Joint probability risk modelling of storm surge and cyclone wind along the coast of Bay of Bengal using a statistical copula

Bushra, Nazla; Trepanier, Jill C.; Rohli, Robert V.

doi:10.1002/joc.6068

Cited by 25 publications

(17 citation statements)

References 102 publications

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“…The participants felt that these regular phenomena are more prevalent during the monsoon season, which causes land loss and shoreline erosion. In addition to these regular phenomena, the recent increase in the frequency of coastal cyclones and in the intensity of storm surge (Bushra, 2016;Bushra et al, 2019) and tidal flooding have accelerated the erosional process along the coast. As these phenomena destroy the vegetation coverage, sand dune fields, and sand piles along the coast, the erosional effects of regular waves, currents, and tides are exacerbated.…”

Section: Application Of Pra Toolsmentioning

confidence: 99%

Technical and Social Approaches to Study Shoreline Change of Kuakata, Bangladesh

et al. 2021

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In recent years, shoreline determination has become an issue of increasing importance and concern, especially at the local level, as sea level continues to rise. This study identifies the rates of absolute and net erosion, accretion, and shoreline stabilization along the coast of Kuakata, a vulnerable coastal region in south-central Bangladesh. Shoreline change was detected by applying remote sensing and geographic information system (RS-GIS)-based techniques by using Landsat Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) satellite images at 30-m resolution from 1989, 2003, 2010, and 2020. The band combination (BC) method was used to extract the shoreline (i.e., land-water boundary) due to its improved accuracy over other methods for matching with the existing shoreline position. This study also used participatory rural appraisal (PRA) tools which revealed the societal impacts caused by the shoreline changes. Coupling RS-GIS and PRA techniques provides an enhanced understanding of shoreline change and its impacts because PRA enriches the RS-GIS outcomes by contextualizing the findings. Results show that from 1989 to 2020, a total of 13.59 km2 of coastal land was eroded, and 3.27 km2 of land was accreted, suggesting that land is retreating at about 0.32 km2 yr–1. Results from the PRA tools support this finding and demonstrate that fisheries and tourism are affected by the shoreline change. These results are important in Kuakata, a major tourist spot in Bangladesh, because of the impacts on fisheries, recreation, resource extraction, land use planning, and coastal risk management.

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Section: Application Of Pra Toolsmentioning

confidence: 99%

Technical and Social Approaches to Study Shoreline Change of Kuakata, Bangladesh

et al. 2021

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“…Bangladesh is very vulnerable to climate change due to its geographical location and is considered to be one of the most natural hazard-susceptible countries in the world [14][15]. It is regularly affected by tidal floods and flash floods, cyclones, coastal erosion, storm surges, soil salinity, thunderstorms with or without hail, droughts, and lightning that cause an enormous loss of life and property and, very importantly, significantly affect agricultural productivity [16].…”

Section: Introductionmentioning

confidence: 99%

Determinants of Farmers’ Risk Perceptions of Hailstorms in Northern Bangladesh: Is Adaptive Capacity the Major Concern?

Raihan¹,

Basu²,

Onitsuka³

et al. 2021

Pol. J. Environ. Stud.

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Extreme weather events (EWEs) such as hailstorms are an increasing threat to agriculture worldwide. To develop successful and efficient hailstorm risk management policies, it is important to understand the composition of farmers' hailstorm risk perceptions. This study aims to identify the determinants of these risk perceptions. This is done by collecting pertinent information on the perceptions of risk, farm traits, adaptive capacity, and various other personal characteristics from farmers' households in hailstorm-oriented areas of northern Bangladesh. By analyzing the explanatory power of various risk factors using the binary logistic regression model, this study reveals that the hailstorm risk perceptions of farmers are embodied by subjective risk factors, such as their perceived control of hailstorm risk, and their personal circumstances. Their perceived resources for tackling hailstorm risk are the most significant predictor variable of hailstorm risk perceptions. Marginal and smallholder farmers are very vulnerable and perceive more risk than is the case with the medium-holder and large-holder farmers, owing to the lack of a compensation policy after the occurrence of hailstorms. The relevant authorities should pay urgent attention to managing hailstorm risks by developing adequate adaptive capacity among farmers in northern Bangladesh.

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“…Therefore, it is highly important to assess the storm surge hazard for levees, and to determine a reasonable levee elevation for the prevention and mitigation of such marine-related disasters in coastal areas. The method usually used to assess storm surge disaster hazard is based on regional disaster system theory [11][12][13][14][15]. The product (in this case, the maximum water level) is then used by government decision makers, insurance companies, and vulnerable communities [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Storm Surge Hazard Assessment of the Levee of a Rapidly Developing City-Based on LiDAR and Numerical Models

et al. 2020

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Rapidly developing cities could require an urgent hazard assessment to ensure the protection of their economy and population against natural disasters. However, these cities that have rapidly developed should have historical records of observations that are too short to provide sufficient data information for such an assessment. This study used ocean numerical models (i.e., Finite-Volume Community Ocean Model (FVCOM) and Parabolic Mild-Slope Wave Module (MIKE 21 PMS) to reconstruct data for a storm surge hazard assessment of the levee at Weifang (China). LiDAR (Light Detection and Ranging) data were also used to obtain 3D point cloud data and the structure of the levee. The designed levee height was calculated based on the simulations and 3D point cloud data, and the results were compared with measured heights to evaluate whether the levee is sufficiently high to satisfy the safety requirement. The findings of this work will enhance the marine disaster prevention capacity of the region and could help reduce economic losses associated with marine-related disasters. The results could also provide support for future work on disaster prevention in the field of coastal marine engineering.

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Joint probability risk modelling of storm surge and cyclone wind along the coast of Bay of Bengal using a statistical copula

Cited by 25 publications

References 102 publications

Technical and Social Approaches to Study Shoreline Change of Kuakata, Bangladesh

Technical and Social Approaches to Study Shoreline Change of Kuakata, Bangladesh

Determinants of Farmers’ Risk Perceptions of Hailstorms in Northern Bangladesh: Is Adaptive Capacity the Major Concern?

Storm Surge Hazard Assessment of the Levee of a Rapidly Developing City-Based on LiDAR and Numerical Models

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