Disaster Risk Reduction Strategies Research Articles

Spatiotemporal evolutionary patterns and driving factors of vulnerability to natural disasters in China from 2000 to 2020

Vulnerability is one of the most important drivers of risk, and efforts in reducing vulnerability have been shown to be an essential strategy for disaster risk reduction (DRR). However, for those developing countries experiencing rapid urbanization, like China, poor understanding of the dynamics of vulnerability has hindered the achievement of DRR goals as set out in the Sendai Framework. Therefore, this study aims to investigate the spatiotemporal evolution of human and economic vulnerability for China from 2000 to 2020, and further explore the impacts of socio-economic development and disaster risk management on vulnerability. The results show an overall declining trend for disaster-related fatalities, but an increasing trend for direct economic losses. Significant regional and provincial disparities of vulnerability are observed: both human and economic vulnerability are highest in western China, modest in central China, and lowest in eastern China. Both human and economic vulnerability to natural disasters is steadily declining for the period 2000 to 2020. Social development and hazard risk management level are found to have significantly negative effects on human and economic vulnerability, while significant effect of economic growth is not detected in our analysis. Urbanization rate and education level are the most important factors in shaping both human and economic vulnerability. Expenditures of DRR, an indicators of risk management, is also found to be a significant determinator of vulnerability. Our findings are useful in informing effective national and regional DRR policy, and can also be generalized to other developing counties with situations similar to those of China.With respect to economic vulnerability—represented by direct economic losses per trillion GDP—the average value for China in last 21 years is 7.17 billion RMB. In terms of overall trends, the 5-year moving average of economic vulnerability decreased from 12.2 billion RMB to 4.2 billion RMB in the period 2000 to 2020, a decrease of 65.6%. Although significant declining trends are also observed for Western, Central and Eastern China, the levels of economic vulnerability in the three regions are quite different. Average economic vulnerabilities for Western, Central and Eastern China over the past two decades are 17.2, 9.1 and 3.4 billion RMB, respectively, which demonstrates that Western China is the most prone to economic damages, while Eastern China is least likely to be economically disrupted. This regional disparity is also consistent with the regional distributions of annual reported direct economic losses from 2000 to 2020. Regarding the overall trends of economic vulnerability for the three regions, the 5-year moving average of economic vulnerability for Western China decreased from 16.0 to 6.3 billion RMB, a decrease of 60.6%; that of Central China, from 22.8 to 7.2 billion RMB, a decline of 68.4%; and that of the Eastern China, from 6.1 to 2.1 billion RMB, a decline of 65.6%.

Assessing vulnerability in ethnic Munda community: A study on a cyclone-prone area of Bangladesh

Despite the much research on cyclone vulnerability in Bangladesh, few papers have addressed the assessment of cyclone vulnerability. Furthermore, there has been no study of the vulnerability of the Munda minority in the Southwestern part of Bangladesh. The Sundarbans, the Gorai River, the Rupsa-Pasur River, and the coastline region are visible in Bangladesh's Southwest. It is often referred to as the Ganges Tidal Plain and consists of a delta that is only partially active. Numerous creeks and canals run through it. This study assesses the vulnerability of the Munda community to cyclones using 28 social, economic, physical, institutional, and cultural indicators. After the cyclone Aila, the education level of 84 Munda households in Gabura and Munshiganj Unions of Shyamnagar Upazila, Satkhira District, increased. Many members of the Munda community live in poverty (less than US$100 monthly income). About 70% of them rely on agriculture and fishing as their primary source of income. They also have alternative sources of income, such as daily labor. However, they were physically vulnerable. Only 7% of Munda houses were semi-pucca (partially concrete houses). Additionally, 85% of Munda houses were built over a decade ago. Cyclones severely damaged approximately 89% of houses in the past. Many (88%) did not have access to proper sanitation. The physical vulnerability was also found to be significantly greater (P < 0.05) in Gabura Union (0.54 ± 0.09) than in Munshiganj Union (0.48 ± 0.13). However, they reported strong institutional support for disseminating cyclone warning messages, information on cyclone shelters, and evacuation procedures during cyclone emergencies. National and international disaster risk reduction strategies should encompass all people of all races, ethnicities, and nationalities.

Outdated regulations and institutional vulnerability: Hydrological risk management in Málaga's municipal planning

Málaga, a Mediterranean region, is increasingly prone to water-related risks, a situation compounded by the impacts of climate change. Urban development practices over the past decades have significantly exacerbated these risks. Our study offers a novel, scientifically derived methodology to evaluate municipal capabilities in managing hydrological risks through urban planning instruments. Leveraging a checklist applied through multicriteria analysis, we scrutinized the integration of theoretical and regulatory frameworks relating to hydrological risks in numerous municipalities. Our findings highlight a glaring deficiency in local Disaster Risk Reduction strategies in alignment with the Sendai Framework. Additionally, there's minimal incorporation of natural risk analysis and mapping into planning instruments. Our results spotlight Málaga's high institutional vulnerability due to its limited capacity in hydrological risk management, underlining the pressing necessity for land use policies informed by risk assessments and prioritizing citizen safety. This study significantly contributes to future urban planning initiatives, offering a roadmap toward more resilient communities amid escalating hydrological risks.

Driving Sustainable Disaster Risk Reduction: A Rapid Review of the Policies and Strategies in Saudi Arabia

This article presents a comprehensive rapid review of the current disaster risk reduction (DRR) efforts in Saudi Arabia, a country exposed to a variety of hazards such as extreme heat, droughts, floods, dust, and sandstorms, along with threats from terrorism and violence. Employing a rapid review approach, our aim was to provide timely insights into DRR strategies, with an emphasis on the unique geographical and socio-political context of Saudi Arabia. This study serves as a valuable reference for similar hazard-prone regions worldwide. Our review encompasses Saudi Arabia’s progress in key areas, such as improving building codes and infrastructure, developing early warning systems, raising public awareness, and strengthening emergency response capabilities. While Saudi Arabia has made commendable strides in implementing international best practices for DRR, our review also identified specific areas where further development and enhancement are needed. These include the need for more sophisticated early warning systems, expanded public awareness campaigns, and continual enhancements in emergency response capabilities. This review offers key insights into the challenges and opportunities within Saudi Arabia’s DRR efforts, highlighting the steps that Saudi Arabia has taken towards resilience. Drawing from specific examples of past disasters, our findings shed light on practical considerations for improving disaster risk management, with the potential to inform policy, enhance public awareness, and contribute to building a safer and more resilient future in Saudi Arabia.

Extreme precipitation patterns in the Asia–Pacific region and its correlation with El Niño-Southern Oscillation (ENSO)

In the Asia–Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990–2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June–August (JJA), and by precipitation frequency in December–February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March–May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.

Accelerated lagged compound floods and droughts in northwest North America under 1.5 °C − 4 °C global warming levels

The recent upsurge in the occurrence of hydroclimatic extremes and their temporal swings has led to severe consequences in many regions around the world. In this study, we characterize the swings between flood and drought events and assess their spatiotemporal frequency and magnitude under climate change. Different scenarios for nonstationary flood and drought swings are investigated over three major river basins in northwest North America. In addition, two novel indices are developed to quantify the severity of the compound flood and drought events in a changing climate. The frequency of flood-to-drought events is projected to increase, with occurrences at the 1.5 °C global warming level happening almost twice than that of the base period. Such transitions are expected to occur more frequently if the world progressively warms. Additionally, the transition time of flood-to-drought events is projected to decrease across all three basins in the study area. Even though drought-to-flood events are expected to become less frequent in a changing climate, the southwest Columbia basin stands out as a hotspot for such transitions. Furthermore, floods are expected to occur earlier in the season, while droughts are projected to occur later, highlighting the increasing variability of floods and droughts of compound hydroclimatic events in a warming world. Additionally, there is a possibility of increased severity for such compound events if global warming is not limited. Our findings assert the necessity of integrating mitigation measures targeting lagged compound flood and drought events into disaster risk reduction strategies.

Application of Sendai Framework for Disaster Risk Reduction in Food Security During Flood Disaster in Malaysia: A Narrative Review

Disaster risk reduction (DRR) plays essential roles in ensuring food security to avoid adverse social, economic and financial implications to the disaster victims. This article aims to review existing DRR strategies in food security during flood disasters and recommend strategies that can be adapted into policies in Malaysia according to the Sendai Framework. Sendai Framework provides comprehensive, globally recognized priority themes in DRR while highlighting governmental and stakeholders’ responsibility. A literature review was carried out by searching available published literatures from online databases and selected information used in this review is taken from articles, journals, reports, national reports, news, and thesis regarding the topic from November 2021 to January 2022. This review revealed that DRR strategies of food security during flood disasters in Malaysia lack one out of 14 work areas in four priorities in the Sendai Framework, which is the national-level risk and vulnerability assessment system and tools. This article proposed 19 recommendations to improve eight work areas across all four priority areas to enhance national food security during flood disasters.

Bridging the Gap: Enhancing Storm Surge Prediction and Decision Support with Bidirectional Attention-Based LSTM

Accurate storm surge forecasting is vital for saving lives and avoiding economic and infrastructural damage. Failure to accurately predict storm surge can have catastrophic repercussions. Advances in machine learning models show the ability to improve accuracy of storm surge prediction by leveraging vast amounts of historical and realtime data such as weather and tide patterns. This paper proposes a bidirectional attention-based LSTM storm surge architecture (BALSSA) to improve prediction accuracy. Training and evaluation utilized extensive meteorological and tide level data from 77 typhoon incidents in Hong Kong and Macao between 2017 and 2022. The proposed methodology is able to model complex non-linearities between large amounts of data from different sources and identify complex relationships between variables that are typically not captured by traditional physical methods. BALSSA effectively resolves the problem of long-term dependencies in storm surge prediction by the incorporation of an attention mechanism. It enables selective emphasis on significant features and boosts the prediction accuracy. Evaluation has been conducted using real-world datasets from Macao to validate our storm surge prediction model. Results show that accuracy and robustness of predictions were significantly improved by the incorporation of attention mechanisms in our models. BALSSA captures temporal dynamics effectively, providing highly accurate storm surge forecasts (MAE: 0.0126, RMSE: 0.0003) up to 72 h in advance. These findings have practical significance for disaster risk reduction strategies, saving lives through timely evacuation and early warnings. Experiments comparing BALSSA variations with other machine learning algorithms consistently validate BALSSA’s superior predictive performance. It offers an additional risk management tool for civil-protection agencies and governments, as well as an ideal solution for enhancing storm surge prediction accuracy, benefiting coastal communities.

Assessing the effectiveness of disaster risk reduction strategies on the regional recovery of critical infrastructure systems

Communities depend on critical infrastructure systems to support their regular operations and future development. Destructive events, such as natural disasters, threaten to disrupt service to these systems and the communities they support. Strategies designed to reduce the impacts from disasters and other events are therefore an important consideration for community planning. At a regional level, coordination between communities supports the efficient use of resources for implementing disaster risk reduction (DRR) measures and completing post-disaster repairs to meet the needs of all residents. Coordination is challenging, however, due to the complexity of regional systems and competing stakeholder interests. This work presents a case study model of regional water, wastewater, and power systems, and demonstrates the effect of seismic hardening and increased resource availability on post-earthquake repair requirements and critical infrastructure recovery. Model results indicate that implementing DRR strategies can reduce required repair costs by over 40 percent and outage severity by approximately 50 percent for the studied sectors. Not all strategies are effective for all sectors and locations, however, so this work discusses the importance of comprehensive, coordinated, and accessible emergency planning activities to ensure that the needs of all residents are considered.

Enhancing household food security through flood disaster risk reduction in little Ruaha River Basin, Iringa district, Tanzania

ABSTRACT The study presents strategies adopted by households in the Little Ruaha River Basin in Iringa district to reduce flood disaster risk thereby enhancing household food security. A mixed research design was employed. Primary data were collected through semi-structured interviews, in-depth interviews, direct field observation and Focus Group Discussions; secondary data were collected through documentary review. The study found that the Little Ruaha river floodplain is very fertile and conducive for crop and livestock rearing. However, the area is frequently affected by flood disasters, thus, making livelihoods at risk. It was also noted that floods in the area affected food production and intensified the households’ food insecurity. It shows that to enhance food security in the household, people moved to safe places during floods, planted trees, dredged the river, practised social cohesion, built flood-resistant houses and used early warning systems. It was also revealed that most flood disaster risk reduction strategies were not effective in enhancing household food security. The study, thus, recommends that the government and other stakehodgders need to organize communities to actively participate in flood disaster risk reduction to reduce their vulnerability to floods and enhance household food security.

LOCAL ORGANIZATIONAL CAPACITY IN NATURAL DISASTER MANAGEMENT IN PAGERWANGI VILLAGE, BANDUNG BARAT DISTRICT

The community is the main actor in disaster management in their area. Involvement as explained by The international strategy for disaster risk reduction (UNDP: 2006) which is one of the strategies by involving community participation in the implementation of disaster risk reduction. The involvement of the community in disaster management policies has been carried out by the government of West Bandung Regency through a disaster resilient village program implemented by the Regional Disaster Management Agency (BPBD). The program is intended to establish and foster local communities for disaster management. This means that the community is facilitated to be involved in disaster management through local organizations formed by the government. Then the local Institution in Pagerwangi Village, Lembang Subdistrict, West Bandung Regency in disaster management is still in the process of developing its resources. The knowledge of organization members about disaster management provides a barrier to the process of strengthening the capacity of local organizations, especially in natural disaster management. So far what has been done is still waiting for encouragement from the local government of West Bandung Regency and from the internal organization itself.&#x0D;

Elderly people evacuation planning in response to extreme flood events using optimisation-based decision-making systems: A case study in western Sydney, Australia

Climate change is causing an increase in the frequency and severity of floods in various regions globally, raising concerns about the efficacy of evacuation planning strategies that were created under different climate scenarios, particularly for vulnerable individuals. Urban areas are at high risk of flooding, making the evacuation of elderly people to safer locations a potential necessity in many future flooding situations. However, despite the significance of transportation planning in the evacuation of the elderly, there has been little research considering the impact of disasters on the areas undergoing evacuation. This paper aims to address this research gap by presenting an integrated evacuation approach for elderly people under flooding conditions. The proposed model combines a flood simulator with multi-objective metaheuristic algorithms to minimise the expected evacuation time for all evacuees and reduce the number of rescue vehicles used. To improve the performance of the optimisation algorithms, dominant properties are established, which are used to create a local search. The proposed approach is tested and validated using a case study in Sydney, Australia, and the findings suggest that the proposed method can generate effective evacuation plans for the elderly in a reasonable amount of time under realistic emergency scenarios brought on by extreme flood events. The study adds to the body of knowledge on disaster risk reduction strategies both theoretically and practically, and has crucial policy implications for emergency managers, planners, and decision-makers in countries where urban areas are becoming increasingly vulnerable to climate change.

Lagged compound dry and wet spells in Northwest North America under 1.5 °C–4 °C global warming levels

The increasing variability and rapid transitions between hydroclimatic extremes and their compounding economic and environmental effects can cause severe consequences. Understanding the changing characteristics of such transitions, including their spatiotemporal frequency and magnitude is critical to developing effective mitigation and adaptation strategies. In this study, lagged compound dry and wet spells are investigated in Northwest North America (NWNA) based on the Standardised Precipitation Index and Standardised Precipitation Evapotranspiration Index for multiple accumulation periods (1, 3, and 6 months). The indices are estimated based on six downscaled Global Climate Models that participated in the 5th phase of the Coupled Model Intercomparison Project under the Representative Concentration Pathways (RCPs) 4.5 and 8.5, in addition to the Variable Infiltration Capacity hydrologic model simulations. We characterize changing behaviour of the lagged compound dry and wet spells under 1.5 °C–4 °C global warming levels. Projections show overall increases in the frequency of wet and dry swings and decreases in the corresponding transition times in NWNA under climate change. In addition, the magnitude, intensity, and duration of wet and dry components of such lagged compound events are projected to increase. With some differences, both indices identify the entire Columbia and southern Fraser basins as hotspots for frequent compound event occurrences. The study identifies increasing hotspots across the domain affected by abrupt transitions under climate change and asserts the necessity of integrating mitigation measures targeting such lagged compound events into disaster risk reduction strategies.

Seismic damage prediction of RC buildings using machine learning

AbstractDecision‐makers and stakeholders require a rapid assessment of potential damage after earthquake events in order to develop and implement disaster risk reduction strategies and to respond systematically in post‐disaster situations. The damage investigated manually after an earthquake are complicated, labor‐intensive, time‐consuming, and error prone process. The development of fragility curves is time consuming and unable to predict the damage for wide classes of structures since it considers few structural properties and only one seismic characteristic. Furthermore, the nonlinear finite element method cannot be utilized for numerous buildings because it involves more time and money. This paper presents the machine learning (ML)‐based seismic damage prediction of RC buildings. It is found that some of the research works only considered seismic parameters or structural parameters to train the ML models and predict the structural damage assessment. However, these ML models may not fully reveal the underlying complexity of the relationship between input parameters and building performance. As a result, their applicability will be limited. This paper evaluates the feasibility of using ML techniques such as K‐nearest neighbor, random forest, decision tree, support vector machine, and artificial neural network to rapidly predict earthquake‐induced reinforced concrete building damage considering both the structural properties and ground motion characteristics. The machine learning models are trained using the simulation results. Due to lack of real earthquake damage datasets or limited access, most of the research works used Scikit Learn train_test_split function to randomly split the entire datasets into training and testing datasets and the performance of the proposed ML technique are evaluated using the testing datasets. However, in this study, the performances of different ML models are evaluated using real earthquake damage datasets of RC buildings collected after 2015 Nepal earthquake. The overall accuracy on testing datasets suggests the capability of machine learning algorithms in successfully predicting the seismic damage of reinforced concrete buildings in quick time with reasonable accuracy. This study is beneficial in emergency response and recovery planning after an earthquake.

Strengthening society preparedness as a strategy for disaster risk reduction in Indonesia

Natural disasters in Indonesia place a heavy and extraordinary burden on the affected people. Disaster victims are often unable to cope with the stress and tension of a disaster, so they turn to the government for help. Disasters also create difficult problems for the government to anticipate and deal with. As a result, the effectiveness of government efforts in disaster management varies. In many cases, the government’s response to disasters is slow, ineffective, often chaotic, and misguided. There is a “gap” between what the government is prepared to do in an emergency management situation and what emerges as the expectations of disaster victims. This paper aims to answer the problem on how the things related to community preparedness can be formulated in disaster management policies. We describe this assertion after conducting field research in six selected regencies in 2021. This mixed methods research is descriptive, with data collected through a survey with respondents and interviews with informants using semi-structured questionnaires. We conclude that there is no other way except society must be able to adapt to disasters and be capable of managing disaster risk reduction. This adaptability is manifested in the forms of society’s preparedness for disasters.

Bushfire and Biodiversity Disaster Risk Reduction Tool: A Community-Led Values-Based Bushfire Risk Management Project with Multi-Agency Support to Develop Strategies to Protect Biodiversity and Manage Bushfire in Upper Beaconsfield, Victoria, Australia

Introduction:This Australian-first project explored residents’ values about living in one of Australia’s extreme bushfire risk areas. The project team developed the Upper Beaconsfield Bushfire and Biodiversity Tool (UPB&amp;BT) which delivers tailored local information for residents living in the area. Designed to empower residents to make informed decisions, this user-friendly, online tool visualizes a community’s devastating bushfire history, reveals residents’ values about living in this area, and provides evidence-based actions to protect biodiversity and manage bushfire fuels on private property.Method:Structured decision-making methodology informed the survey design to elicit residents’ values about biodiversity protection and bushfire risk reduction, by inviting approximately 3000 residents to complete the survey. This community-led project applied a participatory approach by inviting collaboration between government, agencies, universities, and community representatives.Results:Key results revealed 75% of respondents valued nature and lifestyle. 51% saw bushfire risk as an important factor for managing vegetation on private land, while 65% either mow or slash to manage vegetation. Synthesized data informed the content of the UPB&amp;BT, which sourced evidence-based knowledge or specialists’ expertise to provide tailored content and actions that met residents’ diverse values. This included the consequences of chosen actions, which helps residents understand the impact of their decisions. However, results identified confusion in roles and responsibilities.Conclusion:This ground-breaking community-led, government-funded project joined with government, agencies, universities, and community representatives to develop a new bushfire and biodiversity tool to help residents understand biodiversity protection and bushfire management in their local community. Results aim to empower residents to make their own evidence-based and informed choices about managing their properties, thereby contributing to the community good. They decide what is important and identify available actions and their potential consequences. Other communities could replicate this process to localize their own disaster risk reduction strategies.

Mental health risks for cultural heritage professionals within the framework of disaster risk reduction: An exploratory study on the emotional impact of ruins after the 2016 earthquake in central Italy

Across the disaster risk reduction (DRR) community, there is a growing recognition that protecting cultural heritage has a key role in strengthening community sense and resilience. Despite this, however, cultural heritage first aiders, that is, heritage professionals managing the activities of securing movable and immovable cultural heritage in emergencies after disasters, are not adequately recognized in the DRR framework with respect to the mental risks they face, working in the field of emergencies. This study aims to explore the specific quality of mental health risks for cultural heritage first aiders, analyzing the emotional impact of the sight of cultural heritage ruins on a sample of cultural heritage first aiders, compared with a sample of emergency psychologists and earthquake victims, together with exploring the possible role of collateral variables, such as personality traits. Participants were 30 Italian adults who have been involved, to different degrees and roles, in the 2016 Central Italy (Marche region) earthquake or immediately after, for post-disaster emergency activities. Results showed an interesting gradient of the emotional impact of heritage ruins, with heritage professionals at the apex of it. Moreover, heritage professionals showed a higher aesthetic-artistic sensitivity together with the presence of post-traumatic stress long after the disaster event, thus highlighting a specific profile of risk for mental health, which should be taken into serious account by the scientific community. A suggestion is finally proposed on the potential usefulness of including pre-disaster psychological training for cultural heritage aiders in the DRR strategies, also in light of the increasing need for a person-centered approach integrating Mental Health and Psychosocial Support (MHPSS) in the DRR framework.

Developing and understanding cascading effects scenario of typhoons in coastal mega-cities from system perspectives for disaster risk reduction: A case study of shenzhen, China

Coastal mega-cities provide spaces of economic and social activities in contemporary China. Due to the cumulated effects of rapid urbanization and climate change, typhoon disasters always trigger serious cascading effects by affecting interrelated urban elements in high-density urban areas, thereby amplifying disastrous consequences. Developing cascading effects scenarios of typhoons, as well as understanding cause–effect relationships among the involved cascading events is essential to designing disaster risk reduction strategies in coastal mega-cities. However, high uncertainty of the natural hazards and the increasing complexity of coastal mega-cities present challenges to develop and understand cascading effects of typhoons. This research proposes an innovative approach to develop, model, and analyze cascading effects scenario of typhoon disasters in Shenzhen, China for providing insights of disaster risk reduction from system perspectives. First, considering the uncertainty of typhoons and complexity of the study area, the cascading effects scenario of typhoon disasters is developed by encoding hazard transitions triggered by historical cases, in combination with expert judgment. A network approach based on Social Network Analysis is employed to model, visualize, and analyze cascading effects scenarios of typhoons aiming to explore the underlying complexity of typhoon disasters. Finally, disaster risk reduction strategies are designed and evaluated from network analysis perspectives. This research increases the understanding of the evolution process of cascading effects triggered by typhoons in rapid-urbanizing mega-cities from system perspectives. Furthermore, it provides insights of designing effective disaster risk reduction strategies for urban governments to improve sustainability and resilience of coastal mega-cities to typhoon disasters.

Contextualizing Household Adaptation to Flooding in Urbanized Floodplain Areas: Pre-disaster Adaptation, Coping Capacity and Post-Disaster Intervention

As physical flood vulnerability continues to increase in urbanized floodplain areas; understanding and improving household adaptation is an important step towards disaster risk reduction. The study provides an assessment of household adaptation using the resilience model to identify pre-disaster preparedness, household coping capacity, and intervention received during and in post-severe flooding scenarios within communities located in the urbanized floodplain areas of Kosofe. Lagos, Nigeria. Kosofe is the most vulnerable residential area out of the 20 local government areas in Africa’s most populated city, based on flood vulnerability map of the entire city. The study is based on a positivists’ philosophical paradigm, using the deductive approach to gain understanding of resilience model and then tested through a cross-sectional survey involving 324 household heads/representatives in the study area, to contextualize the model in terms of its application in assessing household adaptation. Findings indicate that there is little practice of flood preparedness measures despite high levels of flood risk awareness learnt from previous flood experiences within the area. Similarly, households within the study area rarely use building-based adaptation strategies in coping during severe flooding. Also, government support are very minimal as the most common interventions received by household during and after severe flooding are prayers, savings/thrift contribution, and support from friends and families. The implication of this finding is that by encouraging investments in pre-disaster preparations, deploying adaptive building-based flood disaster risk reduction strategies in new and existing houses, and improving government involvement and support in marginalized urbanized floodplain areas; vulnerable households are better positioned to deal with, cope with and recover from future flood risks.

Cost-benefit-analysis of coastal adaptation strategies and pathways. A case study in West Africa

Understanding the level of vulnerability of human and natural systems to climate variability and change, and how investing in adaptive capacity now will prevent losing billions of dollars in damages in the future are pivotal to making decisions and developing policies related to coastal adaptation. The research presented in this paper focuses on developing a methodological framework to perform a cost-benefit-analysis of disaster risk reduction and climate change adaptation strategies (i.e., protect, accommodate, or retreat options). The method is tested in pilot-site case-studies along the West African countries of Ivory Coast, Ghana, Togo, and Benin. The criterion used in the cost-benefit analysis is the Net Present Value (NPV) for the different risk management alternatives, according to different time horizons and dynamic adaptation pathways to 2100, discount rates and low- and high-cost estimates. Overall, the research makes evident that coastal protection investment costs ensuring the lowest residual risk (virtually zero risk) to 2100 are so high that they are unlikely to be paid back by avoided damages. Planned retreat (coastal setbacks and/or accommodation) allows to obtain most of the benefits (50%–98%) at a fraction of the protection costs (2%–12%). Furthermore, the research provides strong evidence that, when coastal risks are dominated by frequent coastal floods (10-year return period), the cost recovery period for climate-proofing of buildings is low (a few decades) compared to protect or setback measures. Finally, the research illustrates that disaster risk reduction and climate change adaptation strategies cannot be examined in general, but that location specific analysis of both costs and benefits is required.