Natural Hazards Research最新文献

{"title":"Assessment of gully erosion susceptibility using four data-driven models AHP, FR, RF and XGBoosting machine learning algorithms","authors":"Md Hasanuzzaman ,&nbsp;Pravat Shit","doi":"10.1016/j.nhres.2024.05.001","DOIUrl":"10.1016/j.nhres.2024.05.001","url":null,"abstract":"<div><div>Gully erosion is a significant global threat to socioeconomic and environmental sustainability, making it a widespread natural hazard. Developing spatial models for gully erosion is crucial for local governance to effectively implement mitigation measures and promote regional development. This study applied two machine learning (ML) models, RF and XGB, alongside an AHP-based multi-criteria decision method and FR bivariate statistics, to assess gully erosion susceptibility (GES) in the Kangsabati River basin in eastern India's Chotonagpur plateau fringe. A GIS database was created, incorporating recorded gully erosion incidents and 20 conditioning variables, which were evaluated for multicollinearity. These variables served as predictive factors for assessing gully erosion presence in the study area. The models' performance was evaluated using metrics such as RMSE, MAE, specificity, sensitivity, and accuracy. The XGB model outperformed the others, achieving a predictive accuracy of 90.22%. The study found that approximately 6.56% of the Kangsabati catchment is highly susceptible to gully erosion, with 12.39% moderately susceptible and 81.05% not susceptible. The XGB model had the highest ROC value of 85.5 during testing, indicating its superiority over the FR (ROC ​= ​81.7), AHP (ROC ​= ​79.8), and RF (ROC ​= ​83.8) models. These findings highlight the XGB model's efficacy and potential for large-scale GES mapping.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 36-47"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial intelligence for landslide susceptibility and risk analysis: Insights from NH31A and east Sikkim Himalaya settlements","authors":"Sk Asraful Alam ,&nbsp;Sujit Mandal ,&nbsp;Ramkrishna Maiti","doi":"10.1016/j.nhres.2024.10.001","DOIUrl":"10.1016/j.nhres.2024.10.001","url":null,"abstract":"<div><div>Slope instability is a serious concern in the Sikkim Himalayas. The town and numerous road segments along National Highway 31A were ravaged by multiple landslides that occurred in the nearby region. A bivariate statistical method known as frequency ratio (FR), information value (IV), and certainty factor (CF) analysis was employed in this work to examine landslide risk assessment (LRA) and landslide susceptibility zonation (LSZ) maps in the Rorachu watershed. This study represents the first comprehensive analysis of landslide risk in the populated areas of East Sikkim and along NH31A, offering a deeper understanding of the risks involved and contributing to the enhancement of local resilience against landslide hazards. A total of 153 different landslide locations were mapped using Google Earth and GIS software; 30% (46) of these locations were used to validate the models, and 70% of these (107) served as training data for the FR, IV, and CF models. The thirteen landslide causative factors (geology, soil, elevations, slope, curvature, drainage density (DD), road density (RD), rainfall, normalized difference vegetation index (NDVI), land use land cover (LULC), topographic position index (TPI), stream power index (SPI), and topographic wetness index (TWI)) were extracted from a spatial database for LSZ mapping. Landslides were most prevalent on slopes (35°–50°), heights (2500–4100 ​m), and rainfall (2000–2500 ​mm and 3000–3300 ​mm). The area under the curves (AUC) for the FR, IV, and CF models are 0.925 (92.50%), 0.846 (84.60%), and 0.868 (86.20%), respectively. The prediction rates are shown by the AUCs for the FR, IV, and CF models, which are 0.828 (82.8%), 0.750 (%), and 0.836 (83.60%), respectively. According to the landslide risk assessment (LRA), the FR (20.75%), IV (40.91%) and CF (18.78%) models showed high risk on Highway 31A, while the FR (9.05%), IV (38.59%) and CF (20.90%) models showed high risk in densely populated areas. These landslide risk and vulnerability maps can be used to develop land use planning strategies that can save lives and are useful for planners and mitigation measures. Special attention should be paid to urbanization, highway construction, and deforestation.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 187-208"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in the study of natural disasters induced by the \"23.7\" extreme rainfall event in North China","authors":"Chenchen Xie ,&nbsp;Chong Xu ,&nbsp;Yuandong Huang ,&nbsp;Jielin Liu ,&nbsp;Xiaoyi Shao ,&nbsp;Xiwei Xu ,&nbsp;Huiran Gao ,&nbsp;Junxue Ma ,&nbsp;Zikang Xiao","doi":"10.1016/j.nhres.2025.01.003","DOIUrl":"10.1016/j.nhres.2025.01.003","url":null,"abstract":"<div><div>The article compiles and summarizes research on the natural disasters triggered by the \"23.7\" extreme rainfall in North China, utilizing the VOSViewer (Visualization of Similarities viewer) software for bibliometric analysis of existing studies and looking forward to future research. Based on the CNKI(China National Knowledge Infrastructure) database, the article focuses on studies related to meteorological, hydrological, and geological disasters resulting from this event. A total of 145 documents were obtained, including 41 articles on meteorological disaster research, 77 articles on hydrological disaster research, and 12 articles on geological disaster research. In the study of meteorological disasters, analyses of the causes and characteristics of heavy rainstorms have been summarized. In the study of hydrological disasters, analyses of the causes and impacts of floods have been summarized. In the study of geological disasters, analyses of the causes of disasters, case studies, and research on monitoring and early warning have been summarized. This event clearly demonstrates a continuous process from meteorological events to hydrological impacts, and then to geological disasters, forming a distinct \"meteorological-hydrological-geological disaster\" chain. Due to the increasing impact of climate change and human activities on extreme rainfall events, future research should delve deeper into the roles of these factors in floods and geological disasters, strengthen flood disaster management, and enhance geological disaster early warning systems. This is essential for reducing disaster losses and safeguarding the safety of people's lives and property.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 1-13"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Site response analysis for estimation of seismic site amplification in the city of Durban (South Africa)","authors":"B. Manzunzu ,&nbsp;V. Midzi ,&nbsp;B. Zulu ,&nbsp;T. Mulabisana ,&nbsp;T. Pule ,&nbsp;M. Sethobya ,&nbsp;N. Mankayi","doi":"10.1016/j.nhres.2024.11.002","DOIUrl":"10.1016/j.nhres.2024.11.002","url":null,"abstract":"<div><div>The city of Durban has previously experienced higher than expected ground motions from large distant earthquakes. It is potentially exposed to significant seismic hazard due to seismic site amplification, which needs to be estimated for effective mitigation efforts. Detailed stochastic one dimensional (1D) seismic site response analyses were performed at 90 sites in the city. Analytical models have demonstrated that they can simulate reasonably well the seismic ground motions amplification. The most widely used model is the equivalent linear approach. The approach computes the ground response of horizontally layered soil deposits subjected to transient and vertically propagating shear waves through a 1D soil column. Seven earthquake time histories together with developed sub-surface models were selected as input parameters to estimate the seismic site amplification at the 90 sites in the city. The used time histories were taken from the 2014 M5.5 Orkney earthquake with distance range (4.8–46.9 ​km). The uncertainties in ground motion input, variation in the shear wave velocity and variations in the shear modulus reduction and damping curves (i.e. variation of non-linear properties) were carefully modelled. Results obtained from this study were used to prepare maps of peak ground acceleration (PGA) at the surface and amplification factors. The minimum and maximum PGA at surface are estimated as 0.01 ​g and 0.30 ​g respectively. Based on the results of the analysis, the city may sustain amplification in the range of 0.7–4.7 ​at PGA with high values along the coast. The results indicate that the low shear wave velocity values, weak and soft material at shallow depths are responsible for the higher amplifications observed especially along the coast. Therefore, a site-specific design approach should be adopted for the seismic design of critical structures.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 219-228"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atami landslides 2021 Japan: Landfill issues, elderly casualties, key lessons and challenges","authors":"Namita Poudel ,&nbsp;Guo Chi,&nbsp;Cao Yuqiu,&nbsp;Rajib Shaw","doi":"10.1016/j.nhres.2024.06.006","DOIUrl":"10.1016/j.nhres.2024.06.006","url":null,"abstract":"<div><div>Landslides are a common problem worldwide, significantly impacting human societies. Japan is particularly susceptible to multiple hazards, including landslides. The Atami landslide in 2021 raised concerns about Japan's disaster management and evacuation processes. In this context, this research aims to compare the Atami landslide with previous landslides occurring between 2013 and 2021, focusing on their causes and impacts, particularly on elderly people. A comparative method is used to analyze two or more similar types of disasters. To accomplish the objectives of the paper, pertinent reports, government papers, and articles are reviewed. The findings indicate that the Atami landslide was distinct due to secondary causes, specifically illegal landfill management, where the landfill's height was increased beyond permissible limits. During the monsoon season, heavy rainfall led to flash floods in Atami city, resulting in human casualties and property loss. The study also found that the number of elderly casualties was high, similar to previous landslides, highlighting deficiencies in the evacuation system. The research suggests implementing a combined digital and community network-based early warning system and immediate follow-up inspections of other landfill sites as additional measures to improve existing disaster management strategies for future preparedness.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 88-94"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving social resilience to forest fire from community perspective","authors":"Yafang Wen,&nbsp;Ariyaningsih,&nbsp;Chi Guo,&nbsp;Anuska Ray,&nbsp;Rajib Shaw","doi":"10.1016/j.nhres.2024.08.004","DOIUrl":"10.1016/j.nhres.2024.08.004","url":null,"abstract":"<div><div>Recently, terms like social and community resilience have provided new ideas in reducing disaster risks especially in forest fire. However, a comprehensive and in-depth review of community social resilience concerning forest fires is lacking. There is little research investigate whether certain social or community resilience factors can initiate forest fires or whether forest fire prevention positively be influenced by them. To fill this gap, this paper aims to identify and discuss the factors influencing the occurrence of forest fires in the scope of community social resilience. It also provides recommendations for forest fire prevention and enhancing community social resilience to forest fires. PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) framework were used to do the systematic review. The results show that there are 4 main factors concerning the social resilience to forest fire such as, social capital, forest fire cultural, community economic, and community characteristics. In addition, this research also suggests future recommendations for preventing forest fires and improving community resilience to forest fires.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 166-174"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on rescue priority based on high spatiotemporal resolution mobile positioning data","authors":"Na Gao ,&nbsp;Jingjing Liu,&nbsp;Lijuan Yuan","doi":"10.1016/j.nhres.2024.08.003","DOIUrl":"10.1016/j.nhres.2024.08.003","url":null,"abstract":"<div><div>Estimate the key rescue areas of earthquake accurately, which is of great significance for deploying rescue forces and implementing rescue activities in post-earthquake scientifically.This paper based on the idea of first zoning, then classification, and then prioritizing rescue, taking the core area of Tangshan City as the study area, based on urban road data and mobile positioning data, combined with GIS methods to achieve street level rescue zoning, k-means clustering analysis is used to classify rescue sectors, and personnel burial model is used to conduct rescue priority classification.The results indicate that rescue priority is closely related to the time of earthquake occurrence. When the earthquake occurs between 18pm and 7pm in the next day, the number of priority rescue sector at level I and II is the highest. When the earthquake occurs between 8am and 11am on weekends, the number of priority rescue sector in residential areas increases, while the number of priority rescue zone decreases in workspace areas. This study provides refined rescue zoning and priority grading in the early stages of disaster relief with the absence of disaster information, which will help to assist in decision-making for professional force dispatch.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 157-165"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial-temporal assessment of soil erosion using the RUSLE model in the upstream Inaouène watershed, Northern Morocco","authors":"Chakir Hamouch ,&nbsp;Jamal Chaaouan ,&nbsp;Charaf eddine Bouiss","doi":"10.1016/j.nhres.2024.08.002","DOIUrl":"10.1016/j.nhres.2024.08.002","url":null,"abstract":"<div><div>This study aims to assess the risk of soil erosion in two different years (1984 and 2022) to gain insights into the extent of soil loss risk in the study area spatially and temporally. Using the Revised Universal Soil Loss Equation (RUSLE), which evaluates the soil loss rate, focusing primarily on erosivity of rainfall \"R,\" soil erodibility \"K,\" vegetation cover \"C,\" topography \"LS,\" and anti-erosion practices \"P.\" To achieve this, we incorporated various factors of the equation into a Geographic Information System (GIS) and spatial remote sensing. By overlaying these factors, we obtained a quantitative map of soil losses in our watershed. The results of this work show that the upstream Inaouène experienced a strong erosion dynamic in both 1985 and 2022, with a notable decrease in the amount of soil loss in the last year. Soil degradation in 1985 had an average of about 68 (T/ha/year), with maximum and minimum losses between 2162 and 0.067 ​T/ha/year, while losses in 2022 recorded an average of 52.4 (T/ha/year), with a maximum of 1850 (T/ha/year). The study area represents very high quantities of losses in both periods compared to several studies conducted in this region using the same model. This is due to the fact that the study area is located in a region characterized by very favorable natural and human conditions and factors to trigger and promote significant soil losses, including concentrated and intense rainfall, the predominance of fragile rocks, steep slopes, low vegetation cover in the eastern and southeastern part of the terrain, in addition to irrational human interference with the land.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 148-156"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Convolutional Neural Network-based approach for automatically detecting rainfall-induced shallow landslides in a data-sparse context","authors":"Roquia Salam ,&nbsp;Filiberto Pla ,&nbsp;Bayes Ahmed ,&nbsp;Marco Painho","doi":"10.1016/j.nhres.2024.09.001","DOIUrl":"10.1016/j.nhres.2024.09.001","url":null,"abstract":"<div><div>Detecting rainfall-induced shallow landslides in data-sparse regions has become increasingly important for effective landslides disaster management. Previous studies have predominantly focused on automated methods for deep-seated, earthquake-triggered landslides. This study addresses this gap by employing a U-net Convolutional Neural Network (CNN) model to detect rainfall-induced shallow landslides using multi-temporal, high-resolution PlanetScope (3m spatial resolution), medium-resolution Sentinel-2 (10m spatial resolution) imagery, and ALOS-PALSAR-provided digital elevation model (DEM). Four datasets were created: Datasets A and B using PlanetScope, and Datasets C and D using Sentinel-2, with Datasets B and D also including DEM data. A total of 181 manually delineated landslide polygons were used as ground truth masks. Each dataset was tested using repeated stratified hold-out validation. Performance metrics included precision, recall, F1 score, loss, and accuracy. Results indicated that Datasets A and B outperformed the others; however, integrating DEM with Dataset B did not enhance model accuracy. The best mean precision, recall, F1 score, loss, and accuracy were 1, 0.625, 0.625, 0.380, and 0.999, respectively, for both Datasets A and B. This study demonstrates the U-net model's potential for detecting rainfall-induced shallow landslides in various geographic and temporal contexts globally.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 175-186"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of microplastics on soil physical, chemical and biological properties","authors":"Monisha Mondol ,&nbsp;Prodipto Bishnu Angon ,&nbsp;Arpita Roy","doi":"10.1016/j.nhres.2024.02.002","DOIUrl":"10.1016/j.nhres.2024.02.002","url":null,"abstract":"<div><div>Pollution from microplastics (MPs) is recognized as a significant new global change factor that may have an impact on ecosystem services and functions. Although it is known that soil ecosystems, especially agricultural land, are a significant source of MPs, little is known about the effects of MPs on soil ecosystems, such as those above and below ground. As a major secondary source of microplastics (MPs) in various environmental media, the soil environment is where microplastics aggregate. To evaluate the effects of MP contamination on arable land, residential land areas (due to primary and secondary MPs), and the development and reproduction of soil fauna, we performed a global analysis in this study. This study sought to determine whether MP contamination exists in soil and how it influences the physical, chemical, and biological properties of the soil. To examine the causes, impacts, mitigation, and global perspective of MP pollution of soil, several research databases about its identification, occurrences, and consequences were combed for pertinent data and citations. The academic literature is collected using search engines such as Google Scholar, Springer Link, Elsevier, and Frontiers. Through this study, it is possible to evaluate how these qualities, MPs in landfill leachate, and the route of contamination from primary and secondary MPs to the soil affect soil toxicity and its consequential effects on physical, chemical, and biological properties as well as living organisms. This work also addresses the laws, rules, and numerous state-of-the-art treatment strategies for reducing the consequences of MPs. Significant gaps in knowledge require further thorough research.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 1","pages":"Pages 14-20"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}