Natural Hazards Research最新文献

This paper explores the scope and potential of Impact-based Forecast and Warning (IbFW) services for hydro-meteorological hazards in India. It builds upon several global and national initiatives which emphasize that the Early Warning System (EWS) requires to be people-centric and inclusive in order to reduce disaster risk. The objectives of the study are: to understand the current Impact-based Forecast and Warnings framework of the India Meteorological Department (IMD) and its usefulness from the people's perspective. Drawing from fieldwork conducted in Krushnaparasad Block, Puri District of India, the paper argues that there is a shifting focus towards meeting the requirements of general public, but there is a long way to go as far as meeting expectations are concerned. It calls for changes such as strengthening risk assessment modeling, clarity over institutional mandates and adoption of flexible governance frameworks to move from an Impact-based paradigm to Impact Forecast and Warning services.

Flooding is a recurrent and severe natural hazard in Afghanistan, exacerbated by climate change, and poses significant threats to human lives and livelihoods. The country's socioeconomic vulnerabilities make it highly susceptible to the devastating impacts of disasters, resulting in loss of lives, livelihoods, and damage to public and private assets. This study employs a multimethod research approach, combining remote sensing-based flood data analysis with spatial analysis and literature studies, to comprehensively assess flood risk by considering hazard, exposure, and vulnerability indicators. Specifically, a 25-year return flood event was used to examine flood risk for the exposed population. The framework proposed by the IPCC in 2014 was adopted to define flood risk, encompassing hazard, exposure, and vulnerability components. The findings reveal that provinces located near major river basins, particularly in the southern, northern, and northeastern regions, experience the highest flood risk. Notably, the provinces of Nimroz and Helmand in the southern region exhibit pronounced risk index values of 0.20 and 0.10, with a highly exposed population of 36% and 15%, respectively, and vulnerability index values of 0.57 and 0.62. Similarly, in the northern and northeastern regions, the provinces of Jawzjan and Kunduz also display elevated risk levels, each with a risk index value of 0.11, characterized by highly exposed populations of 21% and 18%, respectively, and vulnerability index values of 0.53 and 0.57. This multi-method approach provides valuable insights into the spatial distribution of flood risk and the drivers of population exposure, assisting policymakers and decision-makers in formulating effective flood risk reduction strategies through targeted flood vulnerability and risk reduction measures.

The Main Boundary Thrust (MBT) and Main Boundary Fault (MBF) zones of the southeast Himachal Himalaya are susceptible to various types of mass movement. Several active and in-active landslides are observed along the strike of the MBT. The landslides are mainly controlled by the brecciated and highly fractured nature of the bedrocks, and the intersecting joint sets form wedges. The movements are taking place along the fault planes, fracture planes, and bedding planes; and the types of failure are wedge failure, planar failure, toppling, rock falls, and complex landslides. The various morphotectonic features observed in the study area include fault traces, fault scarps, strath terraces, paleochannels and structurally controlled channels. Fault traces and their associated deformed landforms are the most spectacular tectonic landforms in the area. Along the strike length of the fault traces several linearly arranged sag ponds have formed, in the western segment the fault trace is observed along the MBF and the fault scarp dips south, with a maximum height of about 34 ​m. In the eastern segment the fault trace cut across the MBT, the fault trace is also displaced by transverse faults. Paleochannels and multiple levels of strath and fill terraces collectively indicate the river channel's disequilibrium state concerning the ongoing tectonic activity. The cross-cutting relation and displacement pattern of fault traces indicate later phases of tectonic activity.

Shallow tunnels in urban areas are close to adjacent buildings and municipal pipelines. Ground surface settlement (GSS) due to tunnelling can cause damage to those infrastructures surrounded. Many methods have been proposed for evaluating ground settlement induced by tunnelling, including empirical, analytical, numerical and artificial intelligence methods. This paper reviews the proposed methods in detail based on published 677 articles within past ten years. The principles, assumptions and application scope of those methods are summarized and the advantages and limitations of each method are discussed. Since artificial intelligence (AI) become popular in recent few years, the application of AI in the aspect of tunnelling-induced ground deformation is introduced emphatically. Finally, the challenges of ground displacement prediction by machine learning (ML) are clarified and future research directions are suggested.

The Russian-Ukrainian conflict spawned a high-intensity war that shattered decades of peace in Europe. The use of drones and social media elevates open-source intelligence as a critical strategic asset. However, information from these sources is sporadic, difficult to confirm, and prone to manipulation. Here, we use open-access spaceborne remote sensing data to probe the damage to infrastructure on and off the frontline at the city, region, and country-wide scales in Ukraine. Nighttime light data and Synthetic Aperture Radar images reveal widespread blackout and unveil the destruction of battleground cities, offering contrasted perspectives on the impact of the conflict. Optical satellite images capture extensive flooding along the Dnipro River in the aftermath of the breach of the Kakhovka dam. Leveraging visible, near-infrared, and microwave satellite data, we bring to light disruption of human activities, havoc in the environment, and the annihilation of entire cities during the protracted conflict. Open-source remote sensing can offer objective information about the nature and extent of devastation during military conflicts.

Multi-hazard events have received attention globally due to their increasing frequency and severity in recent years. The coastal region of Bangladesh is particularly vulnerable to multi-hazard events induced by tropical cyclones (TC), including coastal flooding, extreme precipitation, extreme winds, and salinity intrusion. These events inflict substantial damage on human lives and property, yet there has been limited effort to quantitatively assess the associated risks. This study aims to investigate the spatial distribution of multi-hazard risks stemming from TC events, employing a Fuzzy Analytic Hierarchy Process (FAHP) approach. Risk is assessed in relation to hazard, exposure, vulnerability, and mitigation capacities in the study area. Various indicators are selected to define each of these four risk components, with weights determined through expert input for FAHP modeling. The results indicate that more than 50% of the area faces multi-hazard risks, with the hazard component exhibiting the highest degree of risk association, followed by exposure, vulnerability, and adaptive capacity. Storm surge-induced flooding is identified as the most prominent hazard during TC events, followed by intense precipitation, extreme winds, and salinity intrusion. Areas characterized by high population density, a large number of vulnerable populations (e.g., those under 15 years or over 65 years), low elevation, and underdevelopment are found to be the most risk prone. Notably, the presence of hospitals, cyclone centers, and effective warning systems in proximity to an area enhances its potential to withstand multi-hazard impacts. Among the 19 coastal districts, Cox's Bazar and Feni are identified as the most risk prone. The framework and findings presented in this study offer valuable insights for the development and prioritization of multi-hazard risk mitigation policies by identifying the most vulnerable zones and the associated risk factors.