Flood havoc during 2019 in the Sangu River basin caused widespread damage to residents, crops, roads, and communications in parts of hills in Bangladesh. Developing flood hazard maps can play an essential step in risks management. For this purpose, this study assessed 12 hydro‐geomorphological factors, namely, topographic wetness index, elevation, slope, extreme rainfall, land‐use and land‐cover, soil type, lithology, curvature, drainage density, aspect, height above the nearest drainage, and distance from streams. Maps prepared by individual application of the Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP) exhibit validation scores ranging from 0.77 to 0.79. It is found that the ANP‐based model under 1‐day maximum rainfall denotes a reliable hazard map presenting comparable accuracy to the field results. The hazard map under 100‐year return periods shows that a total of 0.71 million population living downstream is prone to “very high” flood because of its lowland morphology, mild slope, and high drainage density. Alarmingly, 39% of roads, 43% of farming lands, and 25% of education buildings are observed to lie in the highest flood‐prone area. Details on subdistrict level exposures have the potential to serve the decision‐makers and planners in site selection for flood management strategies and setting priorities for remedial measures.
A number of cities in Europe's deltaic and coastal regions, such as the London metropolis, Hamburg and Dordrecht, share in part similar challenges such as (re)development activities and expansions onto floodplains and they recognize the need for new planning approaches to manage actual and future flood risks in these areas. The tendency is now to look for new ways to distribute responsibilities between different types of stakeholders, so as to take advantage of different initiatives over differing spatial scales, from the catchment level down to the individual building level. In this respect, there is a clear need to include resilience measures taken at the lowest spatial level as part of a top-down and bottom-up approach. This kind of measure comprises flood proofing of buildings and associated infrastructure as well as adapting building activities to the risk. The extent to which such measures will be provided will probably be dictated by micro and macro economic factors. However, as of yet information on their performance is limited, which particularly holds true for the Dutch context. Consequently, the economic efficiency of these technologies is unclear.In this paper a new database containing economic information involving the costs and benefits for implementing these measures is presented. Flood damage databases have been constructed from a synthesis of all data available from both secondary sources, such as the ABI and FEMA database, and from the real experience of floods. The data is built up from knowledge about the effect of flood water on both the fabric of the building and its contents. In order to investigate the efficiency of private flood proofing of buildings, benefit cost analyses for different building types and elevations are conducted for a case study in Dordrecht, the Netherlands. The benefit for each damage reduction strategy is calculated by estimating the difference in expected annual losses compared to the traditional way of building.
Remotely sensed data has the potential to monitor natural hazards and their consequences on socio-economic systems. However, in much of the world, inadequate validation data of disaster damage make reliable use of satellite data difficult. We attempt to strengthen the use of satellite data for one application -flood index insurance -which has the potential to manage the largely uninsured losses from floods. Flood index insurance is a particularly challenging application of remote sensing due to floods' speed, unpredictability, and the significant data validation required. We propose a set of criteria for assessing remote sensing flood index insurance algorithm performance and provide a framework for remote sensing application validation in data-poor environments. Within these criteria, we assess several validation metrics -spatial accuracy compared to high-resolution PlanetScope imagery (F1), temporal consistency as compared to river water levels (Spearman's ρ), and correlation to government damage data (R 2 ) -that measure index performance. With these criteria we develop a Sentinel-1 flood inundation time series in Bangladesh at high spatial (10m) and temporal (~weekly) resolution and compare it to a previous Sentinel-1 algorithm and a MODIS time series used in flood index insurance. Results show that the adapted Sentinel-1 algorithm (F1avg=0.925, ρavg=0.752, R 2 =0.43) significantly outperforms previous Sentinel-1 and MODIS algorithms on the validation criteria. Beyond Bangladesh, our proposed validation criteria can be used to develop and validate better remote sensing products for index insurance and other flood applications in places with inadequate ground truth damage data.
Purpose The coastal zone of Bangladesh that is in the front line of the battle against climate change faced over 200 natural disasters in the past 40 years, and most of the disasters were cyclones. The inevitable cyclone shelter (CS), the backbone of disaster management (DM), provides short-term safety for the disaster victims in Bangladesh. This study aims to explore the community-based limitations and sustainable development features of CSs including the gender issues. Design/methodology/approach A questionnaire survey was carried out among 230 community people to identify the requirements and sustainable development features of CSs. A field visit was carried out in 23 CSs to capture its existing facilities. Key informant interviews were conducted in the office of Upazila Engineers to strengthen survey data. Findings This research found that the plan of CSs, quality of construction, capacity, facilities, entrance and exit, space allocation, management and policy were not capable enough to fulfill the needs and requirements of the community people. Due to lack of separate facilities, women and girls avoided shelters for fear of sexual and mental harassment in CSs, as they had experiences in the earlier events of cyclones. Insufficient facilities discourage community from using the shelters. Research limitations/implications Women and girls were shy to share their experience in CSs. The historical data were limited in the study area. To the best of the authors’ knowledge, this research presents the actual community-based outcome. During CCRIP training program, the authors met 3,625 community people, and participatory discussions were made to explore the participants’ experiences and perceptions about the sustainable development of CSs. Practical implications South-Asian coastal zones are prone to natural, quasi-natural hazard and disasters, where shelters are required for protecting lives of community people during such disasters such as cyclones, storm surges, and floods. Therefore, this study can help in making sustainable development decisions in terms of constructing shelters in disaster-prone countries like Bangladesh. Social implications The outcomes of this investigation are useful for uplifting psychosocial status to protect lives during disasters such as cyclones, storm surges and floods and increase accessibility to shelters, and users will consider CSs as a social asset. In turn, the acceptability of CSs into community level are expected to be increased for combating against cyclones, storm surges, and floods. Originality/value This study introduces the bottom-up approach that refers to the community-based decision-making to identify the limitations and sustainable improvement of CSs. This research contributes to bridging the gaps between decision-makers and users of CSs. From the authors’ field experience, it can be said that this is the first fieldwork regarding the objectives.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.