Disaster Risk Reduction Strategies Research Articles

Mapping the exposure of tourism to weather extremes: the need for a spatially-explicit gridded dataset for disaster risk reduction

Abstract Tourism is a highly important economic sector worldwide, yet it is often less than optimally represented in terms of detailed spatial information. An accurate spatial representation of tourism can provide valuable insights into the spatial distribution of tourism vulnerabilities and exposure, allowing policymakers to make informed decisions and develop effective strategies for disaster risk reduction and climate change adaptation policies. Here, we stress the need for and propose a first prototype of an open-access spatially-explicit gridded database based on social media data for over 150 different tourism-related classes that depicts tourism density (supply and demand) and perceived satisfaction in Europe. We showcase the potential benefits of such database by mapping the exposure of specific tourism sectors to a range of weather extremes, including floods, windstorms, and heat stress. Based on these results, we argue that a homogeneous spatially-explicit database of tourism is essential to support efficient investments in preparedness and disaster resilience.

Flood risk evaluation of the coastal city by the EWM-TOPSIS and machine learning hybrid method

The frequent occurrence of floods and waterlogging has significantly impacted coastal cities. Effective mapping of flood risk can enhance the precision of disaster risk reduction strategies. However, there is room for improvement in fields such as flood inundation data, evaluation objectivity, and classification refinement. This study, using Xiamen as a case study, advanced flood inundation data accuracy by generating a frequency-based flood inundation map from multi-year remote sensing imagery. This study integrated the EWM-TOPSIS model with a neural network model to evaluate the flood risk. The EWM-TOPSIS model was employed to assess the flood vulnerability and flood exposure, while the multi-class neural network model to simulate the flood hazard. This combined approach reduced subjectivity in the flood risk assessment of Xiamen and achieved a finer level of risk classification compared to traditional binary neural networks. The results indicated that the flood vulnerable areas of Xiamen are concentrated along waterways distant from roads, with high flood exposure in Tong'an and Xiang'an districts. The flood-prone areas in Xiamen are primarily located along the coastal areas characterized by extensive impermeable surfaces. High flood risk areas are mainly distributed in Tong'an and Xiang'an subdistricts, particularly in Xiangping and Xindian. The method developed offers support for accurate flood risk identification and decision-making in cities with limited data resources.

Need Assessment for Coastal Tourism Area in the Face of Tsunami Risk: The Case of Pangandaran

As the fourth world's longest coastline, coastal tourism has become a significant component of Indonesia’s economy. Approximately 57% of this coastline is prone to the deadliest coastal hazard, i.e., tsunami. The progressive development of the tourism industry has created a massive increase in built infrastructure, hotels, roads, electrical and water distribution systems, and an increased number of people, including tourists and tourism workers, in rural coastal tourism areas. Due to the tsunami threat, rural coastal tourism regions' economic and social development faces enormous potential losses in lives and infrastructure and disruption of economic activity, especially for small and medium business enterprises. However, this coastal tourism industry has failed to engage in proper disaster risk reduction strategy and tourism business resilient building in most tourist destination regions in Indonesia. To address these complex problems, this study explores the adaptation of the concept of Business Continuity Plan of a single enterprise to upscale to an area or zone, i.e., the Area Business Continuity Planning, to enhance the holistic disaster-resilient tourism industry in Indonesia, with Pangandaran as the study location. As a newly formed regency, Pangadaran is an emerging super-destination tourism area designated by national and provincial governments. This region experienced a devastating tsunami in 2006, and even today, its coastal communities live under the threat of tsunamis that South Java Megathrust can generate. Based on an in-depth and holistic study, this study finds the Pangandaran coastal tourism resilience level, recognizing critical stakeholders and identifying the collaborative BCP strategies in Pangandaran.  

The Impacts of Multiple Tropical Cyclone Events and Associated Precipitation on Household Income and Expenditures

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards. Damages arise from strong winds, compounded by associated flood-inducing hazards such as heavy rainfall and storm surge. Recent papers have shown that the modelled TC damage estimates fall short of the observed estimates due to the use of wind speed as a sole damage proxy. Damage estimates may be further confounded by inaccurate representations of vulnerability of people and economic sectors, for example, calling for adjusted damage thresholds in less developed regions. This paper evaluates the impacts of compounded TC hazards on household income and expenditure in the Philippines, with adjustments in vulnerability representation drawn from local information. Our results show that the omission of TC-associated precipitation leads to an underestimation of impacts, as well as the number of areas and economic sectors affected by TCs. We find that households cope through a reallocation of budgets and reliance on alternative income sources. Despite extensive public and private disaster risk reduction and management strategies, we still find significant losses in income and expenditures at any number of TC exposure.

An investigation into risk governance processes to encourage behaviour change to reduce disaster risk: A case study of Barbados

Organizations involved in the reduction of risk, emanating from hazardous events, play an important role in influencing the responses of households to reduce disaster risk either by the enforcement of regulations or by encouraging the adoption of best practices. One way this can be done is by examining ways to enhance knowledge exchange, better understanding of household safety behaviours and improved perceptions of risk. Further, micro-level research approaches are needed to examine how organizations involved in risk reduction and households interact in order to understand the contributing factors that hamper effective decision making and actions to reduce disaster risk in small island developing states (SIDS) of the Caribbean.This study investigates how organization's disaster risk reduction (DRR) approaches have incorporated risk perception, safety behaviours, and knowledge into their internal DRR plans. This case study took place in Barbados, a SIDS in the Caribbean. Qualitative data were collected from semi-structured informant interviews (n = 33). Findings of the key stakeholder interviews revealed that most organizations lacked systematic approaches to engage households and lacked clear impact pathways in the theory of change and did not strategically target identified vulnerable population subgroups for the desired behavioural change. There was a noted gap in understanding how risk perception influences and shapes risk and safety behaviours at the household level. Based on the results of this research strategies employed to reduce risk and build resilience can include key ways to integrate how the use of safety culture, and risk perception can enhance knowledge exchange for the development and improvement of place-specific DRR strategies.

Unveiling the Recipe for Disaster Vulnerability: A Multidimensional Analysis in Dumaguete City, Philippines

Disaster vulnerability is not just a condition but a consequence of the interactions of natural and social factors. From this viewpoint, it is imperative to consider both natural and social factors when planning effective disaster risk reduction strategies. This study sought to determine factors that predict disaster vulnerability. Specifically, this research determined the associations between several socio-ecological dimensions (e.g., environmental, social, and economic profile), coping capacity, disaster preparedness, and disaster vulnerability of selected households in Dumaguete city. Using snowball sampling, a descriptive correlational design was used to collect data from self-report surveys of non-probable samples of 150 households from different disaster-prone barangays. Frequency count, weighted mean, and standard deviation were used to describe the data, and a multiple linear regression analysis was done to test the study's hypotheses. Findings show that the respondents manifested moderate levels of coping capacity and disaster preparedness while having high levels of disaster vulnerability. The study revealed that disaster preparedness and coping capacity were negatively correlated to disaster vulnerability. Aside from coping capacity and disaster preparedness, environmental, social, and economic profiles were also noted to predict disaster vulnerability significantly. Environmental profile was the most vital determinant of the participants’ perceived disaster vulnerability. To better prepare for disasters, it is suggested that city disaster risk reduction strategies focus on helping vulnerable barangays develop better adaptive capacities and manage environmental hazards. This could include providing training on essential hazard management and creating income-generating opportunities to offset the adverse effects of disasters.

Multi-hazard could exacerbate in coastal Bangladesh in the context of climate change

Floods and landslides have cascading effects on coastal areas of Bangladesh. This study aims to develop multi-hazard maps (e.g., floods and landslides) for the coastal region, by integrating a genetic algorithm optimizer with Long Short-Term Memory deep learning algorithm (GA-LSTM-DLA), global climate model, and geospatial data. It assesses vulnerabilities to multiple hazards and projects future risks considering the Australian Community Climate and Earth System Simulator Earth System Model 1.5 (ACCESS-ESM1-5) under three climate scenarios, i.e., Shared Socioeconomic Pathways1-2.6, 2-4.5, and 5-8.5 (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The Receiver Operating Characteristic (ROC) curve is used to assess the performance of GA-LSTM-DLA model. According to important feature obtained by random forest (RF) algorithm, most important features for flash, riverine, tidal floods, and landslides are drainage density, rainfall, and geology, respectively. The baseline susceptibility maps for flash, riverine, tidal floods, and landslides are initially recorded as 0.11%, 7.99%, 3.46%, and 0.03%. Projections for the year 2100, under different SSPs, show significant increase, i.e., SSP1-2.6—flash 1.31%, riverine 23.74%, tidal 26.97%, landslides 2.05%; SSP2-4.5—flash 0.12%, riverine 30.97%, tidal 10.23%, landslides 0.18%; SSP5-8.5—flash 0.02%, riverine 17.42%, tidal 6.19%, landslides 0.14%. These projections highlight urgent need for mitigation and adaptation measures against hazards susceptibility, particularly under more extreme socioeconomic scenarios. Overall, the findings of this work are critical for policymakers to develop informed strategies for climate resilience, sustainable development, and disaster risk reduction in the coastal region of Bangladesh.

Adaptive innovation and ethical dilemmas: a participatory action research study amongst cyclone-impacted households in Tamil Nadu, India

PurposeThis paper showcases how the PAR embedded in posthumanist perspectives enabled us to navigate several complexities in the field through methodological situatedness and pluralism. It also attempts to critically outline the drivers and barriers that shaped our capacities to engage with the PAR.Design/methodology/approachThe Tamil Nadu state in the Bay of Bengal along the southeast coast of India is one of the six regions in the world where severe tropical cyclones originate throughout the year. Storm surges in this region are well known for their destructive potential due to strong winds and heavy rainfall. This paper describes our participatory action research (PAR) journey towards strengthening grassroots action by providing access to safe and affordable housing for cyclone-impacted households (CIHs) in the Villupuram district of Tamil Nadu, India. The PAR was guided by an adaptive innovation model (AIM) that draws inspiration from posthumanism, action research and reflective practice traditions.FindingsThe insights from the PAR insist that we must recognise and work with diverse knowledge systems and situated practices to develop meaningful disaster risk reduction (DRR) and climate adaptation strategies. Our approach has to be rooted in the lived experiences of various vulnerable groups, their entanglements with nature and their everyday struggles of interacting with a complex social-ecological system.Originality/valueThis paper is an outcome of a PAR in a cyclone-impacted village in Tamil Nadu, India. The discussions and findings of the paper are original in nature and have not been published elsewhere.

Identifying children’s perception of interior space to the earthquake disaster: A case study of elementary school students in Jakarta

Earthquake disasters affected several physical damages and left traumatic experiences to sensitive groups, especially children. This kind of damage results in after-effect risks from the earthquake. Associated with this condition, the United Nation has published that the number of countries with disaster risk reduction strategies starting in 2015 should be increased. This research is aimed to identify children’s perceptions after the earthquake disaster through virtual settings. The framework used a literature review and a simulation of 3D virtual model testing on a group of elementary school students in Jakarta using a certain model type of room and aperture (window). Colour and window size are the main parameters for data showing the children’s preferences. Potential parameters are expected to be produced as guidance and recommendations on the post-disaster (earthquake-specific) in the future design decision. The parameters are aimed to help decision makers and designers to reach disaster risk reduction, in relation with SDGs on social aspect for the future sustainable development of resilient infrastructure, communities, and cities.

Appraising competency gaps among UNESCO-designated heritage site actors in disaster risk reduction innovations

Communities residing in UNESCO-designated sites, characterised by outstanding universal values, face heightened vulnerability during disasters, necessitating innovative Disaster Risk Reduction (DRR) strategies. The critical role of well-equipped UNESCO site actors in DRR necessary for achieving the goals of broader international frameworks such as Agenda 2030 and the Sendai Framework for Disaster Risk Reduction (SFDRR) warrants this needs assessment study. This study uses a descriptive survey design to assess the competency gaps of UNESCO site actors, including managers and staff, for effective utilisation of DRR innovations (DRRI). Employing the Borich Needs Assessment Model and Ranked Discrepancy Model, an online questionnaire garnered 141 responses from 59 countries. Descriptive statistics, significance tests (at p < .05), correlation tests, Mean Weighted Discrepancy Scores, and Ranked Discrepancy Scores yielded noteworthy findings. Despite recognising the importance of DRRI, respondents demonstrated competence lags, emphasizing the need for tailored training programs. Competency gaps were identified across all 14 listed DRRI, with top priorities including disaster prevention radio, telemetry systems, unmanned aerial vehicles, GIS, remote sensing, resilient materials, and disaster risk insurance. Enhancing competencies in DRRI presents a strategic approach to bolstering disaster preparedness, management, and risk reduction efforts, aligning with global conservation and sustainability goals.

A new regionally consistent exposure database for Central Asia: population and residential buildings

Abstract. Central Asia is highly exposed to a broad range of hazardous phenomena including earthquakes, floods and landslides, which have cause substantial damage in the past. However, disaster risk reduction strategies are still under development in the area. We provide a regional-scale exposure database for population and residential buildings based on existing information from previous exposure development efforts at the regional and national scale. Such datasets are complemented with country-based data (e.g., building census, national statistics) collected by national representatives in each Central Asian country (Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, Uzbekistan). We also develop population and residential-building exposure layers for the year 2080, which support the definition of disaster risk reduction strategies in the region.

Geomorphology mapping and landslide susceptibility for disaster risk reduction and sustainability environment in the Sub DAS Maspo, Mt. Welirang, East Java, Indonesia

Landslides are still problematic for areas with rough surface shapes and high rainfall. Landslides are still causing human life losses, so mitigation efforts for disaster risk reduction must be prioritized. The purpose of this study is geomorphological mapping and landslide hazard mapping as a basis for disaster risk reduction efforts. The method used integrates remote sensing data using geographic information systems. Geomorphology mapping is processed and analyzed using four geomorphological approaches, while for landslide susceptibility maps are analyzed using the Weight of Evidence (WoE) method using existing landslide variables and 17 landslide control factors. The geomorphological mapping results show that in the Maspo sub-watershed, there are 25 landform units based on geomorphological mapping. There are five classes of landslide vulnerability indices, i.e very low index (0.001-0.341) namely 9.38%; low index (0.341-0.471) that is 26.18%; moderate index (0.471-0.584) that is 28.49%; high index (0.584-0.741) that is 23.94% and very high index (0.714-1) that is 12.02%. The accuracy of the landslide hazard map results is 88%, indicating that the landslide hazard map has good accuracy. Dominant landslides of 26.98% and 23.59% occurred in the HS2V1/ME landform, which is the middle slope of the steep hills of the lava eruption of the 2nd Mt. Welirang with moderate geomorphic processes and HS2V1/VSE which is the middle slope of the steep hills of the 2nd eruption of Welirang volcano with the process strong geomorphism. The results of geomorphology mapping and landslide susceptibility can be used as an information base for disaster risk reduction strategies and sustainable environmental management.

Climate Change-Related Disaster Risk Mitigation through Innovative Insurance Mechanism: A System Dynamics Model Application for a Case Study in Latvia

This study explores how the System Dynamics modeling approach can help deal with the problem of conventional insurance mechanisms by studying the feedback loops governing complex systems connected to the disaster insurance mechanism. Instead of addressing the disaster’s underlying risk, the traditional disaster insurance strategy largely focuses on providing financial security for asset recovery after a disaster. This constraint becomes especially concerning as the threat of climate-related disasters grows since it may result in rising long-term damage expenditures. A new insurance mechanism is suggested as a solution to this problem to lower damage costs while safeguarding insured assets and luring new assets to be protected. A local case study utilizing a System Dynamics stock and flow model is created and validated by examining the model’s structure, sensitivity analysis, and extreme value test. The results of the case study performed on a city in Latvia highlight the significance of effective disaster risk reduction strategies applied within the innovative insurance mechanism in lowering overall disaster costs. The logical coherence seen throughout the analysis of simulated scenario results strengthens the established model’s plausibility. The case study’s findings support the innovative insurance mechanism’s dynamic hypothesis and show the main influencing factors on the dynamics within the proposed innovative insurance mechanism. The information this study can help insurance firms, policy planners, and disaster risk managers make decisions that will benefit local communities and other stakeholders regarding climate-related disaster risk mitigation.

A regional-scale approach to assessing non-residential building, transportation and cropland exposure in Central Asia

Abstract. Critical infrastructure has a paramount role in socio-economic development, and its disruption can have dramatic consequences for human communities, including cascading impacts. Assessing critical-infrastructure exposure to multiple hazard is therefore of utmost importance for disaster risk reduction purposes. However, past efforts in exposure assessment have predominantly concentrated on residential buildings, often overlooking the unique characteristics of critical infrastructure. Knowing the location, type and characteristics of critical infrastructure is particularly challenging due to the overall scarcity of data and difficulty of interacting with local stakeholders. We propose a method to assess exposure of selected critical infrastructure and demonstrate it for Central Asia, a region prone to multiple hazards (e.g., floods, earthquakes, landslides). We develop the first regionally consistent exposure database for selected critical infrastructure and asset types (namely, non-residential buildings, transportation and croplands), assembling the available global and regional datasets together with country-based information provided by local authorities and research groups, including reconstruction costs. The method addresses the main known challenges related to exposure assessment of critical infrastructure (i.e., data scarcity, difficulties in interacting with local stakeholders) by collecting national-scale data with the help of local research groups. The analysis also includes country-based reconstruction costs, supporting regional-scale disaster risk reduction strategies that include the financial aspect.

Challenges against the Achievement of Disaster Risk Reduction Strategies in African States

Disaster risk reduction (DRR) strategies play a pivotal role in formalizing and enhancing the efficacy of disaster risk reduction efforts. The overall objective of this study was to assess the progress the African Union member states are making in developing DRR strategies as required by Target E of the Sendai Framework. The study used both qualitative and quantitative approaches where an in-depth desk review of DRR strategies and online questionnaires were administered to 53 respondents. The findings shows about 68 % of the AU member states have national strategies and 35% have sub national strategies but generally there is sluggish progress in updating DRR strategies in accordance with Sendai Framework Target E. An array of formidable challenges has come to light, casting a shadow over the seamless execution of these strategies. Weak technical and institutional capacities, paucity of financial resources, limited decentralization of DRR initiatives, and governance deficiencies emerge as pivotal obstacles that warrant immediate attention. In light of these findings, it is imperative for African governments and their collaborative partners to expedite the development of risk-informed strategies. By doing so, they can successfully actualize the visionary objectives set forth within the Sendai Framework.

Classifying disaster risk reduction strategies: conceptualizing and testing a novel integrated approach

BackgroundAlthough disaster risk reduction (DRR) addresses underlying causes and has been shown to be more cost-effective than other emergency management efforts, there is lack of systematized DRR categorization, leading to insufficient coherence in the terminology, planning, and implementation of DRR. The aim of this study was to conceptualize and test a novel integrated DRR framework that highlights the intersection between two existing classification systems.MethodsGrounded theory was used to conceptualize a novel DRR framework. Next, deductive conceptual content analysis was used to categorize interventions from the 2019 Cities100 Report into the proposed DRR framework. The term “connection” indicates that an intervention can be categorized into a particular section of the novel integrated approach. A “connection” was determined to be present when the intervention description stated an explicit connection to health and to the concept within one of the categories from the novel approach. Further descriptive statistics were used to give insight into the distribution of DRR interventions across categories and into the application of the proposed framework.ResultsThe resulting framework contains nine intersecting categories: “hazard, prospective”, “hazard, corrective”, “hazard, compensatory”, “exposure, prospective”, “exposure, corrective”, “exposure, compensatory”, “vulnerability, prospective”, “vulnerability, corrective”, and “vulnerability, compensatory”. The thematic analysis elucidated trends and gaps in the types of interventions used within the 2019 Cities100 Report. For instance, exposure-prospective, exposure-compensatory, and vulnerability-compensatory were the most under-utilized strategies, accounting for only 3% of the total interventions. Further descriptive statistics showed that upper middle-income countries favored “hazard, corrective” strategies over other DRR categories while lower middle-income countries favored “exposure, corrective” over other DRR strategies. Finally, European cities had the highest percentage of DRR connections (51.39%) compared to the maximum possible DRR connections, while African cities had the lowest percentage of DRR connections (22.22%).ConclusionsThe study suggests that the proposed DRR framework could potentially be used to systematically evaluate DRR interventions for missing elements, aiding in the design of more equitable and comprehensive DRR strategies.

Uncertainty Analysis of the Prediction of Massive Ash Fallout From a Large Explosive Eruption at Sakurajima Volcano

AbstractVolcanic ash hazards present life‐threatening dangers to populations near volcanoes during large explosive eruptions. Vulnerable infrastructures demand a comprehensive disaster risk reduction strategy to protect residents from enormous ashfall accumulations. To prepare for the next large eruption of Sakurajima volcano, authorities in Kagoshima City are developing a countermeasure plan utilizing ash dispersal prediction 24 hr before an eruption. However, the absence of large eruptions in the last century makes it challenging to confirm the accuracy of predictions for hazard area designation. To ensure established protocols are effective, uncertainties in ashfall predictions must be addressed, enabling authorities to make appropriate responses. We simulated the previous large eruption of Sakurajima volcano using multiple wind forecast lead times as historical predictions from July 2018 to December 2022. The uncertainty in prediction results was evaluated by comparing simulation outputs with validation data from the ash dispersal data set. We examined uncertainty in hazard area assignment and its variation depending on risk items, wind field states, and the influences of seasonal patterns and events. Updating ashfall predictions with improved wind forecasts reduces uncertainty for all risk items and increases the precision of identified hazard zones. Furthermore, uncertainty levels are influenced by seasonality and can shift significantly with varying wind strengths controlling ash dispersal process. Providing uncertainty information is vital for decision‐making during ash fallout events, and it is recommended to update response decisions 12 hr after the initial prediction. This study's outcomes will aid in developing better disaster risk management strategies, focusing on volcanic ash hazards.

Earthquake Disaster Risk Reduction Strategies in Pakistan

The site of Pakistan in a region which is seismically active lends urgency to earthquake disaster risks. Seismic susceptibility implied by historical earthquake tremors continues to emphasize needs for sound disaster risk management approaches. This study seeks to critically analyze the current earthquake risk picture in Pakistan, a detailed appraisal of existing Disaster Management mechanisms and systems practice as well as implementation of policies. Using global standards, guides and practices as well as case studies, the study relative to best practice in earthquake risk reduction will be identified with a focus on application potential within Pakistan. Additionally, seismic zoning, vulnerability assessment and exposure analysis will be studied in the research to perform a comprehensive risk assessment of earthquake for the country. Through analyzing the existing challenges and gaps in the system, this paper is going to propose specialized risk reduction strategies for earthquake disaster that will integrate early warning systems implementation into building code implementing communities. The aim is as such to provide workable recommendations for the policymakers and stakeholders in order to lay down a resilient prepared response strategy towards an earthquake disaster risk reduction plan in Pakistan.

Landslide Susceptibility Assessment in Nepal’s Chure Region: A Geospatial Analysis

The Chure Hills, already vulnerable due to their fragile nature, face increased landslide risk, prompting the need for reliable susceptibility assessment. This study uses Poisson regression modeling to assess landslide susceptibility in two highly susceptible districts of the Chure region. Variance inflation factor (VIF) tests were conducted to ensure robustness, indicating no multicollinearity among the variables. Subsequently, Poisson regression analysis identified eight significant variables, among which geology, lineament density, elevation, relief, slope, rainfall, solar radiance, and land cover types emerged as important factors associated with landslide count. The analysis revealed that higher lineament density and slope were associated with lower landslide counts, indicating potential stabilizing geological and topographical influences. The categorical variable, namely geology, revealed that middle Siwalik, upper Siwalik, and quaternary geological formations were associated with lower landslide counts than lower Siwalik. Land cover types, including areas under forest, shrubland, grassland, agricultural land, water bodies, and bare ground, had a substantial significant positive association with landslide count. The generated susceptibility map that exhibited a substantial portion (23.32% in Dang and 5.22% in Surkhet) of the study area fell within the very-high-susceptibility categories, indicating pronounced landslide susceptibility in the Dang and Surkhet districts of the Chure hills. This study offers valuable insights into landslide vulnerability in the Chure region, serving as a foundation for informed decision-making, disaster risk reduction strategies, and sustainable land-use and developmental policy planning.

Coping with disasters: changing patterns of disaster risk reduction activities in the southwestern coastal areas of Bangladesh

Bangladesh is exposed to frequent natural disasters such as floods, cyclones, tidal surges, and earthquakes. To improve resilience, the country has implemented multisectoral and muti-level national interventions based on international guidelines over the past few years. As a result, local people have become more knowledgeable about and adept at coping with disasters. While previous studies have focused on the causes and consequences of this development, this study examines the trend of successful disaster risk reduction (DRR) interventions through qualitative research in the southwest coastal area of Bangladesh. The authors performed 10 in-depth interviews, four focus group discussions, non-participatory observatory notes, and gathered 36 photographs of the surrounding landscapes in two selected villages of Dacope Upazila and Mongla Upazila, Khulna Division of Bangladesh. This study has suggested that coastal residents have changed their actions through DRR due to a range of awareness programs led by governmental and non-governmental organizations. While a top-down approach has improved early warning, disaster preparedness, and safer environments, a bottom-up approach should be considered to incorporate effective local DRR activities such as kinship network support. These findings suggest that both new and traditional disaster-coping activities should be integrated into more effective DRR strategies.