occurrence in Teunom Watershed, Aceh Jaya
by Sugianto Sugianto, Anwar Deli, Edy Miswar, Muhammad Rusdi and Muhammad Irham
Land 2022, 11(8), 1271; https://doi.org/10.3390/land11081271 - 08 Aug 2022
Cited by 31 | Viewed by 6956
Abstract
The change in land use and land cover in upstream watersheds will change the features of drainage systems such that they will impact surface overflow and affect the infiltration capacity of a land surface, which is one of the factors that contributes to [...] Read more.
The change in land use and land cover in upstream watersheds will change the features of drainage systems such that they will impact surface overflow and affect the infiltration capacity of a land surface, which is one of the factors that contributes to flooding. The key objective of this study is to identify vulnerable areas of flooding and to assess the causes of flooding using ground-based measurement, remote sensing data, and GIS-based flood risk mapping approaches for the flood hazard mapping of the Teunom watershed. The purposes of this investigation were to: (1) examine the level and characteristics of land use and land cover changes that occurred in the area between 2009 and 2019; (2) determine the impact of land use and land cover changes on the water overflow and infiltration capacity; and (3) produce flood risk maps for the Teunom sub-district. Landsat imagery of 2009, 2013, and 2019; slope maps; and field measurement soil characteristics data were utilized for this study. The results show a significant increase in the use of residential land, open land, rice fields, and wetlands (water bodies) and different infiltration rates that contribute to the variation of flood zone hazards. The Teunom watershed has a high and very high risk of ~11.98% of the total area, a moderate risk of 56.24%, and a low and very low risk of ~31.79%. The Teunom watershed generally has a high flood risk, with a total of ~68% of the area (moderate to very high risk). There was a substantial reduction in forest land, agricultural land, and shrubs from 2009 to 2019. Therefore, the segmentation of flood-risk zones is essential for preparation in the region. The study offers basic information about flood hazard areas for central governments, local governments, NGOs, and communities to intervene in preparedness, responses, and flood mitigation and recovery processes, respectively. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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17 pages, 3822 KiB  
Article
Study on the Deformation of Filling Bodies in a Loess Mountainous Area Based on InSAR and Monitoring Equipment
by Yuming Wu and Hengxing Lan
Land 2022, 11(8), 1263; https://doi.org/10.3390/land11081263 - 07 Aug 2022
Cited by 2 | Viewed by 1428
Abstract
Several land-creation projects, such as the Lanzhou New Area (LNA), have been undertaken in China as part of the Belt and Road Initiative to bring more living space to the local people in loess areas. However, undisturbed loess and remolded loess have different [...] Read more.
Several land-creation projects, such as the Lanzhou New Area (LNA), have been undertaken in China as part of the Belt and Road Initiative to bring more living space to the local people in loess areas. However, undisturbed loess and remolded loess have different mechanical characteristics, which may influence the stability of the filling process. Therefore, we monitored the deformation through InSAR and field monitoring to investigate the deformation characteristics and their causes. We obtained the horizontal and vertical displacements, internal deformation, water content, and pressure, according to the air–space–ground integrated monitoring technique. The results show that stress and deformation increase rapidly during construction. Deformation in different places is different during the winter: (1) for vertical displacement, uplift is present in the cut area, settlement is present in the fill area, and heterogeneity is evident in other areas; (2) for horizontal displacement, the expansion state is present in the filling area and the compression state is present at the boundary. Laboratory tests show that the difference in soil compression properties is one of the reasons for these deformation characteristics. Additionally, the difference in volumetric water content and permeability coefficient may trigger different mechanical properties on both sides of the boundary. All the evidence indicates that the boundary region is critical for filling projects. It is also necessary to install monitoring equipment to observe deformation. When abnormal deformations appear, we should take measures to control them. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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22 pages, 5349 KiB  
Article
An Efficient User-Friendly Integration Tool for Landslide Susceptibility Mapping Based on Support Vector Machines: SVM-LSM Toolbox
by Wubiao Huang, Mingtao Ding, Zhenhong Li, Jianqi Zhuang, Jing Yang, Xinlong Li, Ling’en Meng, Hongyu Zhang and Yue Dong
Remote Sens. 2022, 14(14), 3408; https://doi.org/10.3390/rs14143408 - 15 Jul 2022
Cited by 15 | Viewed by 2770
Abstract
Landslide susceptibility mapping (LSM) is an important element of landslide risk assessment, but the process often needs to span multiple platforms and the operation process is complex. This paper develops an efficient user-friendly toolbox including the whole process of LSM, known as the [...] Read more.
Landslide susceptibility mapping (LSM) is an important element of landslide risk assessment, but the process often needs to span multiple platforms and the operation process is complex. This paper develops an efficient user-friendly toolbox including the whole process of LSM, known as the SVM-LSM toolbox. The toolbox realizes landslide susceptibility mapping based on a support vector machine (SVM), which can be integrated into the ArcGIS or ArcGIS Pro platform. The toolbox includes three sub-toolboxes, namely: (1) influence factor production, (2) factor selection and dataset production, and (3) model training and prediction. Influence factor production provides automatic calculation of DEM-related topographic factors, converts line vector data to continuous raster factors, and performs rainfall data processing. Factor selection uses the Pearson correlation coefficient (PCC) to calculate the correlations between factors, and the information gain ratio (IGR) to calculate the contributions of different factors to landslide occurrence. Dataset sample production includes the automatic generation of non-landslide data, data sample production and dataset split. The accuracy, precision, recall, F1 value, receiver operating characteristic (ROC) and area under curve (AUC) are used to evaluate the prediction ability of the model. In addition, two methods—single processing and multiprocessing—are used to generate LSM. The prediction efficiency of multiprocessing is much higher than that of the single process. In order to verify the performance and accuracy of the toolbox, Wuqi County, Yan’an City, Shaanxi Province was selected as the test area to generate LSM. The results show that the AUC value of the model is 0.8107. At the same time, the multiprocessing prediction tool improves the efficiency of the susceptibility prediction process by about 60%. The experimental results confirm the accuracy and practicability of the proposed toolbox in LSM. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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