Natural Hazards and Disaster Risks Reduction

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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

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
GeoHazards geohazards	-	2.6	2020	19 Days	CHF 1000
Land land	3.2	4.9	2012	16.9 Days	CHF 2600
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400
Water water	3.0	5.8	2009	17.5 Days	CHF 2600

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16 pages, 7349 KiB  

Open AccessArticle

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 - 6 Nov 2023

Cited by 2 | Viewed by 2489

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  

Open AccessArticle

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

Cited by 1 | Viewed by 1854

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  

Open AccessArticle

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 - 3 Oct 2023

Cited by 3 | Viewed by 2497

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  

Open AccessArticle

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 4 | Viewed by 1891

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  

Open AccessArticle

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 - 4 Sep 2023

Cited by 1 | Viewed by 1905

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  

Open AccessArticle

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 963

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  

Open AccessArticle

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

Cited by 2 | Viewed by 1880

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  

Open AccessArticle

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

Cited by 1 | Viewed by 1461

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  

Open AccessArticle

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 4 | Viewed by 2006

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  

Open AccessArticle

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 9 | Viewed by 1826

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  

Open AccessArticle

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

Cited by 2 | Viewed by 2217

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  

Open AccessArticle

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 8 | Viewed by 2324

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  

Open AccessArticle

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 17 | Viewed by 2081

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  

Open AccessFeature PaperEditor’s ChoiceArticle

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 - 5 Jun 2023

Cited by 1 | Viewed by 2631

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  

Open AccessArticle

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 - 2 Jun 2023

Cited by 3 | Viewed by 1409

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  

Open AccessArticle

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 15 | Viewed by 2205

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  

Open AccessArticle

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 3 | Viewed by 2408

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  

Open AccessArticle

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 2291

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  

Open AccessArticle

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

Cited by 1 | Viewed by 1908

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  

Open AccessArticle

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 4 | Viewed by 2029

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  

Open AccessTechnical 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 - 8 May 2023

Cited by 2 | Viewed by 1929

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  

Open AccessArticle

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 3267

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  

Open AccessArticle

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

Cited by 3 | Viewed by 2265

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  

Open AccessArticle

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 14 | Viewed by 3521

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  

Open AccessReview

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

Cited by 3 | Viewed by 2645

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  

Open AccessArticle

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 6 | Viewed by 2861

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  

Open AccessArticle

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 - 7 Mar 2023

Cited by 5 | Viewed by 3066

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  

Open AccessArticle

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 - 6 Mar 2023

Cited by 2 | Viewed by 2682

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  

Open AccessArticle

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

Cited by 4 | Viewed by 1769

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  

Open AccessArticle

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 - 7 Feb 2023

Cited by 2 | Viewed by 2656

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  

Open AccessArticle

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 - 6 Feb 2023

Cited by 1 | Viewed by 1731

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  

Open AccessArticle

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 - 3 Jan 2023

Cited by 5 | Viewed by 2439

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  

Open AccessArticle

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 2563

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  

Open AccessArticle

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 - 9 Dec 2022

Cited by 3 | Viewed by 2368

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  

Open AccessArticle

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

Cited by 3 | Viewed by 1877

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  

Open AccessArticle

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 - 8 Nov 2022

Cited by 2 | Viewed by 2151

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  

Open AccessArticle

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 7 | Viewed by 2204

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  

Open AccessFeature PaperArticle

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 4 | Viewed by 2998

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  

Open AccessArticle

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 3 | Viewed by 2196

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  

Open AccessArticle

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 16 | Viewed by 4207

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  

Open AccessArticle

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 - 8 Sep 2022

Cited by 10 | Viewed by 2588

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  

Open AccessFeature PaperArticle

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 - 1 Sep 2022

Cited by 2 | Viewed by 2828

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  

Open AccessArticle

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 4 | Viewed by 2458

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  

Open AccessArticle

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 - 8 Aug 2022

Cited by 72 | Viewed by 11235

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  

Open AccessArticle

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 - 7 Aug 2022

Cited by 5 | Viewed by 1936

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  

Open AccessArticle

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 25 | Viewed by 4043

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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24 pages, 6921 KiB  

Open AccessArticle

Multi-Hazard Emergency Response for Geological Hazards Amid the Evolving COVID-19 Pandemic: Good Practices and Lessons Learned from Earthquake Disaster Management in Greece

by Spyridon Mavroulis, Maria Mavrouli, Asimina Kourou, Thekla Thoma and Efthymis Lekkas

Sustainability 2022, 14(14), 8486; https://doi.org/10.3390/su14148486 - 11 Jul 2022

Cited by 11 | Viewed by 3523

Abstract

Since the beginning of 2020, the COVID-19 pandemic has caused unprecedented global disruption with considerable impact on human activities. However, natural hazards and related disasters do not wait for SARS-CoV-2 to vanish, resulting in the emergence of many conflicting issues between earthquake emergency [...] Read more.

Since the beginning of 2020, the COVID-19 pandemic has caused unprecedented global disruption with considerable impact on human activities. However, natural hazards and related disasters do not wait for SARS-CoV-2 to vanish, resulting in the emergence of many conflicting issues between earthquake emergency response actions and pandemic mitigation measures. In this study, these conflicting issues are highlighted through the cases of four earthquakes that struck Greece at different phases of the pandemic. The earthquake effects on the local population and on the natural environment and building stock form ideal conditions for local COVID-19 outbreaks in earthquake-affected communities. However, the implementation of response actions and mitigation measures in light of a multi-hazard approach to disaster risk reduction and disaster risk management has led not only to the maintenance of pre-existing low viral load in the earthquake-affected areas, but in some cases even to their reduction. This fact suggests that the applied measures are good practice and an important lesson for improving disaster management in the future. Taking into account the aforementioned, a series of actions are proposed for the effective management of the impact of a geological hazard in the midst of an evolving biological hazard with epidemiological characteristics similar to the COVID-19 pandemic. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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22 pages, 6972 KiB  

Open AccessArticle

An Assessment of Social Resilience against Natural Hazards through Multi-Criteria Decision Making in Geographical Setting: A Case Study of Sarpol-e Zahab, Iran

by Davoud Shahpari Sani, Mohammad Taghi Heidari, Hossein Tahmasebi Mogaddam, Saman Nadizadeh Shorabeh, Saman Yousefvand, Anahita Karmpour and Jamal Jokar Arsanjani

Sustainability 2022, 14(14), 8304; https://doi.org/10.3390/su14148304 - 7 Jul 2022

Cited by 11 | Viewed by 3407

Abstract

The aim of this study was to propose an approach for assessing the social resilience of citizens, using a locative multi-criteria decision-making (MCDM) model for an exemplary case study of Sarpol-e Zahab city, Iran. To do so, a set of 10 variables and [...] Read more.

The aim of this study was to propose an approach for assessing the social resilience of citizens, using a locative multi-criteria decision-making (MCDM) model for an exemplary case study of Sarpol-e Zahab city, Iran. To do so, a set of 10 variables and 28 criteria affecting social resilience were used and their weights were measured using the Analytical Hierarchy Process, which was then inserted into the Weighted Linear Combination (WLC) model for mapping social resilience across our case study. Finally, the accuracy of the generated social resilience map, the correlation coefficient between the results of the WLC model and the accuracy level of the social resilience map were assessed, based on in-situ data collection after conducting a survey. The outcomes revealed that more than 60% of the study area falls into the low social resilience category, categorized as the most vulnerable areas. The correlation coefficient between the WLC model and the social resilience level was 79%, which proves the acceptability of our approach for mapping social resilience of citizens across cities vulnerable to diverse risks. The proposed methodological approach, which focuses on chosen data and presented discussions, borne from this study can be beneficial to a wide range of stakeholders and decision makers in prioritizing resources and efforts to benefit more vulnerable areas and inhabitants. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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21 pages, 2877 KiB  

Open AccessEditor’s ChoiceArticle

Data-Driven Community Flood Resilience Prediction

by Moustafa Naiem Abdel-Mooty, Wael El-Dakhakhni and Paulin Coulibaly

Water 2022, 14(13), 2120; https://doi.org/10.3390/w14132120 - 2 Jul 2022

Cited by 9 | Viewed by 4573

Abstract

Climate change and the development of urban centers within flood-prone areas have significantly increased flood-related disasters worldwide. However, most flood risk categorization and prediction efforts have been focused on the hydrologic features of flood hazards, often not considering subsequent long-term losses and recovery [...] Read more.

Climate change and the development of urban centers within flood-prone areas have significantly increased flood-related disasters worldwide. However, most flood risk categorization and prediction efforts have been focused on the hydrologic features of flood hazards, often not considering subsequent long-term losses and recovery trajectories (i.e., community’s flood resilience). In this study, a two-stage Machine Learning (ML)-based framework is developed to accurately categorize and predict communities’ flood resilience and their response to future flood hazards. This framework is a step towards developing comprehensive, proactive flood disaster management planning to further ensure functioning urban centers and mitigate the risk of future catastrophic flood events. In this framework, resilience indices are synthesized considering resilience goals (i.e., robustness and rapidity) using unsupervised ML, coupled with climate information, to develop a supervised ML prediction algorithm. To showcase the utility of the framework, it was applied on historical flood disaster records collected by the US National Weather Services. These disaster records were subsequently used to develop the resilience indices, which were then coupled with the associated historical climate data, resulting in high-accuracy predictions and, thus, utility in flood resilience management studies. To further demonstrate the utilization of the framework, a spatial analysis was developed to quantify communities’ flood resilience and vulnerability across the selected spatial domain. The framework presented in this study is employable in climate studies and patio-temporal vulnerability identification. Such a framework can also empower decision makers to develop effective data-driven climate resilience strategies. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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20 pages, 9924 KiB  

Open AccessArticle

Combined ERT and GPR Data for Subsurface Characterization of Weathered Hilly Slope: A Case Study in Zhejiang Province, Southeast China

by Yajing Yan, Yongshuai Yan, Guizhang Zhao, Yanfang Zhou and Zhoufeng Wang

Sustainability 2022, 14(13), 7616; https://doi.org/10.3390/su14137616 - 22 Jun 2022

Cited by 7 | Viewed by 2429

Abstract

Rain-triggered landslides frequently threaten public safety, infrastructure, and the economy during typhoon seasons in Zhejiang Province. Landslides are complex structural systems, and the subsurface features play a significant role in their stability. Their early identification and the evaluation of potential danger in terms [...] Read more.

Rain-triggered landslides frequently threaten public safety, infrastructure, and the economy during typhoon seasons in Zhejiang Province. Landslides are complex structural systems, and the subsurface features play a significant role in their stability. Their early identification and the evaluation of potential danger in terms of the rupture surface and unstable body are essential for geohazard prevention and protection. However, the information about the subsurface acquired by conventional exploration approaches is generally limited to sparse data. This paper describes a joint application of ground-penetrating radar (GPR) with a 100 MHz antenna and the electrical resistivity tomography (ERT) method with the Wenner configuration to identify the stratum structure and delineate the potentially unstable body of a clay-rich slope, the results of which were further verified using borehole data and field observation. The acquired results from the GPR and ERT surveys, consistent with each other, indicate two stratigraphic layers comprising silty clay and silty mudstone. Moreover, the potential rupture zone very likely exists in the highly weathered mudstone in the depth range of 3–7 m, and the average depth is 5 m. In addition, the thickness of the unstable mass is greater on the east and crest parts of the slope. Conclusively, the optimum combination of ERT and GPR is reliable for conducting rapid and effective delineation of subsurface characteristics of clayey slopes for risk assessment and mitigation during the typhoon season. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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25 pages, 9635 KiB  

Open AccessArticle

Multi-Hazard Meteorological Disaster Risk Assessment for Agriculture Based on Historical Disaster Data in Jilin Province, China

by Jiawang Zhang, Jianguo Wang, Shengbo Chen, Siqi Tang and Wutao Zhao

Sustainability 2022, 14(12), 7482; https://doi.org/10.3390/su14127482 - 19 Jun 2022

Cited by 22 | Viewed by 4386

Abstract

The impact of global climate change is gradually intensifying, and the frequent occurrence of meteorological disasters poses a serious challenge to crop production. Analyzing and evaluating agricultural multi-hazard meteorological disaster risks based on historical disaster data and a summary of disaster occurrences and [...] Read more.

The impact of global climate change is gradually intensifying, and the frequent occurrence of meteorological disasters poses a serious challenge to crop production. Analyzing and evaluating agricultural multi-hazard meteorological disaster risks based on historical disaster data and a summary of disaster occurrences and development patterns are important bases for the effective reduction of natural disaster risks and the regulation of agricultural production. This paper explores the technical system of agricultural multi-hazard meteorological disaster risk assessment and establishes a disaster risk assessment model based on the historical disaster data at the regional level from 1978–2020 in the first national comprehensive natural disaster risk census, carrying out multi-hazard meteorological disaster risk assessments in 18 major grain-producing regions in Jilin province. The empirical evidence shows: (1) drought and flood disasters are the key disasters for agricultural meteorological disaster prevention in Jilin province. Hotspots of drought and flood disasters are widely distributed in the study area, while hail and typhoons are mainly concentrated in the eastern region with a certain regionality. (2) The risk values of the four major meteorological disasters all decreased with the increase of the disaster index. Under the same disaster index, the disaster risk of various disasters in the main grain-producing areas is as follows: drought > flood > typhoon > hail. Under different disaster indices, Jiutai, Nongan, Yitong, Tongyu, and other places all presented high and medium–high risk levels. (3) From the spatial evolution trend, along with the rising disaster index, the risk of multi-hazard meteorological hazards is spatially oriented in a southeastern direction, and the risk level of multi-hazard meteorological hazards in the central part of the study area decreases gradually along with the increasing damage index. In addition, regional agricultural multi-hazard meteorological disaster risk reduction recommendations are made in three aspects: institutional construction, management model, and reduction capacity. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 5913 KiB  

Open AccessArticle

The Outburst of a Lake and Its Impacts on Redistribution of Surface Water Bodies in High-Altitude Permafrost Region

by Zekun Ding, Fujun Niu, Guoyu Li, Yanhu Mu, Mingtang Chai and Pengfei He

Remote Sens. 2022, 14(12), 2918; https://doi.org/10.3390/rs14122918 - 18 Jun 2022

Cited by 9 | Viewed by 2392

Abstract

The lakes distributed in permafrost areas on the Tibetan Plateau (TP) have been experiencing significant changes during the past few decades as a result of the climate warming and regional wetting. In September 2011, an outburst occurred on an endorheic lake (Zonag Lake) [...] Read more.

The lakes distributed in permafrost areas on the Tibetan Plateau (TP) have been experiencing significant changes during the past few decades as a result of the climate warming and regional wetting. In September 2011, an outburst occurred on an endorheic lake (Zonag Lake) in the interior of the TP, which caused the spatial expansion of three downstream lakes (Kusai Lake, Haidingnor Lake and Salt Lake) and modified the four independent lake catchments to one basin. In this study, we investigate the changes in surficial areas and water volumes of the outburst lake and related downstream water bodies 10 years after the outburst. Based on the meteorological and satellite data, the reasons for the expansion of downstream lakes were analyzed. Additionally, the importance of the permafrost layer in determining hydrological process on the TP and the influence of from lake expansion on engineering infrastructures were discussed. The results in this study showed the downstream lakes increased both in area and volume after the outburst of the headwater. Meanwhile, we hope to provide a reference about surface water changes and permafrost degradation for the management of lake overflow and flood on the TP in the background of climate warming and wetting. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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26 pages, 12995 KiB  

Open AccessArticle

Landslide Deformation Extraction from Terrestrial Laser Scanning Data with Weighted Least Squares Regularization Iteration Solution

by Lidu Zhao, Xiaping Ma, Zhongfu Xiang, Shuangcheng Zhang, Chuan Hu, Yin Zhou and Guicheng Chen

Remote Sens. 2022, 14(12), 2897; https://doi.org/10.3390/rs14122897 - 17 Jun 2022

Cited by 10 | Viewed by 2946

Abstract

The extraction of landslide deformation using terrestrial laser scanning (TLS) has many important applications. The landslide deformation can be extracted based on a digital terrain model (DTM). However, such methods usually suffer from the ill-posed problem of a multiplicative error model as illustrated [...] Read more.

The extraction of landslide deformation using terrestrial laser scanning (TLS) has many important applications. The landslide deformation can be extracted based on a digital terrain model (DTM). However, such methods usually suffer from the ill-posed problem of a multiplicative error model as illustrated in previous studies. Moreover, the edge drift of commonly used spherical targets for point cloud registration (PCR) is ignored in the existing method, which will result in the unstable precision of the PCR. In response to these problems, we propose a method for extracting landslide deformations from TLS data. To archive the PCR of different period point clouds, a new triangular pyramid target is designed to eliminate the edge drift. If a fixed target is inconvenient, we also propose a PCR method based on total station orientation. Then, the use of the Tikhonov regularization method to derive the weighted least squares regularization solution is presented. Finally, the landslide deformation is extracted by DTM deference. The experiments are conducted on two datasets with more than 1.5 billion points. The first dataset takes Lashagou NO. 3 landslide in Gansu Province, China, as the research object; the point cloud data were collected on 26 February 2021 and 3 May 2021. The registration accuracy was 0.003 m based on the permanent triangular pyramid target and 0.005 m based on the total station orientation. The landslide deforms within 3 cm due to the ablation of the frozen soil. The second dataset is TLS data from the Lihua landslide in Chongqing, China, collected on 20 April 2021 and 1 May 2021. The overall deformation of the Lihua landslide is small, with a maximum value of 0.011 m. The result shows that the proposed method achieves a better performance than previous sphere-based registration and that the weighted least square regularization iterative solution can effectively reduce the ill-condition of the model. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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25 pages, 6965 KiB  

Open AccessArticle

Flash Flood Risk Assessment and Mitigation in Digital-Era Governance Using Unmanned Aerial Vehicle and GIS Spatial Analyses Case Study: Small River Basins

by Ștefan Bilașco, Gheorghe-Gavrilă Hognogi, Sanda Roșca, Ana-Maria Pop, Vescan Iuliu, Ioan Fodorean, Alexandra-Camelia Marian-Potra and Paul Sestras

Remote Sens. 2022, 14(10), 2481; https://doi.org/10.3390/rs14102481 - 22 May 2022

Cited by 25 | Viewed by 5181

Abstract

Watercourses act like a magnet for human communities and were always a deciding factor when choosing settlements. The reverse of these services is a potential hazard in the form of flash flooding, for which human society has various management strategies. These strategies prove [...] Read more.

Watercourses act like a magnet for human communities and were always a deciding factor when choosing settlements. The reverse of these services is a potential hazard in the form of flash flooding, for which human society has various management strategies. These strategies prove to be increasingly necessary in the context of increased anthropic pressure on the floodable areas. One of these strategies, Strategic Flood Management (SFM), a continuous cycle of planning, acting, monitoring, reviewing and adapting, seems to have better chances to succeed than other previous strategies, in the context of the Digital-Era Governance (DEG). These derive, among others, from the technological and methodological advantages of DEG. Geographic Information Systems (GIS) and Unmanned Aerial Vehicles (UAV) stand out among the most revolutionary tools for data acquisition and processing of data in the last decade, both in qualitative and quantitative terms. In this context, this study presents a hybrid risk assessment methodology for buildings in case of floods. The methodology is based on detailed information on the terrestrial surface—digital surface model (DSM) and measurements of the last historical flash flood level (occurred on 20 June 2012)—that enabled post-flood peak discharge estimation. Based on this methodology, two other parameters were calculated together with water height (depth): shear stress and velocity. These calculations enabled the modelling of the hazard and risk map, taking into account the objective value of buildings. The two components were integrated in a portal available for the authorities and inhabitants. Both the methodology and the portal are perfectible, but the value of this material consists of the detailing and replicability potential of the data that can be made available to administration and local community. Conceptually, the following are relevant (a) the framing of the SFM concept in the DEG framework and (b) the possibility to highlight the involvement and contribution of the citizens in mapping the risks and their adaptation to climate changes. The subsequent version of the portal is thus improved by further contributions and the participatory approach of the citizens. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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21 pages, 5985 KiB  

Open AccessArticle

Calculating Economic Flood Damage through Microscale Risk Maps and Data Generalization: A Pilot Study in Southern Italy

by Gianna Ida Festa, Luigi Guerriero, Mariano Focareta, Giuseppe Meoli, Silvana Revellino, Francesco Maria Guadagno and Paola Revellino

Sustainability 2022, 14(10), 6286; https://doi.org/10.3390/su14106286 - 21 May 2022

Cited by 5 | Viewed by 2879

Abstract

In recent decades, floods have caused significant loss of human life as well as interruptions in economic and social activities in affected areas. In order to identify effective flood mitigation measures and to suggest actions to be taken before and during flooding, microscale [...] Read more.

In recent decades, floods have caused significant loss of human life as well as interruptions in economic and social activities in affected areas. In order to identify effective flood mitigation measures and to suggest actions to be taken before and during flooding, microscale risk estimation methods are increasingly applied. In this context, an implemented methodology for microscale flood risk evaluation is presented, which considers direct and tangible damage as a function of hydrometric height and allows for quick estimates of the damage level caused by alluvial events. The method has been applied and tested on businesses and residential buildings of the town of Benevento (southern Italy), which has been hit by destructive floods several times in the past; the most recent flooding occurred in October 2015. The simplified methodology tries to overcome the limitation of the original method—the huge amounts of input data—by applying a simplified procedure in defining the data of the physical features of buildings (e.g., the number of floors, typology, and presence of a basement). Data collection for each building feature was initially carried out through careful field surveys (FAM, field analysis method) and subsequently obtained through generalization of data (DGM, data generalization method). The basic method (FAM) allows for estimating in great detail the potential losses for representative building categories in an urban context and involves a higher degree of resolution, but it is time-consuming; the simplified method (DGM) produces a damage value in a shorter time. By comparison, the two criteria show very similar results and minimal differences, making generalized data acquisition most efficient. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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25 pages, 13377 KiB  

Open AccessArticle

Impact of Urbanization on Seismic Risk: A Study Based on Remote Sensing Data

by Liqiang An and Jingfa Zhang

Sustainability 2022, 14(10), 6132; https://doi.org/10.3390/su14106132 - 18 May 2022

Cited by 3 | Viewed by 3192

Abstract

The management of seismic risk is an important aspect of social development. However, urbanization has led to an increase in disaster-bearing bodies, making it more difficult to reduce seismic risk. To understand the changes in seismic risk associated with urbanization and then adjust [...] Read more.

The management of seismic risk is an important aspect of social development. However, urbanization has led to an increase in disaster-bearing bodies, making it more difficult to reduce seismic risk. To understand the changes in seismic risk associated with urbanization and then adjust the risk management strategy, remote-sensing technology is necessary. By identifying the types of earthquake-bearing bodies, it is possible to estimate the seismic risk and then determine the changes. For this purpose, this study proposes a set of algorithms that combine deep-learning models with object-oriented image classification and extract building information using multisource remote sensing data. Following this, the area of the building is estimated, the vulnerability is determined, and, lastly, the economic and social impacts of an earthquake are determined based on the corresponding ground motion level and fragility function. Our study contributes to the understanding of changes in seismic risk caused by urbanization processes and offers a practical reference for updating seismic risk management, as well as a methodological framework to evaluate the effectiveness of seismic policies. Experimental results indicate that the proposed model is capable of effectively capturing buildings’ information. Through verification, the overall accuracy of the classification of vulnerability types reaches 86.77%. Furthermore, this study calculates social and economic losses of the core area of Tianjin Baodi District in 2011, 2012, 2014, 2016, 2018, 2020, and 2021, obtaining changes in seismic risk in the study area. The result shows that for rare earthquakes at night, although the death rate decreased from 2.29% to 0.66%, the possible death toll seems unchanged, due to the increase in population. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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21 pages, 10752 KiB  

Open AccessArticle

Improved Shallow Landslide Susceptibility Prediction Based on Statistics and Ensemble Learning

by Zhu Liang, Wei Liu, Weiping Peng, Lingwei Chen and Changming Wang

Sustainability 2022, 14(10), 6110; https://doi.org/10.3390/su14106110 - 18 May 2022

Cited by 5 | Viewed by 2530

Abstract

Rainfall-induced landslides bring great damage to human life in mountain areas. Landslide susceptibility assessment (LSA) as an essential step toward landslide prevention has attacked a considerate focus for years. However, defining a reliable or accurate susceptibility model remains a challenge although various methods [...] Read more.

Rainfall-induced landslides bring great damage to human life in mountain areas. Landslide susceptibility assessment (LSA) as an essential step toward landslide prevention has attacked a considerate focus for years. However, defining a reliable or accurate susceptibility model remains a challenge although various methods have been applied. The main purpose of this paper is to explore a comprehensive model with high reliability, accuracy, and intelligibility in LSA by combing statistical methods and ensemble learning techniques. Miyun country in Beijing is selected as the study area. Firstly, the dataset containing 370 landslide locations inventories and 13 conditioning factors were collected and non-landslide samples were prepared by clustering analysis. Secondly, random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting decision tree (Ada-DT) were selected as base learners for the Stacking ensemble method, and these methods were evaluated using measures like area under the curve (AUC). Finally, the Gini index and frequent ratio (FR) were combined to analyze the major conditioning factors. The results indicated that the performance of the Stacking method was enhanced with an AUC value of 0.944 while the basic classifiers also performed well with 0.906, 0.910, and 0.917 for RF, GBDT, and Ada-DT, respectively. Regions with a distance to a stream less than 2000 m, a distance to a road less than 3000 m, and elevation less than 600 m were susceptible to the landslide hazard. The conclusion demonstrates that the performance of LSA desires enhancement and the reliability and intelligibility of a model can be improved by combining binary and multivariate statistical methods. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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18 pages, 6415 KiB  

Open AccessArticle

Pre-Seismic Temporal Integrated Anomalies from Multiparametric Remote Sensing Data

by Zhonghu Jiao and Xinjian Shan

Remote Sens. 2022, 14(10), 2343; https://doi.org/10.3390/rs14102343 - 12 May 2022

Cited by 17 | Viewed by 2531

Abstract

Pre-seismic anomalies have the potential to indicate imminent strong earthquakes in the short to medium terms. However, an improved understanding of the statistical significance between anomalies and earthquakes is required to develop operational forecasting systems. We developed a temporal integrated anomaly (TIA) method [...] Read more.

Pre-seismic anomalies have the potential to indicate imminent strong earthquakes in the short to medium terms. However, an improved understanding of the statistical significance between anomalies and earthquakes is required to develop operational forecasting systems. We developed a temporal integrated anomaly (TIA) method to obtain the temporal trends of multiparametric anomalies derived from the Atmospheric Infrared Sounder (AIRS) product before earthquakes. A total of 169 global earthquakes that occurred from 2006 to 2020 and had magnitudes of ≥7.0 and focal depths of ≤70 km were used to test this new method in a retrospective manner. In addition, 169 synthetic earthquakes were randomly generated to demonstrate the suppression capacity of the TIA method for false alarms. We identified four different TIA trends according to the temporal characteristics of positive and negative TIAs. Long-term correlation analyses show that the recognition ability was 12.4–28.4% higher for true earthquakes than for synthetic earthquakes (i.e., higher than that of a random guess). Incorporating 2–5 kinds of TIAs offered the best chance of recognizing imminent shocks, highlighting the importance of multiparameter anomalies. Although the TIA trend characteristics before the earthquakes were not unique, we identified certain unexplained pre-seismic phenomena within the remote sensing data. The results provide new insight into the relationships between pre-seismic anomalies and earthquakes; moreover, the recognition ability of the proposed approach exceeds that of random guessing. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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21 pages, 5575 KiB  

Open AccessArticle

A Multimodal Data Analysis Approach to Social Media during Natural Disasters

by Mengna Zhang, Qisong Huang and Hua Liu

Sustainability 2022, 14(9), 5536; https://doi.org/10.3390/su14095536 - 5 May 2022

Cited by 9 | Viewed by 3638

Abstract

During natural disasters, social media can provide real time or rapid disaster, perception information to help government managers carry out disaster response efforts efficiently. Therefore, it is of great significance to mine social media information accurately. In contrast to previous studies, this study [...] Read more.

During natural disasters, social media can provide real time or rapid disaster, perception information to help government managers carry out disaster response efforts efficiently. Therefore, it is of great significance to mine social media information accurately. In contrast to previous studies, this study proposes a multimodal data classification model for mining social media information. Using the model, the study employs Late Dirichlet Allocation (LDA) to identify subject information from multimodal data, then, the multimodal data is analyzed by bidirectional encoder representation from transformers (Bert) and visual geometry group 16 (Vgg-16). Text and image data are classified separately, resulting in real mining of topic information during disasters. This study uses Weibo data during the 2021 Henan heavy storm as the research object. Comparing the data with previous experiment results, this study proposes a model that can classify natural disaster topics more accurately. The accuracy of this study is 0.93. Compared with a topic-based event classification model KGE-MMSLDA, the accuracy of this study is improved by 12%. This study results in a real-time understanding of different themed natural disasters to help make informed decisions. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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13 pages, 2570 KiB  

Open AccessArticle

Large Scale Laboratory Experiment: The Impact of the Hydraulic Characteristics of Flood Waves Caused by Gradual Levee Failure on Inundation Areas

by Kwang Seok Yoon, Khawar Rehman, Hyung Ju Yoo, Seung Oh Lee and Seung Ho Hong

Water 2022, 14(9), 1446; https://doi.org/10.3390/w14091446 - 30 Apr 2022

Cited by 3 | Viewed by 2474

Abstract

As a levee failure and the consequent flooding cause significant financial losses and sometimes human casualties, they have led to considerable concern among city officials. Therefore, researchers have devoted considerable effort to investigating the hydraulic characteristics of sudden transient flow in the form [...] Read more.

As a levee failure and the consequent flooding cause significant financial losses and sometimes human casualties, they have led to considerable concern among city officials. Therefore, researchers have devoted considerable effort to investigating the hydraulic characteristics of sudden transient flow in the form of propagated waves to inundation areas during a levee and/or dam failure. A large number of studies, however, have mostly focused on simple one-dimensional cases investigated numerically and/or experimentally, and thus, important hydraulic characteristics, particularly near the failure zone, have not been adequately captured because of three-dimensional complexities. Taking these complexities into consideration, this study conducts a large-scale experiment to examine the characteristics of wave propagation in an open area caused by a gradual levee failure. From the experimental observations, this study provides the propagation speed of a wave front and suggests a formula for the maximum flood depth corresponding to the peak flood wave in the inundation area. We expect the findings to provide hydraulic engineers and scientists with fundamental insights into transient flow during a gradual levee failure. By contributing to our theoretical understanding, the measurements can also be used as validation tools for future numerical simulation and are likely to contribute to the establishment of emergency action plans that can help city officials cope with flood inundation. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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30 pages, 12163 KiB  

Open AccessReview

Catastrophic Floods in Large River Basins: Surface Water and Groundwater Interaction under Dynamic Complex Natural Processes–Forecasting and Presentation of Flood Consequences

by Tatiana Trifonova, Mileta Arakelian, Dmitriy Bukharov, Sergei Abrakhin, Svetlana Abrakhina and Sergei Arakelian

Water 2022, 14(9), 1405; https://doi.org/10.3390/w14091405 - 27 Apr 2022

Cited by 1 | Viewed by 2266

Abstract

A unique approach has been developed for explaining and forecasting the processes of flood and/or mudflow (debris) formation and their spread along riverbeds in mountainous areas, caused by flash increases in the water masses involved (considerably increasing in their expected level because of [...] Read more.

A unique approach has been developed for explaining and forecasting the processes of flood and/or mudflow (debris) formation and their spread along riverbeds in mountainous areas, caused by flash increases in the water masses involved (considerably increasing in their expected level because of precipitation intensity) due to groundwater contributions. Three-dimensional crack-nets within the confines of unified rivershed basins in mountain massifs are a natural transportation system (as determined by some dynamic external stress factors) for groundwater, owing to hydrostatic/hydrodynamic pressure distribution, varied due to different reasons (e.g., earthquakes). This process reveals a wave nature characterized by signs of obvious self-organization, and can be described via the soliton model in nonlinear hydrodynamics on the surface propagation after a local exit of groundwater as the trigger type. This approach (and related concepts) might result in a more reliable forecasting and early warning system in case of natural water hazards/disasters, taking into account a groundwater-dominant role in some cases. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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15 pages, 3237 KiB  

Open AccessArticle

Correlation Dimension in Sumatra Island Based on Active Fault, Earthquake Data, and Estimated Horizontal Crustal Strain to Evaluate Seismic Hazard Functions (SHF)

by Wahyu Triyoso, David P. Sahara, Dina A. Sarsito, Danny H. Natawidjaja and Sigit Sukmono

GeoHazards 2022, 3(2), 227-241; https://doi.org/10.3390/geohazards3020012 - 22 Apr 2022

Cited by 10 | Viewed by 3181

Abstract

This study intends to evaluate the possible correlation between the correlation dimension (D_C) and the seismic moment rate for different late Quaternary active fault data, shallow crustal earthquakes, and GPS on the island of Sumatra Probabilistic Seismic Hazard Analysis (PSHA). The [...] Read more.

This study intends to evaluate the possible correlation between the correlation dimension (D_C) and the seismic moment rate for different late Quaternary active fault data, shallow crustal earthquakes, and GPS on the island of Sumatra Probabilistic Seismic Hazard Analysis (PSHA). The seismicity smoothing was applied to estimate the D_C of active faults (D_F) and earthquake data (D_E) and then to correlate that with the b-value, which will be used to identify seismic hazard functions (SHF) along with the Sumatra Fault Zone (SFZ). The seismicity based on GPS data was calculated by the seismic moment rate that is estimated based on pre-seismic horizontal surface displacement data. The correlation between D_F, D_E, and the b-value was analyzed, and a reasonable correlation between the two seismotectonic parameters, D_F-b, and D_E-b, respectively, could be found. The relatively high D_C coincides with the high seismic moment rate model derived from the pre-seismic GPS data. Furthermore, the SHF curve of total probability of exceedance versus the mean of each observation point’s peak ground acceleration (PGA) shows that the relatively high correlation dimension coincides with the high SHF. The results of this study might be very beneficial for seismic mitigation in the future. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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18 pages, 5827 KiB  

Open AccessArticle

Fast Displacement Estimation of Multiple Close Targets with MIMO Radar and MUSICAPES Method

by Jian Wang, Yuming Wang, Yueli Li and Xiaotao Huang

Remote Sens. 2022, 14(9), 2005; https://doi.org/10.3390/rs14092005 - 21 Apr 2022

Cited by 7 | Viewed by 2101

Abstract

Interferometric radar is a hot research topic in manmade target displacement measuring applications, as it features high precision, a large operation range, and a remote multiple point measuring ability. Most one-dimensional interferometric radars use single-input single-output (SISO) radar architecture to achieve a high [...] Read more.

Interferometric radar is a hot research topic in manmade target displacement measuring applications, as it features high precision, a large operation range, and a remote multiple point measuring ability. Most one-dimensional interferometric radars use single-input single-output (SISO) radar architecture to achieve a high repetition measuring rate of more than 200 Hz; however, it cannot resolve multiple targets with the same radial range but different azimuth angles. This paper presents a multiple-input multiple-output (MIMO) radar that adopts a limited number of antennas (usually tens) to simultaneously improve azimuth resolution and achieve a high repetition measuring rate. A MUSICAPES algorithm is proposed, which is cascades the multiple signal classification (MUSIC) algorithm and the amplitude and phase estimation (APES) filter. The MUSIC algorithm is used to further improve the angular resolution of the small array. The APES is used to precisely recover the phases of the multiple close targets by suppressing their mutual interferences. Simulations and experiments with a millimeter-wave radar validate the performance of the proposed method. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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20 pages, 3037 KiB  

Open AccessArticle

Spatiotemporal Characteristics of Drought and Wet Events and Their Impacts on Agriculture in the Yellow River Basin

by Qingqing Li, Yanping Cao, Shuling Miao and Xinhe Huang

Land 2022, 11(4), 556; https://doi.org/10.3390/land11040556 - 9 Apr 2022

Cited by 12 | Viewed by 2798

Abstract

Droughts and floods have proven to be threats to food security worldwide. This research used the standardized precipitation index (SPI) to examine the spatiotemporal characteristics of drought and wet events from 1961 to 2020 in the Yellow River basin (YRB). Grain yield data [...] Read more.

Droughts and floods have proven to be threats to food security worldwide. This research used the standardized precipitation index (SPI) to examine the spatiotemporal characteristics of drought and wet events from 1961 to 2020 in the Yellow River basin (YRB). Grain yield data were combined to assess how drought and wet frequency have affected the agricultural system. The occurrence frequency of drought was greater than that of wetness in time, drought frequency decreased, and wetness increased. Spatially, the frequency of drought in all provinces except Shanxi was higher than that of wetness. The grain yield per unit area of the YRB was generally highest in Shandong province and lowest in Gansu province. The grain yield per unit area have shown a significant growth trend in the nine provinces of the YRB since 1961. Drought had a negative effect on the grain yield per unit area in each province, while wetness had a positive effect on the grain yield per unit area in all provinces except Shandong. In general, the influence of drought on grain yield per unit area decreased, while the influence of wetness on grain yield per unit area increased. The results indicate that human activities are effective against preventing and controlling drought and wet disasters and can provide a reference for other parts of the world. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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23 pages, 6813 KiB  

Open AccessArticle

Some Considerations for Using Numerical Methods to Simulate Possible Debris Flows: The Case of the 2013 and 2020 Wayao Debris Flows (Sichuan, China)

by Xianzheng Zhang, Chenxiao Tang, Yajie Yu, Chuan Tang, Ning Li, Jiang Xiong and Ming Chen

Water 2022, 14(7), 1050; https://doi.org/10.3390/w14071050 - 27 Mar 2022

Cited by 3 | Viewed by 2995

Abstract

Using a numerical simulation method based on physical equations to obtain the debris flow risk range is important for local-scale debris flow risk assessment. While many debris flow models have been used to reproduce processes after debris flow occurrence, their predictability in potentially [...] Read more.

Using a numerical simulation method based on physical equations to obtain the debris flow risk range is important for local-scale debris flow risk assessment. While many debris flow models have been used to reproduce processes after debris flow occurrence, their predictability in potentially catastrophic debris flow scenarios has mostly not been evaluated in detail. Two single-phase flow models and two two-phase models were used to reproduce the Wayao debris flow event in 2013. Then the Wayao debris flow event in 2020 was predicted by the four models with the same parameters in 2013. The depth distributions of the debris source and deposition fan were mapped by visual interpretation, electric resistivity surveys, field measurements, and unmanned aerial vehicle (UAV) surveys. The digital elevation model (DEM), rainfall data, and other simulation parameters were collected. These models can reproduce the geometry and thickness distribution of the debris flow fan in 2013. However, the predictions of the runout range and the deposition depth are quite different from the actuality in 2020. The performance and usability of these models are compared and discussed. This could provide a reference for selecting physical models to assess debris-flow risk. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 13928 KiB  

Open AccessFeature PaperArticle

Sequence Analysis of Ancient River Blocking Events in SE Tibetan Plateau Using Multidisciplinary Approaches

by Yiwei Zhang, Jianping Chen, Qing Wang, Yongchao Li, Shengyuan Song, Feifan Gu and Chen Cao

Water 2022, 14(6), 968; https://doi.org/10.3390/w14060968 - 18 Mar 2022

Cited by 1 | Viewed by 2623

Abstract

The temporary or permanent river blocking event caused by mass movement usually occurs on steep terrain. With the increase of mountain population and land use pressure and the construction of water conservancy and hydropower projects, river blocking events have gradually attracted people’s attention [...] Read more.

The temporary or permanent river blocking event caused by mass movement usually occurs on steep terrain. With the increase of mountain population and land use pressure and the construction of water conservancy and hydropower projects, river blocking events have gradually attracted people’s attention and understanding. The area in this study is affected by strong tectonic activity in the Jinsha River suture zone and the rapid uplift of the Tibetan Plateau. In the past 6000 years, there have been at least five obvious river blocking events in the reach. The number and density are very rare. Combining field investigation, indoor interpretation, laboratory tests, optically stimulated luminescence (OSL) dating, SBAS-InSAR and previous studies, multidisciplinary approaches are used to systematically summarize the analysis methods and further the understanding of one river blocking event and multiple river blocking events from different perspectives. Especially in multiple river blocking events, we can get the wrong results if interaction is not considered. Through this study, the general method of analyzing the river blocking event and the problems that should be paid attention to in sampling are given, and relatively reliable historical results of river blocking events are obtained. This method has applicability to the identification and analysis of river blocking events and age determination of dams with multiple river blockages. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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14 pages, 3997 KiB  

Open AccessArticle

Numerical Simulation of Fluid Pore Pressure Diffusion and Its Mechanical Effects during Wenchuan Aftershocks

by Tao Chen, Yaowei Liu and Guomeng Zhang

Water 2022, 14(6), 952; https://doi.org/10.3390/w14060952 - 18 Mar 2022

Viewed by 2305

Abstract

The Ms 8.0 Wenchuan earthquake occurred on 12 May 2008, in the Sichuan Province of China, and it was accompanied by a series of strong aftershocks. The mechanisms contributing to the triggering of the Wenchuan aftershocks have attracted international attention. In this paper, [...] Read more.

The Ms 8.0 Wenchuan earthquake occurred on 12 May 2008, in the Sichuan Province of China, and it was accompanied by a series of strong aftershocks. The mechanisms contributing to the triggering of the Wenchuan aftershocks have attracted international attention. In this paper, based on previous analysis of spatiotemporal distribution of aftershocks regarding pore pressure diffusion of deep fluid, we established a three-dimensional hydraulic–mechanical coupling model and investigated the influence of fluid migration and its mechanical effects in the Longmenshan fault zone by using FLAC3D software. We obtained the characteristics of the pore pressure diffusion and fault reactivation within 70 days in an area NA. The results show that the pore pressure significantly increases up to 80 MPa during fluid intrusion into the fault plane. The pore pressure increase along the fault dip is greater than that along the fault strike, with a maximum difference of 3.18 MPa. The increase in pore pressure along the fault reduces the effective stress and leads to fault reactivation. The evolution of the fault reactivation area calculated in the model is compared with the spatiotemporal characteristics of the aftershocks. This study is meaningful for furthering the understanding of the role of deep fluids in fault dynamics and aftershocks triggering. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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24 pages, 12252 KiB  

Open AccessArticle

Susceptibility Assessment of Debris Flows Coupled with Ecohydrological Activation in the Eastern Qinghai-Tibet Plateau

by Hu Jiang, Qiang Zou, Bin Zhou, Zhenru Hu, Cong Li, Shunyu Yao and Hongkun Yao

Remote Sens. 2022, 14(6), 1444; https://doi.org/10.3390/rs14061444 - 17 Mar 2022

Cited by 18 | Viewed by 3382

Abstract

The eastern margin of the Qinghai-Tibet Plateau is an extreme topography transition zone, and characterized by significant vegetation zonation, in addition to geographic features (such as enormous topographic relief and active tectonics) that control the occurrence of debris flows, which are rapid, surging [...] Read more.

The eastern margin of the Qinghai-Tibet Plateau is an extreme topography transition zone, and characterized by significant vegetation zonation, in addition to geographic features (such as enormous topographic relief and active tectonics) that control the occurrence of debris flows, which are rapid, surging flows of water-charged clastic sediments moving along a steep channel and are one of the most dangerous mountain hazards in this region. There is thus an urgent need in this region to conduct a regional-scale debris flow susceptibility assessment to determine the spatial likelihood of a debris flow occurrence and guarantee the safety of people and property, in addition to the smooth operation of the Sichuan-Tibet transport corridor. It is, however, a challenging task to estimate the region’s debris flow susceptibility while taking into consideration the comprehensive impacts of vegetation on the occurrence of debris flows, such as the positive effect of root anchoring and the negative effect of vegetation weight loads. In this study, a novel regional-scale susceptibility assessment method was constructed by integrating state-of-the-art machine learning algorithms (such as support vector classification (SVC), random forest (RF), and eXtreme Gradient Boosting (XGB)) with the removing outliers (RO) algorithm and particle swarm optimization (PSO), allowing the impacts of vegetation on debris flow initiation to be integrated with the topographical conditions, hydrological conditions, and geotechnical conditions. This method is finally applied to assess the regional-scale susceptibility of debris flows in the Dadu River basin on the eastern margin of the Qinghai-Tibet Plateau. The study results show that (i) all hybrid machine learning techniques can effectively predict the occurrence of debris flows in the extreme topography transition zone; (ii) the hybrid machine learning technique RO-PSO-SVC has the best performance, and its accuracy (ACC) is 0.946 and the area under the ROC curve (AUC) is 0.981; (iii) the RO-PSO algorithm improves SVC, RF, and XGB performance (according to the ACC value) by 3.84%, 2.59%, and 5.94%, respectively; and (iv) the contribution rate of ecology-related variables is almost only one-tenth that of topography- and hydrology-related factors, according to the factor important analysis for RO-PSO-SVC. Furthermore, debris flow susceptibility maps for the Dadu River basin were created, which can be used to assess and mitigate debris flow hazards. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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14 pages, 15589 KiB  

Open AccessArticle

BLP3-SP: A Bayesian Log-Pearson Type III Model with Spatial Priors for Reducing Uncertainty in Flood Frequency Analyses

by Dan Tian and Lei Wang

Water 2022, 14(6), 909; https://doi.org/10.3390/w14060909 - 14 Mar 2022

Cited by 3 | Viewed by 3296

Abstract

Gauge stations have uneven lengths of discharge records owing to the historical hydrologic data collection efforts. For watersheds with limited water data length, the flood frequency model, such as the Log-Pearson Type III, will have large uncertainties. To improve the flood frequency prediction [...] Read more.

Gauge stations have uneven lengths of discharge records owing to the historical hydrologic data collection efforts. For watersheds with limited water data length, the flood frequency model, such as the Log-Pearson Type III, will have large uncertainties. To improve the flood frequency prediction for these watersheds, we propose a Bayesian Log-Pearson Type III model with spatial priors (BLP3-SP), which uses a spatial regression model to estimate the prior distribution of the parameters from nearby stations with longer data records and environmental factors. A Markov chain Monte Carlo (MCMC) algorithm is used to estimate the posterior distribution and associated flood quantiles. The method is validated using a case study watershed with 15 streamflow gauge stations located in the San Jacinto River Basin in Texas, US. The result shows that the BLP3-SP outperforms other choices of the priors for the Bayesian Log-Pearson Type III model by significantly reducing the uncertainty in the flood frequency estimation for the station with short data length. The results have confirmed that the spatial prior knowledge can improve the Bayesian inference of the Log-Pearson Type III flood frequency model for watersheds with short gauge period. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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14 pages, 5292 KiB  

Open AccessTechnical Note

Distinct Susceptibility Patterns of Active and Relict Landslides Reveal Distinct Triggers: A Case in Northwestern Turkey

by Marco Loche, Luigi Lombardo, Tolga Gorum, Hakan Tanyas and Gianvito Scaringi

Remote Sens. 2022, 14(6), 1321; https://doi.org/10.3390/rs14061321 - 9 Mar 2022

Cited by 8 | Viewed by 3840

Abstract

To understand the factors that make certain areas especially prone to landslides, statistical approaches are typically used. The interpretation of statistical results in areas characterised by complex geological and geomorphological patterns can be challenging, and this makes the understanding of the causes of [...] Read more.

To understand the factors that make certain areas especially prone to landslides, statistical approaches are typically used. The interpretation of statistical results in areas characterised by complex geological and geomorphological patterns can be challenging, and this makes the understanding of the causes of landslides more difficult. In some cases, landslide inventories report information on the state of activity of landslides, adding a temporal dimension that can be beneficial in the analysis. Here, we used an inventory covering a portion of Northwestern Turkey to demonstrate that active and relict landslides (that is, landslides that occurred in the past and are now stabilised) could be related to different triggers. To do so, we built two landslide susceptibility models and observed that the spatial patterns of susceptibility were completely distinct. We found that these patterns were correlated with specific controlling factors, suggesting that active landslides are regulated by current rainfalls while relict landslides may represent a signature of past earthquakes on the landscape. The importance of this result resides in that we obtained it with a purely data-driven approach, and this was possible because the active/relict landslide classification in the inventory was accurate. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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18 pages, 7541 KiB  

Open AccessFeature PaperArticle

In Situ Experimental Study of Natural Diatomaceous Earth Slopes under Alternating Dry and Wet Conditions

by Zhixing Deng, Wubin Wang, Tengfei Yan, Kang Xie, Yandong Li, Yangyang Liu and Qian Su

Water 2022, 14(5), 831; https://doi.org/10.3390/w14050831 - 7 Mar 2022

Cited by 6 | Viewed by 3937

Abstract

Very few studies have focused on diatomaceous earth slopes along high-speed railways, and the special properties of diatomaceous earth under alternating dry and wet conditions are unknown. This paper studies diatomaceous earth in the Shengzhou area, through which the newly built Hangzhou–Taizhou high-speed [...] Read more.

Very few studies have focused on diatomaceous earth slopes along high-speed railways, and the special properties of diatomaceous earth under alternating dry and wet conditions are unknown. This paper studies diatomaceous earth in the Shengzhou area, through which the newly built Hangzhou–Taizhou high-speed railway passes, and the basic physical and hydraulic properties of diatomaceous earth are analyzed by indoor test methods. A convenient, efficient, and controllable high-speed railway slope artificial rainfall simulation system is designed, and in situ comprehensive monitoring and fissure observation are performed on site to analyze the changes in various diatomaceous soil slope parameters under rainfall infiltration, and to explore the cracking mechanisms of diatomaceous earth under alternating dry and wet conditions. The results indicate extremely poor hydrophysical properties of diatomaceous earth in the Shengzhou area; the disintegration resistance index values of natural diatomaceous earth samples subjected to dry and wet cycles are 1.8–5.6%, and the disintegration is strong. Comprehensive indoor tests and water content monitoring show that natural diatomaceous earth has no obvious influence when it contacts water, but it disintegrates and cracks under alternating dry and wet conditions. The horizontal displacement of both slope types mainly occurs within 0.75–2.75 m of the surface layer, indicating shallow surface sliding; after testing, natural slope crack widths of diatomaceous earth reach 10–25 mm, and their depths reach 40–60 cm. To guarantee safety during high-speed railway engineering construction, implementing proper protection for diatomaceous earth slopes is recommended. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 5926 KiB  

Open AccessArticle

Investigation of Tsunami Waves in a Wave Flume: Experiment, Theory, Numerical Modeling

by Boris Vladimirovich Boshenyatov

GeoHazards 2022, 3(1), 125-143; https://doi.org/10.3390/geohazards3010007 - 3 Mar 2022

Viewed by 3843

Abstract

To protect the coastal areas of the seas and oceans from the destructive force of tsunami waves, coastal and surface barriers are usually built. However, for high waves, these barriers turn into underwater barriers through which tsunami waves pass practically without losing their [...] Read more.

To protect the coastal areas of the seas and oceans from the destructive force of tsunami waves, coastal and surface barriers are usually built. However, for high waves, these barriers turn into underwater barriers through which tsunami waves pass practically without losing their energy. In this paper, we study a new principle of suppression of the energy of tsunami waves by underwater barriers. The problems of experimental and numerical modeling of the processes of generation, propagation, and interaction of gravity wave of the tsunami type with underwater barriers are considered. It is shown that, under certain conditions near the underwater barriers, large-scale vortex structures occur that accumulate a significant part of the energy of the incident wave. Here, if the barriers parameter h/(H + A) = 0.84 ÷ 0.85 (h—height of the barriers, A—amplitude of incident wave on a barrier, H—depth of the reservoir), then the vortex structures accumulate up to 50% of the wave energy incident on the barrier. A theoretical model explaining the effect of anomalous vortex suppression of tsunami wave energy by underwater barriers has been developed. Theoretical calculations and results of numerical modeling based on the Navier–Stokes Equations are consistent with experimental studies in a hydrodynamic wave flume. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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12 pages, 4000 KiB  

Open AccessTechnical Note

Tropical Cyclone Impact and Forest Resilience in the Southwestern Pacific

by Baptiste Delaporte, Thomas Ibanez, Marc Despinoy, Morgan Mangeas and Christophe Menkes

Remote Sens. 2022, 14(5), 1245; https://doi.org/10.3390/rs14051245 - 3 Mar 2022

Cited by 7 | Viewed by 3561

Abstract

Tropical cyclones (TCs) can have profound effects on the dynamics of forest vegetation that need to be better understood. Here, we analysed changes in forest vegetation induced by TCs using the normalized difference vegetation index (NDVI). We used an accurate historical database of [...] Read more.

Tropical cyclones (TCs) can have profound effects on the dynamics of forest vegetation that need to be better understood. Here, we analysed changes in forest vegetation induced by TCs using the normalized difference vegetation index (NDVI). We used an accurate historical database of TC tracks and intensities, together with the Willoughby cyclone model to reconstruct the 2D surface wind speed structure of TCs and analyse how TCs affect forest vegetation. We used segmented linear models to identify significant breakpoints in the relationship between the reconstructed maximum sustained wind speed (Wmax) and the observed changes in NDVI. We tested the hypothesis that the rate of change in damage caused by TCs to forest and recovery time would increase according to Wmax thresholds as defined in the widely used Saffir–Simpson hurricane wind scale (SSHWS). We showed that the most significant breakpoint was located at 50 m/s. This breakpoint corresponds to the transition between categories 2 and 3 TCs in the SSHWS. Below this breakpoint, damages caused to forest vegetation and the time needed to recover from these damages were negligable. We found a second breakpoint, with a sharp increase in damages for winds >75 m/s. This suggested that extremely intense tropical cyclones, which might be more frequent in the future, can cause extreme damages to forest vegetation. Nevertheless, we found high variation in the observed damages and time needed to recover for a given Wmax. Further studies are needed to integrate other factors that might affect the exposure and resistance to TCs as well as forests’ capacity to recover from these disturbances. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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17 pages, 3704 KiB  

Open AccessArticle

Extracting Disaster-Related Location Information through Social Media to Assist Remote Sensing for Disaster Analysis: The Case of the Flood Disaster in the Yangtze River Basin in China in 2020

by Tengfei Yang, Jibo Xie, Guoqing Li, Lianchong Zhang, Naixia Mou, Huan Wang, Xiaohan Zhang and Xiaodong Wang

Remote Sens. 2022, 14(5), 1199; https://doi.org/10.3390/rs14051199 - 28 Feb 2022

Cited by 24 | Viewed by 3603

Abstract

Social media texts spontaneously produced and uploaded by the public contain a wealth of disaster information. As a supplementary data source for remote sensing, they have played an important role in disaster reduction and emergency response in recent years. However, social media also [...] Read more.

Social media texts spontaneously produced and uploaded by the public contain a wealth of disaster information. As a supplementary data source for remote sensing, they have played an important role in disaster reduction and emergency response in recent years. However, social media also has certain flaws, such as insufficient location information, etc. This affects the efficiency of combining these data with remote sensing data. For flood disasters in particular, extensively flooded areas limit the distribution of social media data, which makes it difficult for these data to function as they should. In this paper, we propose a disaster reduction framework to solve these problems. We first used an approach that was based on search engine and lexical rules to automatically extract disaster-related location information from social media texts. Then, we combined the extracted information with the upload location of social media itself to construct location-pointing relationships. These relationships were used to build a new social network, which can be used in combination with remote sensing images for disaster analysis. The analysis integrated the advantages of social media and remote sensing. It can not only provide macro disaster information in the study area but can also assist in evaluating the disaster situation in different flooded areas from the perspective of public observation. In addition, the timeliness of social media data also improved the continuity and situational awareness of flood monitoring. A case study of the flood disaster in the Yangtze River Basin in China in 2020 was used to verify the effectiveness of the method described in this paper. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 9966 KiB  

Open AccessArticle

Tsunami Hazard Zone and Multiple Scenarios of Tsunami Evacuation Route at Jetis Beach, Cilacap Regency, Indonesia

by Fx Anjar Tri Laksono, Asmoro Widagdo, Maulana Rizki Aditama, Muhammad Rifky Fauzan and János Kovács

Sustainability 2022, 14(5), 2726; https://doi.org/10.3390/su14052726 - 25 Feb 2022

Cited by 9 | Viewed by 4283

Abstract

The 2006 tsunami, throughout the Pangandaran to Cilacap Coast, resulted in 802 deaths and 1623 houses being destroyed. At Jetis beach, Cilacap Regency, 12 people died, and hundreds of houses were damaged. This area is a tourism destination, visited by hundreds of people [...] Read more.

The 2006 tsunami, throughout the Pangandaran to Cilacap Coast, resulted in 802 deaths and 1623 houses being destroyed. At Jetis beach, Cilacap Regency, 12 people died, and hundreds of houses were damaged. This area is a tourism destination, visited by hundreds of people per week. Therefore, this study aims to determine a tsunami hazard zone and the most effective evacuation route based on multiple factors and scenarios. The method of this study includes scoring, weighting, and overlaying the distance of the Jetis beach from the shoreline and the river, including the elevation and topography. The study results depict five levels of tsunami hazard zone at the Jetis beach: an area of high potential impact, moderately high, moderate, moderately low, and low. The southern Jetis beach is the most vulnerable area with regard to tsunamis, characterized by low elevation, proximity to the beach and rivers, and gentle slopes. The simulation results show the four fastest evacuation routes with the distance from the high-risk zone to the safe zone of around 683–1683 m. This study infers that the southern part of the Jetis beach, in the moderate to high impact zone, needs greater attention as it would suffer worst impact from a tsunami. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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17 pages, 4454 KiB  

Open AccessArticle

Regional Landslide Hazard Assessment Using Extreme Value Analysis and a Probabilistic Physically Based Approach

by Hyuck-Jin Park, Kang-Min Kim, In-Tak Hwang and Jung-Hyun Lee

Sustainability 2022, 14(5), 2628; https://doi.org/10.3390/su14052628 - 24 Feb 2022

Cited by 8 | Viewed by 2639

Abstract

The accurate assessment of landslide hazards is important in order to reduce the casualties and damage caused by landslides. Landslide hazard assessment combines the evaluation of spatial and temporal probabilities. Although various statistical approaches have been used to estimate spatial probability, these methods [...] Read more.

The accurate assessment of landslide hazards is important in order to reduce the casualties and damage caused by landslides. Landslide hazard assessment combines the evaluation of spatial and temporal probabilities. Although various statistical approaches have been used to estimate spatial probability, these methods only evaluate the statistical relationships between factors that have triggered landslides in the past rather than the slope failure process. Therefore, a physically based approach with probabilistic analysis was adopted here to estimate the spatial distribution of landslide probability. Meanwhile, few studies have addressed temporal probability because historical records of landslides are not available for most areas of the world. Therefore, an indirect approach based on rainfall frequency and using extreme value analysis and the Gumbel distribution is proposed and used in this study. In addition, to incorporate the nonstationary characteristics of rainfall data, an expanding window approach was used to evaluate changes in the mean annual maximum rainfall and the location and scale parameters of the Gumbel distribution. Using this approach, the temporal probabilities of future landslides were estimated and integrated with spatial probabilities to assess and map landslide hazards. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 5831 KiB  

Open AccessArticle

Interseismic Fault Coupling and Slip Rate Deficit on the Central and Southern Segments of the Tanlu Fault Zone Based on Anhui CORS Measurements

by Tingye Tao, Hao Chen, Shuiping Li, Xiaochuan Qu and Yongchao Zhu

Remote Sens. 2022, 14(5), 1093; https://doi.org/10.3390/rs14051093 - 23 Feb 2022

Cited by 4 | Viewed by 2410

Abstract

The Tanlu fault zone, extending over 2400 km from South China to Russia, is one of the most conspicuous tectonic elements in eastern Asia. In this study, we processed the Global Positioning System (GPS) measurements of Anhui Continuously Operating Reference System (AHCORS) between [...] Read more.

The Tanlu fault zone, extending over 2400 km from South China to Russia, is one of the most conspicuous tectonic elements in eastern Asia. In this study, we processed the Global Positioning System (GPS) measurements of Anhui Continuously Operating Reference System (AHCORS) between January 2013 and June 2018 to derive a high-precision velocity field in the central and southern segments of the Tanlu fault zone. We integrated the AHCORS data with those publicly available for geodetic imaging of the interseismic coupling and slip rate deficit distribution in the central and southern segments of the Tanlu fault zone. This work aims at a better understanding of strain accumulation and future seismic hazard in the Tanlu fault zone. The result indicates lateral variation of coupling distribution along the strike of the Tanlu fault zone. The northern segment of the Tanlu fault zone has a larger slip rate deficit and a deeper locking depth than the southern segment. Then, we analyzed three velocity profiles across the fault. The result suggests that the central and southern segments of the Tanlu fault zone are characterized by right-lateral strike-slip (0.29–0.44 mm/y) with compression components (0.35–0.76 mm/y). Finally, we estimated strain rates using the least-squares collocation method. The result shows that the dilatation rates concentrate in the region where the principal strain rates are very large. The interface of extension and compression is always accompanied by sudden change of direction of principal strain rates. Especially, in the north of Anhui, the dilatation rate is largest, reaching $3.780\times {10}^{-8}/a$. Our study suggests that the seismic risk in the northern segment of the Tanlu fault zone remains very high for its strong strain accumulation and the lack of historical large earthquakes. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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23 pages, 1559 KiB  

Open AccessArticle

Reported Occurrence of Multiscale Flooding in an Alpine Conurbation over the Long Run (1850–2019)

by Jean-Dominique Creutin, Juliette Blanchet, Alix Reverdy, Antoine Brochet, Céline Lutoff and Yannick Robert

Water 2022, 14(4), 548; https://doi.org/10.3390/w14040548 - 12 Feb 2022

Cited by 4 | Viewed by 3267

Abstract

This paper deals with the identification of extreme multiscale flooding events in the Alpine conurbation of Grenoble, France. During such events, typically over one to several days, the organization in space and time of the generating hydrometeorological situation triggers the concurrent reaction of [...] Read more.

This paper deals with the identification of extreme multiscale flooding events in the Alpine conurbation of Grenoble, France. During such events, typically over one to several days, the organization in space and time of the generating hydrometeorological situation triggers the concurrent reaction of varied sets of torrents and main rivers and creates diverse socioeconomic damages and disruptions. Given the limits of instrumental data over the long run, in particular at the torrent scale, we explore the potential of a database of reported extreme flood events to study multiscale flooding over a Metropolitan domain. The definition of Metropolitan events is mainly based on the database built by the RTM (Restauration des Terrains de Montagne, a technical service of the French Forest Administration). Relying on expert reports, the RTM database covers the long lifetime of this French national service for the management of mountainous areas (1850–2019). It provides quantitative information about the time and place of inundation events as well as qualitative information about the generating phenomena and the consequent damages. The selection process to define Metropolitan events simply chronologically explores the RTM database and complements it with historical research data. It looks for concurrence between site events at the same date under a chosen set of criteria. All scales together, we selected 104 Metropolitan events between 1850 and 2019. Exploring the list of dates, we examine the homogeneity of the Metropolitan events over 1850–2019 and their space–time characteristics. We evidence the existence of multiscale flooding at the Metropolitan scale, and we discuss some implications for flood risk management. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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14 pages, 22842 KiB  

Open AccessArticle

Correlation between Building Damages and Losses with the Microzonation Map of Mataram—Case Study: Lombok Earthquake 2018, Indonesia

by Bambang Setyogroho, Dicky Muslim, Muhammad Suwongso Sadewo, Ghazi Oktavidi Muslim, Safri Burhanuddin and Hendarmawan Hendarmawan

Sustainability 2022, 14(4), 2028; https://doi.org/10.3390/su14042028 - 10 Feb 2022

Cited by 3 | Viewed by 3277

Abstract

The high intensity of the earthquake on Lombok Island on 5 August 2018, with a magnitude of 7.0 Mb, caused material losses experienced by the affected residential areas. The Indonesian Geological Agency in 2015 published a microzonation map that mapped zones prone to [...] Read more.

The high intensity of the earthquake on Lombok Island on 5 August 2018, with a magnitude of 7.0 Mb, caused material losses experienced by the affected residential areas. The Indonesian Geological Agency in 2015 published a microzonation map that mapped zones prone to earthquake shocks to mitigate disasters. This study aimed to compare the level of damage and loss in residential areas due to earthquakes in Mataram City with earthquake-prone zones using a microzonation map. The correlation between damage and loss value of residentials with microzonation maps was evaluated using the overlay method. The results showed that the level of damage and the value of the loss of houses in the high disaster-prone zone (red zone) showed the highest loss value. In comparison, the level of losses in the moderate disaster-prone zone (yellow zone) and light disaster-prone zone (blue zone) on the microzonation map shows a low and lower loss value. This study concludes that the microzonation map helps determine the damage zone and the level of disaster vulnerability caused by the earthquake hazard. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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17 pages, 1023 KiB  

Open AccessArticle

Using ARC-D Toolkit for Measuring Community Resilience to Disasters

by Muhammad Awfa Islam, Musabber Ali Chisty, Abdullah Fuad, Md. Mostafizur Rahman, Maliha Muhtasim, Syeda Erena Alam Dola, Fariha Jahin Biva and Nesar Ahmed Khan

Sustainability 2022, 14(3), 1758; https://doi.org/10.3390/su14031758 - 3 Feb 2022

Cited by 5 | Viewed by 4625

Abstract

Increased levels of resilience will reduce the negative consequences of any disaster and develop the capacities of communities to mitigate future disasters. The main objective of this study was to measure the level of resilience of two different communities in two different study [...] Read more.

Increased levels of resilience will reduce the negative consequences of any disaster and develop the capacities of communities to mitigate future disasters. The main objective of this study was to measure the level of resilience of two different communities in two different study areas and compare the resilience levels in terms of a flood. The study used the Analysis of Resilience of Communities to Disasters (ARC-D) toolkit. The study was conducted in two different areas to compare the level of community resilience. Both quantitative and qualitative methods were used in the study. A structured questionnaire was developed by using the toolkit. Results of the study indicated that communities in study area 1 were more resilient than communities in study area 2. Communities from study area 1 were more aware of their risk(s) and problem(s) and ensured proper strategies and actions to solve problems. On the other hand, communities in study area 2 were less aware of their risk(s). The strategies and actions implemented by the communities of study area 1 focused on the short-term problem(s), which reduced their level of resilience. Measuring resilience is very important in terms of developing disaster risk reduction (DRR) plans and incorporating DRR in the development process in lower-income countries and developing countries. As data scarcity is one of the major issues in developing countries, introducing a community resilience assessment mechanism can be a great help to reduce gaps in the planning and implementation process. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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20 pages, 12170 KiB  

Open AccessFeature PaperArticle

Sea Level Rise Impact on Compound Coastal River Flood Risk in Klaipėda City (Baltic Coast, Lithuania)

by Erika Čepienė, Lina Dailidytė, Edvinas Stonevičius and Inga Dailidienė

Water 2022, 14(3), 414; https://doi.org/10.3390/w14030414 - 29 Jan 2022

Cited by 13 | Viewed by 4562

Abstract

Due to climate change, extreme floods are projected to increase in the 21st century in Europe. As a result, flood risk and flood-related losses might increase. It is therefore essential to simulate potential floods not only relying on historical but also future projecting [...] Read more.

Due to climate change, extreme floods are projected to increase in the 21st century in Europe. As a result, flood risk and flood-related losses might increase. It is therefore essential to simulate potential floods not only relying on historical but also future projecting data. Such simulations can provide necessary information for the development of flood protection measures and spatial planning. This paper analyzes the risk of compound flooding in the Danė River under different river discharge and Klaipėda Strait water level probabilities. Additionally, we examine how a water level rise of 1 m in the Klaipėda Strait could impact Danė River floods in Klaipėda city. Flood extent was estimated with the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) and visualized with ArcGIS Pro. Research results show that a rise in the water level in the Klaipėda Strait has a greater impact on the central part of Klaipėda city, while that of the maximum discharge rates of the river affected the northern upstream part of the analyzed river section. A sea level rise of 1 m could lead to an increase in areas affected by Danė floods by up to three times. Floods can cause significant damage to the infrastructure of Klaipėda port city, urbanized territories in the city center, and residential areas in the northern part of the city. Our results confirm that, in the long run, sea level rise will significantly impact the urban areas of the Klaipėda city situated near the Baltic Sea coast. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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16 pages, 2527 KiB  

Open AccessArticle

A Multiscale Normalization Method of a Mixed-Effects Model for Monitoring Forest Fires Using Multi-Sensor Data

by Lanbo Feng, Huashun Xiao, Zhigao Yang and Gui Zhang

Sustainability 2022, 14(3), 1139; https://doi.org/10.3390/su14031139 - 20 Jan 2022

Cited by 8 | Viewed by 2446

Abstract

This paper points out the shortcomings of existing normalization methods, and proposes a brightness temperature inversion normalization method for multi-source remote sensing monitoring of forest fires. This method can satisfy both radiation normalization and observation angle normalization, and reduce the discrepancies in forest [...] Read more.

This paper points out the shortcomings of existing normalization methods, and proposes a brightness temperature inversion normalization method for multi-source remote sensing monitoring of forest fires. This method can satisfy both radiation normalization and observation angle normalization, and reduce the discrepancies in forest fire monitoring between multi-source sensors. The study was based on Himawari-8 data; the longitude, latitude, solar zenith angle, solar azimuth angle, emissivity, slope, aspect, elevation, and brightness temperature values were collected as modeling parameters. The mixed-effects brightness temperature inversion normalization (MEMN) model based on FY-4A and Himawari-8 satellite sensors is fitted by multiple stepwise regression and mixed-effects modeling methods. The results show that, when the model is tested by Himawari-8 data, the coefficient of determination ($R^2$) reaches 0.8418, and when it is tested by FY-4A data, $R^2$ reaches 0.8045. At the same time, through comparison and analysis, the accuracy of the MEMN method is higher than that of the random forest normalization method (RF) ($R^2=0.7318$), the pseudo-invariant feature method (PIF) ($R^2=0.7264$), and the automatic control scatter regression method (ASCR) ($R^2=0.6841$). The MEMN model can not only reduce the discrepancies in forest fire monitoring owing to different satellite sensors between FY-4A and Himawari-8, but also improve the accuracy and timeliness of forest fire monitoring. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 7344 KiB  

Open AccessArticle

Determining the Risk Level of Heavy Rain Damage by Region in South Korea

by Jongsung Kim, Donghyun Kim, Myungjin Lee, Heechan Han and Hung Soo Kim

Water 2022, 14(2), 219; https://doi.org/10.3390/w14020219 - 12 Jan 2022

Cited by 8 | Viewed by 3758

Abstract

For risk assessment, two methods, quantitative risk assessment and qualitative risk assessment, are used. In this study, we identified the regional risk level for a disaster-prevention plan for an overall area at the national level using qualitative risk assessment. To overcome the limitations [...] Read more.

For risk assessment, two methods, quantitative risk assessment and qualitative risk assessment, are used. In this study, we identified the regional risk level for a disaster-prevention plan for an overall area at the national level using qualitative risk assessment. To overcome the limitations of previous studies, a heavy rain damage risk index (HDRI) was proposed by clarifying the framework and using the indicator selection principle. Using historical damage data, we also carried out hierarchical cluster analysis to identify the major damage types that were not considered in previous risk-assessment studies. The result of the risk-level analysis revealed that risk levels are relatively high in some cities in South Korea where heavy rain damage occurs frequently or is severe. Five causes of damage were derived from this study—A: landslides, B: river inundation, C: poor drainage in arable areas, D: rapid water velocity, and E: inundation in urban lowlands. Finally, a prevention project was proposed considering regional risk level and damage type in this study. Our results can be used when macroscopically planning mid- to long-term disaster prevention projects. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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19 pages, 8563 KiB  

Open AccessArticle

Spatially Varying Relationships between Land Subsidence and Urbanization: A Case Study in Wuhan, China

by Zhengyu Wang, Yaolin Liu, Yang Zhang, Yanfang Liu, Baoshun Wang and Guangxia Zhang

Remote Sens. 2022, 14(2), 291; https://doi.org/10.3390/rs14020291 - 9 Jan 2022

Cited by 18 | Viewed by 3354

Abstract

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land [...] Read more.

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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12 pages, 457 KiB  

Open AccessArticle

Income Diversification and Income Inequality: Household Responses to the 2013 Floods in Pakistan

by Shaikh M. S. U. Eskander and Sam Fankhauser

Sustainability 2022, 14(1), 453; https://doi.org/10.3390/su14010453 - 1 Jan 2022

Cited by 4 | Viewed by 3221

Abstract

In this paper we investigate the economic response of rural households to the 2013 floods in Pakistan. The case study illustrates the important roles of labor supply adjustments and income diversification in coping with climate-related risks. Using detailed household panel data that were [...] Read more.

In this paper we investigate the economic response of rural households to the 2013 floods in Pakistan. The case study illustrates the important roles of labor supply adjustments and income diversification in coping with climate-related risks. Using detailed household panel data that were collected before and after the 2013 floods, we find that the exposure to flood results in lower participation in farm activities. The overall effects are decreased diversification in the sources of income and ambiguous reduction in inequality which is associated with overall declines in incomes. These changes could be locked in if affected households do not have sufficient assets to resume farming. The results suggest intervention points for public policy, related to labor mobility and access to capital. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)

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