Disaster Mitigation Measures Research Articles

Application of a Hybrid Model in Landslide Susceptibility Evaluation of the Western Tibet Plateau

The evaluation of landslide susceptibility plays a crucial role in preventing the risks associated with landslides and debris flows, providing valuable insights for the effective prevention and mitigation of geological hazards. However, there is limited research on high-altitude areas. Therefore, this study chose the western Tibetan Plateau as the study area, a representative area known for its susceptibility to landslides and high attitudes. In this study, seven factors were identified based on research objectives. Information value (IVM), weight of evidence (WOE), information value logistic regression (IVM-LR), weight of evidence logistic regression (WOE-LR), information value multi-layer perceptron (IVM-MLP) and weight of evidence multi-layer perceptron (WOE-MLP) were selected and compared for landslide susceptibility. The percentage of disaster area included in each risk level, the AUC value and the ROC curve were used to evaluate the accuracy of the results. The ROC curves of the results were close to the upper–left corner and the AUC values exceeded 0.85, an indication that all results were highly accurate. Moreover, the percentage of disaster area included for each risk showed an upward trend regarding susceptibility. The results indicated that the hybrid model exhibited superior performance in assessing landslide susceptibility at high altitudes. Overall, the results showed great significance regarding disaster prevention and mitigation measures of local governments.

Sustainability of Knowledge and practice regarding disasters among people living in flood-prone areas of Nepal

The main objective of this study is to examine the sustainability of knowledge and practice regarding disasters among people living in flood-prone areas of Nepal. Data for this survey were collected through a cross-sectional research design using a quantitative method. CARE Nepal and Handicap International implemented a community-based disaster risk reduction VISTAR project in Nepal’s Kailali, Dadeldhura, Kanchanpur, and Dang districts. The study used the baseline, end-line, and mainly post-project sustainability (PPS) survey data for detailed analysis. The study was conducted in four rural municipalities/municipalities of the Sudurpashchim Province. Univariate, Bivariate, and multivariate analyses (binary logistic regression) were applied to examine the sustainability of knowledge and practice regarding disasters among people living in flood prone areas of Nepal. It was observed that slightly over two-thirds of the respondents (67.5%) were female, while nearly one-third (32.5%) of them were male. More than one-fourth (27.5%) of the respondents were from the 25-34 age group, followed by one-fourth (25.1%) from the 35-44 age group. Knowledge of various types of disasters had increased for all types in the end-line (24.5 in the baseline to 32.9 in the end line) and showed sustainability in the PPS study (44.08) on average. Only less than a fourth (24%) of respondents reported the Household (HH) level plan requirement to mitigate the effect of disaster. Multivariate analysis found that respondents whose caste/ethnicity was Dalit (aOR= 1.3, 95% CI=0.7 2.23) and Janjati (aOR= 1.37, 95% CI=0.7 – 2.67) were more likely to know about the requirement of the HH level plan to mitigate the effect of a disaster than Brahmin/Chettri. Likewise, respondents whose primary source of income was small business/service were 3 times (aOR= 3.58, 95% CI= 1.46- 8.81) more likely to know about the requirement of the HH level plan to, mitigate the effect of a disaster than those whose source of income was agriculture. Knowledge of the type of disaster and the need for a household-level plan to mitigate disaster is very low. Thus, programs that advocate the importance of following disaster mitigation measures at the community and household level should be targeted to motivate people to be self-equipped to tackle possible disaster incidents.

Vulnerability assessment of the fishery system in China’s coastal provinces since 2000

Coastal fishery systems are vital for both the environment and the economy, and at present, they face heightened vulnerability due to global climate change and natural disasters. A clearer understanding of the challenges that the system presents can be obtained by examining the vulnerabilities of fishery systems. This study employed a vulnerability scoping diagram framework and a multi-indicator approach combined with the entropy weight method for assigning weights to systematically evaluate the vulnerabilities of fishery systems in China’s coastal provinces. The spatiotemporal variation characteristics of vulnerability were analyzed and characterized, and the primary obstacles that affect vulnerability are discussed. The findings suggest that China’s coastal provinces’ fishery systems display vulnerability in terms of both time and space. From a temporal perspective, Liaoning, Hebei, and Shandong provinces exhibited an increasing trend in vulnerability, while Tianjin, Jiangsu, Zhejiang, Shanghai, Fujian, Guangdong, Guangxi, and Hainan showed decreasing trends. From a spatial perspective, Hainan and Liaoning’s fishery systems exhibited extremely high vulnerability in most years. In contrast, Tianjin consistently experienced extremely low vulnerability in most years. From the perspective of obstacles, the main factor was the funding for the extension of aquaculture technology, and this remained the primary obstacle factor across all years. The findings are significant for enhancing our understanding of vulnerability in fishery systems and for strengthening disaster prevention and mitigation measures. The results provide robust support for the improvement of management and the protection of fishery systems.

Improving wave height prediction accuracy with deep learning

A novel convolutional neural network-long short-term memory (CNN-LSTM) model is proposed for wave height prediction. The model effectively extracts relevant features such as wind speed, wind direction, wave height, latitude, and longitude. The proposed model outperforms traditional machine learning algorithms such as multi-layer perceptron (MLP), support vector machine (SVM), random forest and LSTM, especially for extreme values and fluctuations. The model has a significantly lower average root mean square error (RMSE) of 71.1%, 72.8%, 71.9% and 72.2% for MLP, SVM, random forest and LSTM, respectively. Our model is computationally more efficient than traditional numerical simulations, making it suitable for real-time applications. Moreover, it has better long-term robustness compared to traditional models. The integration of CNN and LSTM techniques improves wave height prediction accuracy while enhancing its efficiency and robustness. The proposed CNN-LSTM model provides a promising tool for effective wave height prediction, making a valuable contribution to coastal disaster prevention and mitigation. Future research should aim to improve long-term prediction accuracy, and we believe that the CNN-LSTM model plays a crucial role in developing real-time coastal disaster prevention and mitigation measures. Overall, our study represents a significant step towards achieving more accurate and efficient wave height prediction using machine learning techniques.

Several strong historical earthquakes during Ming and Qing Dynasties and their effects to local reconstruction at Southern Shanxi Province, North China: Insight from the Chinese literature

The dissection of related Chinese literature of historical strong earthquakes is very important for formulating effective disaster mitigation measures. During the Ming and Qing Dynasties (AD 1368–1910) in North China, there were three strong earthquakes (AD 1556 Huaxian M 8.25 earthquake, AD 1695 Linfen M 7.75 earthquake and AD 1815 Pinglu M 6.75 earthquake), caused great damages to local cities of southern Shanxi Province, including damages of various types of buildings, numerous casualties, while the society and economy suffered a sudden heavy blow. Meanwhile, the occurrence of these earthquakes also provides important opportunities to restore the regional social order. In addition to the support of national disaster relief policies, the local officials actively organized people to cope with the disasters, made every effort to reconstruct the cities, that reflected the feelings of "caring about People's livelihood" or "the principle of supremacy of life", to improve the efficiency of regional social order benign operation. Certainly, the recovery and reconstruction process after the three strong earthquakes reflected imbalance between different time, regions, and between urban and rural areas. The literature review in this article has certain reference significance for the formulation and improvement of current disaster reduction measures.

Automatic detection of crop lodging from multitemporal satellite data based on the isolation forest algorithm

Rapid identification of crop lodging has implications for optimizing disaster prevention and mitigation measures. This study proposes a sequentially integrated algorithm for crop lodging identification, which first automatically extracts lodged and non-lodged samples based on the isolation forest algorithm from the screened features dataset and then uses a supervised classifier for lodging identification. Taking the crop lodging disaster caused by the super typhoon “Maysak” in Bohetai Township as an example, we calculated 162 feature indices from Sentinel-1 and Sentinel-2 satellite data pre- and post-disaster and screened the optimal features. Then, the abnormal scores of the cultivated-land pixels were calculated using the isolation forest algorithm. After that, we calculated the coefficient of variation (CV) of the abnormal scores of each group, extracted the lodged and non-lodged samples based on the cumulative CV contribution rate, and input samples into three supervised classifiers (random forest, maximum likelihood, and support vector machine) to identify lodged crop pixels. The results showed that feature screening increased the identification accuracy of crop lodging by more than 10% and difference features of short-wave infrared (SWIR) and red edge bands contributed significantly to the identification. The accuracy of crop lodging automatic identification was verified using samples obtained from visual interpretation and digitization of UAV images as reference data and the overall accuracy reached 78%. The proposed method can simultaneously recognize lodging of different crop types without the need to select lodged samples and extract lodged ranges for each crop. With low data acquisition costs and high automation, the proposed method has promising applications in agricultural disaster emergency management and agricultural insurance loss assessment.

Landslide Susceptibility Evaluation of Bayesian Optimized CNN Gengma Seismic Zone Considering InSAR Deformation

Landslides are one of the most common geological disasters in China, characterized by suddenness and uncertainty. Traditional methods are not sufficient for the accurate identification, early warning, and forecasting of landslide disasters. As high-resolution remote sensing satellites and interferometric synthetic aperture radar (InSAR) surface deformation monitoring technology have been leaping forward, the traditional methods of landslide monitoring data sources are limited, and there have been few effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors, etc. In this study, an area extending 10 km from the VII isobar of the Gengma earthquake was taken as the study area, and 13 evaluation factors were screened out by integrating the factors of InSAR surface deformation, topography, and geological environment. Landslide susceptibility was evaluated through the Bayesian optimized convolutional neural network (BO-CNN), and the Bayesian optimized random forests (BO-RF) and particle swarm optimization support vector machines (PSO-SVM) models were selected for comparative analyses. The accuracy of the model was evaluated by using three indices, including the ROC curve, the AUC value, and the FR value. Specifically, the ROC curves of PSO-SVM, BO-RF, and BO-CNN were close to the upper-left corner, indicating excellent model performance. Moreover, the AUC values were computed as 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslides in the high susceptibility area of BO-CNN reached up to 14.9 and exceeded those of PSO-SVM and BO-RF, respectively. Furthermore, the mentioned values of the SVM and BO-RF models were 4.55 and 3.69 higher. The experimental results indicated that, compared with other models, the BO-CNN model used in this study had a better effect on landslide susceptibility evaluation, and the research results are of great significance to the disaster prevention and mitigation measures of local governments.

Disaster Mitigation Model for Sustainable Tourism Development at the Nam Salu Openpit Geosite: Insights from the Belitong UNESCO Global Geopark

This research aims to develop an effective disaster mitigation model to support sustainable tourism development at the Nam Salu Openpit Geosite, which is an integral part of the Belitong UNESCO Global Geopark. The qualitative approach method uses descriptive methods through case studies, namely the Open Pit Nam Salu (OPNS) geosite. The results of research conducted regarding the Open Pit Nam Salu (OPNS) Geosite in East Belitung revealed that the potential threat of disaster to this tourist site is very significant. The main factors influencing the vulnerability of OPNS Geosites to natural disasters include ecosystem damage due to unmanaged mining activities, changes in the landscape caused by intensive mining practices, and disruption of slope stability due to excessive exploitation of natural resources. In addition, climate change can also worsen the risk of disasters, including landslides and coastal erosion. Therefore, it is necessary to carry out structured disaster mitigation measures, including an early warning system, emergency management training, regular risk mapping, evacuation planning, development of a disaster information center, as well as education and public awareness programs to maintain the sustainability of the OPNS Geosite as a safe tourist destination. and sustainable.

A comparative analysis on flood risk assessment and management performances between Beijing and Munich

With climate change and rapid urbanization, the prevalent flood disasters and associated risks in urban areas have become increasingly crucial global issues. Risk assessment is a basic step in flood management and mitigation, while flood management is important to achieve risk mitigation. A comprehensive assessment framework considering both pre- and post-disasters that can address flood risk is lacking. Therefore, this study developed an integrated framework by combining the assessments of flood risk and flood management performance. Taking Beijing and Munich as research objects, this study generated flood risk maps at the grid scale for the period 2000–2020 and comparatively assessed the performance of various flood management measures. The urban flood risk in Beijing showed an increasing trend and then a decreasing one from 2000 to 2020, exhibiting high spatial characteristics in the southeast and low spatial characteristics in the northwest. The flood risk in Munich showed an overall decreasing trend, with strong spatial characteristics in the center area but less so in suburban areas. The shift from low to high urbanization levels was the major factor increasing the regional flood risk. Therefore, effective flood management measures in urban areas could potentially mitigate the flood risk, and Munich had a higher flood management performance owing to its well-developed flood management systems. This study provides a new framework for flood risk assessment and resilient flood management and contributes to the development of practical measures for disaster mitigation in rapidly-developing urban areas.

Socialization on Saving Lives with Disaster Mitigation in Poko Village, Jambon District, Ponorogo Regency

Natural disasters cause massive losses and damage and have quite a large impact both materially and non-materially and can cause changes to the socio-economic conditions of the people as the affected parties. The lack of public knowledge of actions and disaster management through mitigation that occurred in Poko Village, Jambon District caused natural disasters that occurred to have an impact. The purpose of this article is to analyze the effectiveness of outreach in increasing community awareness and preparedness related to potential disasters in the Poko Village area, Jambon District. This research method uses a qualitative approach. The results showed that the socialization program had succeeded in increasing community awareness regarding disaster risks in Poko Village. Through the dissemination of clear information and the active participation of the community in evacuation simulations and mitigation exercises, the level of disaster preparedness has increased significantly. Knowledge of disaster mitigation measures, such as creating evacuation routes and participation in rapid response teams, has also seen a marked increase.

Effects of Disaster Management towards Academic Achievement in Public Secondary Schools in Arusha District

This study investigated the effects of disaster management towards academic achievement in public secondary schools in Arusha District Council, Tanzania. Objectives were to; examine ways of managing disasters in secondary schools and effects of disaster management towards academic achievement of students in public secondary schools. Emergency Management Theory guided the study. Convergent mixed methods design was adopted. Questionnaires, documentary analysis, photo taking and interviews were used to collect data from 105students and 85teachers selected by simple and stratified random sampling techniques. Five school heads and 4 WEOs were purposively selected. Validity was fortified through expert inputs. Reliability employed test-retest technique and reliability index, SQ r=0.735, TQ r=0.827and NTSQ r= 0.761were obtained. Credibility and dependability of qualitative data was established through detailed reporting of the research process. Qualitative data underwent thematic analysis. Quantitative data were analysed using descriptive statistics in the SPSS version 23 and results were presented in tables. Findings include provision of fire extinguishers to help in putting off fire outbreaks, enhancing drainage system and raising building foundation to prevent surface runoff from accessing classrooms and offices. Proper use of fire extinguishers to minimize damages caused by fire in schools hence minimal interference to learning process. In conclusion, without a disaster management plan, schools spend more time and resources reacting to a situation instead of planning for the anticipated disaster. Recommendations entailed all institutions to provide fire extinguishers, enhance drainage system and improve students’ discipline as disaster mitigation measures.

Indirect and Direct Impacts of Typhoon In-Fa (2021) on Heavy Precipitation in Inland and Coastal Areas of China: Synoptic-Scale Environments and Return Period Analysis

Abstract In July 2021, Typhoon In-Fa (TIF) triggered a significant indirect heavy precipitation event (HPE) in central China and a direct HPE in eastern China. Both these events led to severe disasters. However, the synoptic-scale conditions and the impacts of these HPEs on future estimations of return periods remain poorly understood. Here, we find that the remote HPE that occurred ∼2200 km ahead of TIF over central China was a predecessor rain event (PRE). The PRE unfolded under the equatorward entrance of the upper-level westerly jet. This event, which encouraged divergent and adiabatic outflow in the upper level, subsequently intensified the strength of the upper-level westerly jet. In contrast, the direct HPE in eastern China was due primarily to the long duration and slow movement of TIF. The direct HPE occurred in areas situated less than 200 km from TIF’s center and to the left of TIF’s propagation trajectory. Anomaly analyses reveal favorable thermodynamic and dynamic conditions and abundant atmospheric moisture that sustained TIF’s intensity. A saddle-shaped pressure field in the north of eastern China and peripheral weak steering flow impeded TIF’s movement northward. Hydrologically, the inclusion of these two HPEs in the historical record leads to a decrease in the estimated return periods of similar HPEs. Our findings highlight the potential difficulties that HPEs could introduce for the design of hydraulic engineering infrastructure as well as for the disaster mitigation measures required to alleviate future risk, particularly in central China.

Glacier Change in the West Kunlun Main Peak Area from 2000 to 2020

Glaciers are sensitive indicators of climate change, and investigation of their dynamics is crucial for ensuring regional ecological security as well as disaster prevention and mitigation measures. Based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) imagery, the outlines and length of glaciers in the West Kunlun Main Peak Area (WKMPA) during 2000–2020 were obtained by combining a band ratio method with manual interpretation and an automatic extraction method for the glacier centerline, respectively. There were 440 glaciers in the WKMPA in 2020, covering an area of 2964.59 ± 54.87 km2, with an average length of 2916 ± 60 m. The glacier count increased due to division, while the area and length all exhibited a declining trend from 2000 to 2020, at rates of −0.04%·a−1 (24.83 km2) and −0.11%·a−1 (66 m), respectively. Glacier retreat was primarily observed during the early period (2000–2005). Except for glaciers located above an elevation of 6250 m, the glacier area decreased with each altitude interval from 2000 to 2020, and the rate of relative change in glacier area generally decreased with increasing altitude. Moreover, except for a slight increase in north-facing glaciers, the area of glaciers facing other orientations decreased during 2000–2020. The accuracy of the empirical formula fit for glacier length was highly dependent on glacier class, with greater precision observed for smaller glaciers and lower precision for larger valley-basin glaciers due to their complex morphological structures being neglected and only a single quantitative relationship being considered. There was a time lag of 12 years between temperature changes and glacier area response in this region. The mechanism by which glacier division affects glacier change is complex, requiring dissection of multiple factors such as area, length, and terminal elevation before and after division.

Multi-Criteria Seismic Risk Assessment Based on Combined Weight-TOPSIS Model and CF-Logistic Regression Model—A Case Study of Songyuan City, China

Urban seismic hazards are natural disasters caused by earthquakes in urban areas, which may lead to serious casualties, the collapse of buildings, infrastructure damage, and other impacts, require huge social resources for recovery and reconstruction, and even affect the security stability and sustainable development of the area. This paper adopts the research idea of “Risk = Hazard × Exposure × Vulnerability ÷ Emergency response and recovery capability” and constructs an evaluation system containing 24 representative indicators on this basis. The CF-logistic regression model is applied in the study to calculate the seismic hazard, while the combined weight-TOPSIS model is used to assess the vulnerability of urban hazard-bearing body. Lastly, the study conducts multi-criteria seismic risk evaluation using the GIS platform. The results show that the overall seismic risk in Songyuan is moderate, with 18.66% of the medium-risk area, 37.68% of the very low risk area, 33.96% of the low-risk area, 8.47% of the high-risk area, and 1.23% of the very high-risk area. The significance of this study is to provide a scientific basis for formulating corresponding disaster prevention and mitigation measures and emergency plans, improving urban disaster prevention and emergency response capabilities, reducing urban earthquake disaster losses, and helping to achieve safe and stable urban development.

Prediction of Wave Forces on the Box-Girder Superstructure of the Offshore Bridge with the Influence of Floating Breakwater

In recent years, with global warming and frequent natural disasters, existing offshore bridges are facing the risk of extreme wave action. The research on disaster prevention and mitigation measures of the box-girder superstructure of offshore bridges under extreme wave action is still scarce. In this paper, a numerical model based on the RANS equation and k-ε turbulence model is established to study the wave forces on the box-girder superstructures of offshore bridges with the influence of a floating breakwater. A numerical method for studying the interaction of waves and structures is proposed and verified through experimental data. The effects of many parameters of the floating breakwater on wave attenuation are investigated and a prediction model of the wave reduction rate based on neural network algorithm is proposed. The results show that the reduction rate of wave forces for fixed breakwaters can reach more than 30%, which indicates that a floating breakwater has a significant effect in reducing the wave forces on the box-girder superstructure. The wave reduction performances of the displacement-restricted breakwater and the fixed breakwater are better than that of an elastic restricted breakwater. The prediction model proposed based on the BP neural network is accurate in estimating the maximum wave forces on the box-girder superstructure with the influence of the floating breakwater.

A networked risk perspective for analysing debris flow losses factors considering mitigation measures

ABSTRACT As debris flow disasters are becoming increasingly severe worldwide, it is necessary to deepen the research on disaster losses, especially the impact and role of disaster mitigation measures. Based on the regional disaster system theory, this paper sets an influencing factor system of debris flow losses. Then, from the perspective of networked risk, the risk propagation network is established through the Delphi method. Finally, the social network analysis method is introduced to discuss the risk propagation relationship between these factors from two aspects of the overall network analysis and node centrality analysis. The results reveal the chain-like influence characteristics of factors and clarify the main points relevant departments should emphasise in disaster risk reduction. Environmental and engineering mitigation measures strongly influence other factors, thus dominating the risk propagation in forming debris flow losses. The peril of debris flow, residents’ escape ability, and emergency rescue can be easily influenced by other factors, so increasing the resistance of these sensitive factors to the source of influence would support loss reduction. The research results can be applied to risk assessment and loss reduction of debris flow disasters.

Questionnaire on employee awareness of disaster mitigation measures in municipal governments

In the event of a disaster, municipal governments are expected to fulfil several responsibilities. However, owing to organizational reforms, cost reductions, and workforce reductions experienced by Japanese municipal governments in the 1990s and 2000s, they have arguably become incapable of providing effective community-based administration. In this context, a questionnaire survey was conducted on the employees of municipal governments in coastal regions of Japan where earthquakes and tsunamis are commonly anticipated. An attempt was made to evaluate the current state of disaster awareness within organizations and among staff members based on the survey results and clarify organizational and individual issues. Those surveyed were 288 officials with significant disaster response roles. The questionnaire survey was conducted to evaluate their understanding of various disaster response measures and their knowledge of their responsibilities. In the questionnaire, three disaster phases were considered: the predisaster, rescue, and reconstruction phases. The responses of each employee corresponding to each phase were recorded. The results indicate that, although various plans were well known to all participants to a certain extent, the level of understanding varied between departments. In addition, departmental employees who were often involved in disaster mitigation were concerned about the coherence and effectiveness of the operations undertaken in various plans. Thus, these issues should be considered in future reviews of disaster response plans. Despite considerable progress in the development and distribution of emergency plans, much remains to be done to raise awareness regarding specific action plans among the staff. This concerns the specificity, coherence, and effectiveness of each plan rather than the knowledge of the personnel.

Nature-Based solutions for landslide risk reduction: a critcal review of academic literature

Landslides are a widespread natural hazard that threatens the built and natural environment and increases the areas of deforestation. Landslides have an impact on human life, the impact can be reduced by reducing the risk of landslides, reducing the risk of landslides aims to reduce the number of people affected, deaths and economic losses. Forests and vegetation can provide a protective function against landslides consisting of hydrological and soil conditions, such as soil moisture, water infiltration, and others. This ability of vegetation is called nature based solutions. The 46 studies selected for this landslide nature-based solution were analyzed with a focus on an in-depth literature review. The articles were analyzed with three focus reviews, namely: 1) types of landslides, 2) solutions regarding landslide mitigation, and 3) landslide risks. The types of landslides discussed in this article are 73% shallow landslide types, 22% landslide types rotation and 5% flow landslide type. The risk in this article regarding hazards/threats is discussed at 57%, exposure around 21% and vulnerability around 22%. Landslide risk reduction solutions in the articles reviewed, as many as 44% discussed nature-based solutions, 30% about other solutions, and 30% there were no solutions in reducing landslide risk. In the publication of 46 articles, nature-based solution approaches that are widely mentioned are environmental engineering, soil bioengineering and protected forests. The nature-based solution in this research shows that vegetation is the main solution in disaster mitigation measures.

Simulated distributions of pumice rafts in Japan following eruptions at volcanic islands and submarine volcanoes

Voluminous pumice rafts produced by the 2021 phreatomagmatic eruption of Fukutoku-Oka-no-Ba, a submarine volcano located in the Izu-Bonin Islands, reached many Japanese ports and islands, damaging fisheries and hindering marine traffic and trade. This event emphasized the necessity for governments and stakeholders to develop plans in advance and prepare disaster mitigation measures before an eruption. To investigate when and to what extent pumice might intersect trade routes and arrive at islands after future eruptions, we conducted particle tracking simulations of eruptions at major volcanic islands and submarine volcanoes near Japan using the velocity field from the ocean reanalysis dataset. Seven major volcanoes that have produced pumice rafts in the past century were selected: the submarine volcano NNE of Iriomote Island, Izu-Tobu Volcanoes, Miyakejima, Bayonnaise Rocks, Nishinoshima, Kaitoku Seamount, and Fukutoku-Oka-no-Ba. We partly reproduced the distribution of pumice arrivals recorded after the 1986 Fukutoku-Oka-no-Ba eruption, demonstrating the potential effectiveness of the simulations. We report likely pumice raft arrivals and drifting durations for the investigated eruptive scenarios, which may aid future risk assessments for pumice arrivals.

Machine learning-based automatic construction of earthquake catalog for reservoir areas in multiple river basins of Guizhou province, China

Large reservoirs have the risk of reservoir induced seismicity. Accurately detecting and locating microseismic events are crucial when studying reservoir earthquakes. Automatic earthquake monitoring in reservoir areas is one of the effective measures for earthquake disaster prevention and mitigation. In this study, we first applied the automatic location workflow (named LOC-FLOW) to process 14-day continuous waveform data from several reservoir areas in different river basins of Guizhou province. Compared with the manual seismic catalog, the recall rate of seismic event detection using the workflow was 83.9%. Of the detected earthquakes, 88.9% had an onset time difference below 1 s, 81.8% has a deviation in epicenter location within 5 km, and 77.8% had a focal depth difference of less than 5 km, indicating that the workflow has good generalization capacity in reservoir areas. We further applied the workflow to retrospectively process continuous waveform data recorded from 2020 to the first half of 2021 in reservoir areas in multiple river basins of western Guizhou province and identified five times the number of seismic events obtained through manual processing. Compared with manual processing of seismic catalog, the completeness magnitude had decreased from 1.3 to 0.8, and a b-value of 1.25 was calculated for seismicity in western Guizhou province, consistent with the b-values obtained for the reservoir area in previous studies. Our results show that seismicity levels were relatively low around large reservoirs that were impounded over 15 years ago, and there is no significant correlation between the seismicity in these areas and reservoir impoundment. Seismicity patterns were notably different around two large reservoirs that were only impounded about 12 years ago, which may be explained by differences in reservoir storage capacity, the geologic and tectonic settings, hydrogeological characteristics, and active fault the reservoir areas. Prominent seismicity persisted around two large reservoirs that have been impounded for less than 10 years. These events were clustered and had relatively shallow focal depths. The impoundment of the Jiayan Reservoir had not officially begun during this study period, but earthquake location results suggested a high seismicity level in this reservoir area. Therefore, any seismicity in this reservoir area after the official impoundment deserves special attention.