Natural Hazards Research最新文献

Flooding disasters are occurring more frequently across the globe. Resilience capacity also differs with developing countries less able to withstand the devastating impacts of flooding. The level and type of action to prevent or mitigate flooding is dependent on the prevalent views on its principal drivers. This research engages with experts in the field of flood risk management in Nigeria, Africa's most populous country where the threats and frequency of flooding has increased over the years. An in-depth qualitative case study was conducted with semi-structured interviews used as the primary data collection tool. Understanding and distinguishing the core drivers of flooding according to context is pertinent because in a situation where the drivers are deemed to be factors beyond human control, there is risk of little action. The experts in this research acknowledged the influence of climate change on flooding which has led to increase in rainfall intensity, frequency and duration. However, they attributed the flooding being experienced in the research location to be due to more controllable human factors including lack of infrastructure, poor urban planning and governance, and weak implementation and enforcement of laws and policies. A mix of structural and non-structural solutions were recommended to better manage flooding and achieve the goal of sustainable cities and settlements.

This paper aims to provide an overview of the risks and trends of natural disasters in Southeast Asian countries and discuss necessary future countermeasures. Quantitative analysis of natural disasters was performed using data collected from EM-DAT. The disaster risk assessment for countries and disaster types was conducted using a frequency-impact risk matrix and risk ranking identification, which is a novel approach based on actual disaster data. The findings suggest that Indonesia, the Philippines, and Thailand face the highest mortality, affected population, and economic damage risks, respectively. Moreover, the study reveals that Southeast Asian countries are vulnerable to climate-related disasters. This risk assessment gives us a comprehensive understanding of natural disaster risks in Southeast Asian countries, enabling us to identify the most vulnerable countries in the region and determine the most significant disaster-type countermeasures for each country.

In May 2020, a magnitude 5.0 earthquake occurred in Qiaojia County, Yunnan. This earthquake was characteristics of relatively common “small earthquakes and major disasters” in the Zhaotong area of northeastern Yunnan. Yunnan province is an area in China with a high incidence of moderately strong earthquakes with magnitude 5 or above. In this region, the unique geological structure background and geographical environment of the Zhaotong area make it the most severely damaged area not only in Yunnan but also in all of China. The geological structure of the Zhaotong area is complex, and the neotectonic movements are strong. Based on the disasters of 8 moderate and strong earthquakes in Zhaotong since 2000, this paper analyses the causes of the “small earthquakes and major disasters” in Zhaotong city and provides suggestions for disaster reduction and emergency response after an earthquake.

The COVID-19 pandemic has had far-reaching impacts on every aspect of human life since the first confirmed case in December 2019. Costa Rica reported its first case of COVID-19 in March 2020, coinciding with a notable correlation between the occurrence of disaster events at the municipal scale over the past five decades. In Costa Rica, over 90% of disasters are hydrometeorological in nature, while geological disasters have caused significant economic and human losses throughout the country's history. To analyze the relationship between COVID-19 cases and disaster events in Costa Rica, two Generalized Linear Models (GLMs) were used to statistically evaluate the influence of socio-environmental parameters such as population density, social development index, road density, and non-forested areas. The results showed that population and road density are the most critical factors in explaining the spread of COVID-19, while population density and social development index can provide insights into disaster events at the municipal level in Costa Rica. This study provides valuable information for understanding municipal vulnerability and exposure to disasters in Costa Rica and can serve as a model for other countries to assess disaster risk.

Loess areas have a unique geological environment, and geological disasters occur there frequently. In this work, the typical loess area Lvliang was used as the study area. Using the historical landslide catalog, 12 influencing factors were chosen by integrating multisource heterogeneous spatiotemporal big data such as remote sensing, ground investigation, and basic geography. Based on frequency ratio (FR) and improved TabNet deep learning technology, landslide susceptibility evaluation and uncertainty analysis were performed. The results showed that the TabNet evaluation model using FR and self-supervised learning performs well and has the highest FR in extremely high-prone areas. Compared with other methods, this method has the highest scores in areas under the curve and susceptibility index distribution and the lowest uncertainty. Moreover, the SHAP method was used for interpretability analysis of the model. Therefore, this study can provide new ideas for landslide susceptibility management.

The complex geology and undulating terrain made Nepal vulnerable to natural disasters like landslides. Benighat-Rorang Rural Municipality (RM), in the Dhading district of Nepal's Bagmati province, has experienced several minor to massive landslides that have harmed both nature and civilization. This study examines the factors influencing landslides in the Benighat-Rorang RM by analyzing soil structure, geology, land cover, geomorphology (primarily slopes and aspects), fault lines, drainage density, weather data, and road density to generate a comprehensive Landslide Susceptibility Mapping (LSM). The LSM will help in identifying landslide-prone zones (high to low), which will, in turn, enable stakeholders to implement appropriate mitigation measures across the landslide-induced rural municipality. The current study intends to create Landslide susceptibility zonation mapping within and around the studied area by applying the AHP method while taking into account the optimal set of geo-environmental parameters to identify regions at risk of future landslides. Elevation, Slope, Aspect, Drainage, Geology, Soil Classes, Fault Line, Lineaments, Land-cover, Road Networks, Population, and climatic parameters (Rainfall, Temperature, Relative Humidity, Surface Pressure, and Wind Speed) are among the fourteen geo-environmental elements used for this research. Using the field verification approach, the results of this procedure have been validated, which can be observed in an estimated success rate curve. Meteorological factors, such as temperature, rainfall, relative humidity, surface pressure, and wind speed, have been examined regarding landslide susceptibility. Thus, an integrated assessment of landslide susceptibility was applied to the area to identify inhabited areas vulnerable to or at risk of landslides. Furthermore, the placement of public amenities throughout the research zone was considered while conducting the social vulnerability risk analysis. Finally, landslide susceptibility zonation, climatic factors influencing landslide susceptibility, and social vulnerability assessment results of the study area have been combined to generate a risk map identifying landslide-prone municipal facilities and vulnerable communities. This study will help in building resilient landslide communities through effective spatial urban planning that incorporates regional risks induced by landslides with infrastructure development and management strategies.

Natural-hazard crises generate much uncertainty among individuals, organizations, and communities. As feelings of uncertainty grow, individuals experience higher levels of stress and negative impacts to their psychological well-being. People desperately seek information and guidance on what to do and expect, along with how to adapt when faced with crises. While crisis-response organizations are key information disseminators, individuals also seek information from non-crisis-response organizations such as places where they work, volunteer, attend school, or worship. As the frequency of natural-hazard crises increases, so do the expectations of non-crisis-response organizations as valuable information sources.

However, there is limited research on the information needs of internal stakeholders and the adequacy of the information provided. In this paper, a new reliable and valid scale, Crisis Information Needs and Adequacy for Internal Stakeholders (CINA-IS) is introduced. Three studies to develop and test this scale are described in detail. This 6-item, one-factor scale can be used to assess the adequacy of the information provided during a crisis from the perspective of internal stakeholders. Organizations and those who study them are encouraged to use this scale to improve internal crisis communication. Adequately meeting internal stakeholders' information needs has the potential to help reduce uncertainty and negative psychological impacts on an organizations’ most important asset – its people.