Natural Hazards Research最新文献

Floods are major Extreme Weather Events (EWEs) that are more frequent and intense. Floods has multifarious dire impacts on human health, but health implications of floods are limitedly examined from a gender lens, particularly in the context of developing countries, like Bangladesh. Floods periodically hit in Bangladesh. The 2017 was a catastrophic year for Bangladesh. The year experienced two consecutive floods that were more catastrophic in the last couple of decades and direly affected 24 districts of the country. The floods resulted in health stress and intensifying exposure to manifold health vulnerabilities. Our study aimed to investigate gendered health complications caused by the floods and the impacts of the confluence of the floods and vulnerabilities relating to water, sanitation, health care facilities on reproductive health. To explore gendered dimensions of health, we conducted 280 household surveys, 4 Focus Group Discussions, 4 In-Depth Interviews, and 6 Key Informant Interviews within the framework of mixed-method research in a northern flood-prone district named Jamalpur. Our findings showed that 84.6% of the respondents stated water gets polluted during floods, and 69.6% identified polluted water as a major challenge while collecting water during floods. Due to living with polluted floodwater, fever (66.4%) and diarrheal diseases (55.4%) were most common among women. In respect to reproductive health, 75% of the females reported improper menstrual management causing mental shocks and vaginal infections; over 66.4% females noted remaining without any measures. To mitigate health vulnerability, majority of the rural women (78.6%) encountered challenges – including the dearth of available medicine and poor transportation and communication. Health vulnerability also increased when poor communities failed to afford the cost of medicine because of poor economic condition and food insecurity. Consequently, our study recommends for fostering health education and the immediate deployment of health care facilities on an emergency basis to reduce health complications, especially among marginal groups (e.g., women and children). Future research can explore how the intersection of economic insecurity and flood whet differential health complications among poor and non-poor.

This paper presents a comprehensive seismic hazard assessment for Guwahati city, located in the northeast region of India. The earthquake data considered for the study is from 1762 to 2020, which was sourced from the published data of various seismological agencies. The fault information comprises of the latest studies and Seismotectonic Atlas (SEISAT) data. The density of earthquakes close to the faults was used to define the fault zones. The G-R relationship was utilized to calculate the seismicity parameters of the identified faults. We have used PSHA and DSHA to estimate the ground motion parameters such as peak ground acceleration and spectral acceleration at various probabilities of exceedance to calculate the level of seismic hazard. The results indicate that the seismic hazard in Guwahati is moderate to high, with several active faults in the vicinity and a high potential for strong ground motions. This study includes identifying the controlling source for Guwahati and plotting the seismic hazard curve and uniform hazard spectra for various probabilities of exceedance, which will give a basic idea of the seismic hazard of the city. The findings of this study can be used as a basis for earthquake risk reduction and mitigation strategies in Guwahati.

There has been a surge in research on adaptation planning to address climate change and its effects. This study conducted a bibliometric analysis of the keywords “adaptation planning” and “climate change” to determine the level of research being undertaken using a proposed Advanced Bibliometric Analytical Framework (ABAF). ABAF intends to overcome the inconsistency and vagueness surrounding the existing bibliometric analytical frameworks. Three types of analyses, namely performance analysis, rank analysis, and scientific mapping, were carried out on a dataset of 1087 research articles retrieved from the Web of Science database. The study found contributions from 1515 institutions and 116 countries. Most studies were published in English and Chinese languages only. An upward trend was observed in the number of publications per year, with 135 being the highest number recorded in 2021, emphasizing SDG13: Climate Action, followed by SDGs 6, 15, and 14. Findings show adaptation planning as a trending discourse in the impact reduction of climate extreme events. The results of this study can serve as a foundation for future research on adaptation planning for climate change. Additionally, ABAF can be applied in any bibliometric analytical study, and the framework could be expanded to include additional analysis typologies and metrics to enhance its comprehensiveness.

Over the last two decades, urban floods and their impacts have been on the rise worldwide, owing to both climatic changes and human activities. The present study examines different at-risk elements, such as residential, commercial, and critical facilities, to evaluate their multi-components of vulnerability to urban floods in Peshawar, Pakistan. Based on the impacts of urban floods, the weightage of each component of the vulnerability for the selected elements at risk is defined. This study presents and uses the modified Fisher's ideal quantity index to combine the different vulnerability components into a single value. Additionally, the Patnaik and Narayan vulnerability index is employed to generalize sector-wise vulnerabilities across the study area. The results show that the old physical infrastructure of commercial and manufacturing units in the Kohati Gate area is highly vulnerable to urban floods, while the residential units are the least susceptible due to their distanced location from the drainage system. In Hayatabad, encroachments along the torrent's sides, affecting housing and educational institutions, contributed to increased vulnerability to urban floods, despite their relatively lower physical vulnerability. The study provides a new platform for understanding the multi-components of vulnerability to urban floods and tackling the challenges posed by urban floods effectively.

Climate vulnerability in the Indian region becomes a major concern due to the frequent hydro-meteorological extreme events throughout the year. The number of extreme rainfall events (ERE) associated with monsoon, thunderstorms and short-spanned local cloudbursts which are mainly ranges from a few hours to a few days, has increased in recent decades over the subcontinent. There is a need to quantify these high impact weather events and to understand the spatio-temporal dynamics and associated physical processes for the real time prediction for pro-active disaster management. This review paper highlights the various research works carried out and suggests the need of observation, modelling efforts for simulation/prediction of the EREs in the continental India. The works starting from cloudburst in the Himalayan region (Leh, Uttarakhand, Himachal Pradesh) to the heavy rainfall in Kerala, Bangalore, Mumbai, Chennai etc. as presented by earlier researchers are being reported in this compilation. The ERE intensity and frequency distribution in India are being analyzed using IMD gridded rainfall observation for 72 years. The analysis indicates the increasing trend in the intensity of daily rainfall during the ERE in the subcontinent. The current state of research in the multi-scale study of the ERE as well as their future changes based on climate model outputs are reviewed and the challenges are also reviewed. Evaluation of the capability of the state of art meso scale models like Weather Research and Forecasting (WRF) model for the simulation of such events at high resolution using the high-performance computing and the assimilation techniques are also emphasized in the recent research in this field. Along with the impact of large-scale physical processes like El Nino Southern Oscillations (ENSO), also the sensitivity of the urbanization, topography in the simulation of the convective meso-scale events is being presented and which indicated the down-scaled data are the best tool for the ERE research. This review will surely help the interdisciplinary researchers for the extreme analysis of the high impact hydro-meteorological disaster events.

Flooding continues to ravage communities and leave societies driven by quest towards a more likely solution to flood threats. The need to accommodate both the provision of fundamental human needs and the core values and functions of the natural environment, for instance, controlling floods, puts emphasis on sustainability and illustrates the worth of ecosystem-based approach to flood risk management in locations inhabited by almost half a million people in danger of flooding. This study aims to assess the awareness of ecosystem services in the Ogun State of Nigeria and how a sustainable appropriation of the natural resources can aid local flood risk mitigation and control. The study employed a mixed-method approach through a thorough literature search to gather secondary data and a semi-structured questionnaire to source primary data from a population of 1483 participants in the study area. From the analyses, a considerable proportion of the participants (∼70%) possess a profound knowledge of flood risk and are aware of local flood abatement and ecosystem services. Based on all measured variables, only less than half of the sampled respondents identified with the idea of ecosystem, although just about 43.6% of the sampled population failed to grasp that exploring more efficient ways of using natural resources can aid in tackling flooding in the study area. With this outcome in mind, the area under study can only attain a holistic flood risk management framework by making ecosystem-based flood risk management the centrepiece of local flood risk mitigation policy and practice. This research suggests a new angle to help incorporate ecosystem service into local FRM, fortify the resilience of communities and adapt indigenous methods and assets for flood risk mitigation economy and regulation.

Bangladesh is highly vulnerable to the adverse impacts of extreme sea levels (ESLs) because of its geographical location with low-lying coast. In addition, high discharge of huge rain water to the nearby coast may influence the ESL. The effects of different meteorological forcings like atmospheric pressure, wind-induced wave, and surges to ESL have been investigated intensively around Bangladesh. However, the role of surface rainfall to the ESL along the coast of Bangladesh remains unknown. In this study, the role of surface rainfall to the ESL was investigated for Cox's Bazar area along the eastern coast of Bangladesh. The ESL events were selected by applying the threshold of 500 ​mm height. The variations in SLA during seven days in prior to the ESL was predicted by multivariate regression using selected climatic variables of rainfall, sea level pressure, and wind. It was revealed that the prediction of ESL considering the contribution of rainfall outperforms the predictions without rainfall. The significant contribution of rainfall for prediction of ESL at Cox's Bazar, reflecting the hilly landscape at Cox's Bazar where a clear response of high surface runoff is expected. The findings suggest that the rainfall have an important effect to the ESL change along the eastern coast of Bangladesh. Therefore, incorporating rainfall effect is essential for better prediction of the ESLs which helps coastal management and reduction of hazards.

Social vulnerability assessment is a dynamic process, which varies from place to place. In the present study, the social vulnerability index (SVI) of Malda district has been prepared because of several impacts of flood inundation. The flood inundation layer has been generated using multi-temporal remote sensing data. The flood inundation layer is prepared from real-time Synthetic Aperture Radar (SAR) data. For social vulnerability assessment, the most efficient indicators are household composition, age & sex composition, and underprivileged population (SC& ST). Economic and educational data has been collected from the Census of India Handbook 2011. All these data are combined with the district's village database on the GIS platform. The weightage overlay analysis method is applied to generate the social vulnerability index of the study area, where the multi-influencing factor (MIF) technique has been used for determining the influencing factors. The social vulnerability index has categories into Very High (4%), High (37%), Moderate (32%) and Low (27%). The social vulnerability index is being further intersected with the flood inundation layer to build a database for the most vulnerable area of this district. It has been observed that 70 villages are in Very High zones, 662 villages are in High, 578 villages are in Moderate and 479 villages are in Low zones. This study will help the disaster manager and stakeholders about the vulnerable situation of the study area and also depict the importance of geospatial techniques in disaster management.

Natural hazards often pose a considerable amount of social vulnerability which is the function of exposure, sensitivity and adaptation. Livelihood vulnerability assessment (LVA) benefits site-specific resilience building and disaster management. There are two popular indices of LVA – (1) the livelihood vulnerability index (LVI) of the Intergovernmental Panel on Climate Change (IPCC, 2007) and another method by (2) Hahn et al. (2009). The study intends to reveal the index that is more suitable to address the flood-induced livelihood vulnerability of the rural communities of the Mayurakshi river basin, India. To this end, the nature of exposure, adaptive capacity and sensitivity involving 35 parameters are measured mainly based on the primary data collected from a questionnaire survey executed over 2382 households spreading over 43 villages from five community development (C.D.) blocks. Moreover, the annual flood reports, district census reports, topographical maps, and satellite images are used as secondary data. The result shows that as per Hahn et al.’s LVI, Khargram (LVI- 0.41) is the most vulnerable block while Nabagram (LVI- 0.35) is the least vulnerable block. However, according to IPCC-LVI, Bharatpur-I has the highest LVI (0.02) and Burwan has the lowest LVI (-0.09). It is observed that exposure exhibits a strong positive correlation with IPCC-LVI and adaptive capacity also maintains a similar correlation with Hahn et al.’s LVI. Interestingly, Kandi is the most exposed block (score: 0.59) with a high adaptive capacity (score: 0.47) resulting in its exclusion from the high LVI category of both methods. This comparative performance assessment underscores the significance of the work before the decision-makers in preparing microscale disaster management plans.

The country wide lockdown implemented during 27th April to 14^th June 2021 in order to prevent the spread of COVID-19 during the second wave in India. Effect of the restricted lockdown resulted in improved air quality. This study focuses on analyzing the spatio-temporal distribution analysis of major air pollutant concentration over Bangalore city in India. The inverse distance weighting (IDW) method is implemented for the spatial analysis in order to quantify the distribution of the pollutant concentrations at each location in the Urban city of Bangalore. The research considers the distinct periods of pre-lockdown and lockdown during the second wave of COVID-19 pandemic in 2021 to investigate the impact of reduced human activities on air quality over the city. The study mainly utilizes the air pollution data collected from Central Pollution Control Board (CPCB) monitoring stations across Bangalore, including measurements of pollutants such as PM_2.5, PM₁₀, O₃, NO₂, SO₂, and CO. The IDW method is implemented to create the high-resolution pollution concentration maps for both the pre-lockdown and lockdown periods. This spatial distribution provides valuable insights into the variations in the pollution levels though out the Bangalore city. The comparative analysis of the concentration maps reveals significant changes in air pollution levels between the two periods; similarly, the temporal weekly average analysis also witnessed negative anomalies during the lockdown weeks. The results indicate substantial reductions in pollutant concentrations during the second wave COVID-19 lockdown, attributed to decreased vehicular emissions, industrial activities, and construction operations. The pre-lockdown period serves as a baseline for assessing the improvements in air quality during the lockdown. The spatio-temporal modeling approach enhances our understanding of the distribution patterns of air pollutants across the Bangalore metropolitan city. The findings underscore the potential benefits of implementing sustainable strategies to maintain improved air quality even after the pandemic subsides.