Implementing Disaster Risk Reduction Research Articles

Implementation outcomes of disaster risk reduction (DRR) policy in public facilities (PFs): Aceh perspective, Indonesia

PurposeAceh province has established various infrastructure and regulations related to disaster risk and management after the Indian Ocean Tsunami (IOT) hit the province. Hence, this study investigates the implementation of Disaster Risk Reduction (DRR) in Public Facilities (PFs) in Banda Aceh municipality using implementation outcome variables (acceptability, adoption, appropriateness, feasibility, compliance, implementation cost, coverage and sustainability).Design/methodology/approachQualitative methods, including in-depth interviews and document reviews, were applied to collect data for this study. The data were then analysed thematically using NVivo 12 software.FindingsThe lack of public communication regarding DRR in PFs to all involved stakeholders resulted in poor acceptability, adoption, coverage and compliance with the policy implementation among public facilities’ chiefs, owners or managers. Additionally, they were reluctant to implement DRR plans and activities within their facilities due to limited DRR funds.Practical implicationsThis study’s results can contribute to reviewing the policy and practices of Aceh government authorities and other involved stakeholders to improve policy implementation of DRR activities comprehensively across eight groups of public facilities in Banda municipality, other districts in Aceh province, and local areas in Indonesia. Further, the methods used in this study to assess DRR regulations’ progress towards the eight implementation outcome variables can be applied widely to other settings.Originality/valueNo research was found on examining the policy implementation of DRR in PFs in Aceh province, which motivated the author to conduct this work.

For resilient rural shorelines: reviewing Nature-based Solutions for flood risk reduction in small coastal communities

Coastal flood risk poses a serious, existential threat to shoreline populations around the world both now and in the future. Unsurprisingly, global decision makers are considering their options – one of these being Nature-based Solutions – for effective disaster risk reduction which specifically targets coastal flooding. While strides have been made in the field of Nature-based Solutions for coastal flooding, much of this attention has been directed towards the urban setting, with a wealth of scholastic documentation to support this notion. The sizeable rural populations scattered throughout the world's small coastal communities, meanwhile, have been largely neglected in academic literature. Without this information, it is impossible to properly capture the full potential of Nature-based Solutions in (global) flood risk modelling endeavours or understand their role in the future of equitable disaster risk reduction. In light of this gap, we have reviewed the limited amount of existing literature from around the world involving the implementation and effectiveness of Nature-based Solutions in small coastal communities. We analysed 28 peer-reviewed studies to gather common themes and insights about the barriers and opportunities unique to these rural shorelines. Takeaways we have identified include a near consistent scarcity of resources (e.g., technical, financial, institutional) to implement disaster risk reduction measures; an abundance of space and opportune land use regimes which make Nature-based Solutions a highly plausible option; amplified nature contributions to people leading to larger benefits reaped from investments into Nature-based Solutions; and the presence of local knowledge regarding societal norms, climate patterns, and ecosystem capabilities. We argue that these four common themes point to the fact that more attention must be given to coastal flooding-focused Nature-based Solutions in the rural setting. As such, we present this collation as a starting point for future projects of similar setting and scope. We also recommend improving benefit-cost analysis methods as well as including local knowledge and other perspectives in future global assessments of coastal flood risk.

Combining machine learning (ML) and participatory rural appraisal (PRA) for disaster risk preparedness (DRP): Evidence from the poorest region of Luzon, Philippines

In the field of social science, disaster risk preparedness (DRP) is considered immeasurable due to its multidimensional nature, making it infamously difficult to quantify. The current measurements are costly, labor-intensive, and time-consuming. Consequently, policymakers struggle to target policies effectively when implementing disaster risk reduction management initiatives. By combining Participatory Rural Appraisal (PRA) and Machine Learning (ML) to train and test community-based system datasets, this work proposes novel approaches to DRP in the poorest region of Luzon, Philippines. We utilized sophisticated econometrics models along with ML categorization methods. Through the analysis of 34 locales and 4 sectors within a disaggregation system over 429 ensemble runs using cross-validation techniques, we then combined the results. The Support Vector Machine (SVM) classifier achieved the highest accuracy of 91.55 % randomly and 94.53 % within the pipeline, surpassing all other models. It also confirms the current relationship between DRP and multidimensional attributes (a total of 21 factors) in terms of correlation and causation. Our work showcases the potential of ML for disaster risk prediction, potentially reducing costs, saving labor, and optimizing time, especially in the most impoverished areas of the Philippines. Ultimately, through extensive PRA, the outcomes have provided different localities with tools for targeting policies in disaster risk management.

Upaya Mengurangi Resiko Bencana di Pedesaan dengan Memanfaatkan Citra Penginderaan Jauh

The natural disaster is one of the phenomena that can occur at any time, anywhere and anytime. The most common disasters are floods, landslides, tornadoes and earthquakes, which can cause damage, loss of life and even loss of life. The conditions of Tabaroge Village and its surroundings are prone to flooding geographically, geologically, hydrologically and demographically. The condition of the East Luwu Regency area is at the confluence of several earth tectonic plates. Therefore, most of the potential disaster threats are in the Tabaroge Village area and its surroundings. Based on the occurrence of natural disasters in East Luwu Regency in recent years, which occurred in several villages. Judging from the characteristics of the Tabaroge Village area, Efforts to Reduce Disaster Risk in Rural Areas by Utilising Remote Sensing Imagery aims to provide information on locations that have disaster risk. This research uses the analysis methods of Standardised Precipitation Index (SPI), Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), Soil Adjusted Vegetation Index (SAVI) and Inverse Distance Weighted (IDW) for data exploration using Arcmap (GIS). In future development, it is expected to be able to implement disaster risk reduction by utilising remote sensing imagery in Tabaroge Village, East Luwu Regency.

The Extent of Implementation of Disaster Risk Reduction and Management in The Third District of Negros Oriental

The Extent of Implementation of Disaster Risk Reduction and Management in The Third District of Negros Oriental

Mapping the risk reduction benefits of coral reef conservation – Hawaiʻi case study

Effective disaster risk reduction measures are vital to coastal communities around the world. While nature-based solutions provide coastal communities with a promising alternative to traditional engineering-based solutions; these solutions are often overlooked by communities when planning and implementing disaster risk reduction measures. This study builds upon the literature that demonstrates the effectiveness of coral reef conservation to mitigate coastal flood risk. Our approach utilizes freely available tools and data to quantify the economic value of coral reef conservation for the Hawaiian Islands. We explore a scenario that depicts coastal flooding if the upper 1 m of the coral reef were to be lost. The study analyzes the Average Annual Loss (AAL) and losses avoided based on a series of 4 coastal flood scenario return periods with and without coral reefs. This case study finds that the preservation of the upper 1 m of coral reefs for the main islands of Hawaiʻi provides the state with $629 million in annual losses avoided to buildings. A hot spot analysis of the losses avoided identifies areas where conservation efforts could be prioritized. Our findings provide additional support to the use of nature-based solutions as an effective disaster risk reduction measure, and provides communities and stakeholders with a methodology that can be implemented using readily available data and tools.

Disaster risk reduction in elementary schools in flood-prone areas (Case: disaster risk reduction in Grogol flood-prone areas, Indonesia)

Floods disaster have caused much damage and disruption to the continuity of education. Therefore, disaster risk reduction efforts must be carried out, especially in the school environment. This study aims to analyze how Disaster Risk Reduction efforts are conducted in elementary schools in the Grogol flood-prone area, Indonesia. This research is quantitative research with a survey design. Data collection is carried out using questionnaires and documentation. The instrument used is a closed questionnaire with indicators of Disaster Risk Reduction, including knowledge and attitudes, school policies, preparedness planning, and resource mobility. The population in this study were five elementary schools located in flood-prone areas of Grogol, Indonesia, including SDN Madegondo 1, SDN Madegondo 3, SDN Pandean 1, SDN Kadokan 1, and SDN Pandean 2. Respondents in this study were 40 teaching staff who consisted of principals, homeroom teachers, and teachers from each elementary school. The data analysis technique used is descriptive statistical data analysis. The results of this study were shocking; even though floods overflow the river almost every year, all schools in the flood-prone areas were classified as in the low class in implementing Disaster Risk Reduction for flood disasters. One factor that has a dominant influence was the absence of an official policy from the government that officially regulates the implementation of Disaster Risk Reduction for flood disasters in the region. The results of this study are expected to be used as a basis for implementing disaster risk reduction by elementary schools against floods.

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.

Implementation of Disaster Risk Reduction and Management in the Context of Inclusive Education

Implementation of Disaster Risk Reduction and Management in the Context of Inclusive Education

Potential for Various Riverine Flood DRR Measures at the Global Scale

Flooding events that occur on the Earth’s rivers annually cause large amounts of monetary and human impacts. These impacts are expected to increase through the end of the 21st century for various reasons. Decision makers must take action now and implement disaster risk reduction measures to avoid large increases to damages in the future. On the global scale, we model three disaster risk reduction measures – namely dykes and levees, dry-proofing, and zoning restrictions – and evaluate them in terms of their economic performance (via benefit-cost analysis) as well as their ability to achieve a predefined risk reduction target based on current relative levels of risk, referred here to as efficacy. We show that large decreases to future expected annual damages can be obtained if certain measures are implemented throughout various sub-national regions of the world, most notably in regions with high levels of projected population growth. We see that the two aforementioned evaluation metrics, when used to select a disaster risk reduction measure for implementation, result in different outcomes for three-fourths of the world’s sub-national regions, most often in East Asia and the Pacific as well as South Asia. In these instances, decision makers must choose what is more important – achieving a risk reduction target, or having investments pay-off in the long run, even if it requires a large amount of up-front capital. This opens the dialogue for incorporating other non-monetary values into the decision making process for disaster risk management, and also points to the potential of hybridising riverine adaptation measures to achieve multiple risk and societal objectives at once.

Integrated Disaster Risk Management in the Education Process in Schools

Research in educational disaster mitigation has developed and is widely carried out, especially in schools. This research explores good practices based on the experience of teachers in Indonesia regarding the possibility of integrating DRR (Disaster Risk Reduction) education into the learning process in schools. This study used research and development (R and D) methods with the APPED model (preliminary analysis and research, design, production, evaluation and dissemination), which was carried out for two years. In particular, this paper reports the results of the first year’s research with research activities including: (i) analysis and preliminary research and (ii) design. In the initial analysis and research stages, the research team carried out several activities, including analysis of material coverage, learning outcomes, and learning activities through literature review and document analysis, combined with case studies and FGD (Focus Group Discussion) involving 87 teachers in Yogyakarta, Malang, and Ciamis. Furthermore, the results of the activities in the second stage, (Design), are in the form of an analysis of the needs of students in DRR (Disaster Risk Reduction) education based on Ecosystem-based Disaster Risk Reduction (Eco-DRR). Studies reveal that DRR (Disaster Risk Reduction) education has the potential to be integrated into educational activities in schools. Practically, the main components of DRR (Disaster Risk Reduction) education include: coverage of materials, learning outcomes, and learning activities. The research results also show that the integrated interdisciplinary curriculum model has the potential to be adopted in the implementation of DRR (Disaster Risk Reduction) education, through intra-curricular, extra-curricular and co-curricular learning activities. This finding has implications for the need for teacher involvement in the next research stage, where production, evaluation, and dissemination processes are carried out. Good practices that have been carried out by teachers have become one of the important instruments in implementing integrated disaster risk management with the educational process in schools . Further, important to consider the integration of science and indigenous knowledge (ISIK) in implementing DRR education in schools, through intra-curricular, extra-curricular and co-curricular. The disaster and mitigation knowledge were empirical, genuine, participatory and interactive, within the localities context. Schools can be good agents for dissemination of the ISIK perspective in disaster and mitigation studies. Although the relation between scientific and indigenous knowledge is proposed by the participants, but theoretically and practically needed follow-up studies, especially to reduce the level of vulnerability.

Identification of Understanding of Disaster Preparedness in the School Environment

Flores Island is vulnerable towards natural disasters. Therefore, it requires an effective disaster warning ma-nagement. In this context, schools play an important role in disaster warning system. However, not all schools implement Disaster Risk Reduction (DRR) procedures effectively. Therefore, efforts are needed to improve disaster warning system among schools by integrating the three pillar principles, which include safe facilities, effective disaster management, and resilience education. This study aims to understand the state of school readiness in the Flores region and assess the extent to which these schools apply the three pillar criteria for school disaster warning system. The research method used is a qualitative descriptive ap-proach, with data collection through an open questionnaire distributed using Google Forms. The result showed that the locations of the respondent's schools are spread across the most disaster-prone areas of Flo-res, especially along the coastal areas. In addition, there are still many schools in the region that have diffe-rent levels of understanding and awareness regarding to disaster warning system. Based on that issue, the program for activating the disaster warning system in school area is very important to apply and can increase public awareness of disaster warning system. To achieve that idea, a collaboration between school commit-tees, external parties, and the Flores community is essential to strengthen the school infrastructure and to build an effective response towards potential disaster risks and threats.

Community Activation for Disaster Risk Reduction Through OpenStreetMap: A Scoping Review

The advancement of geospatial technology has significantly altered how data is utilised for facilitating the growth of open-access data for disaster risk reduction (DRR). OpenStreetMap (OSM) is a part of Volunteered Geographic Information (VGI), built on the concept of volunteerism and heavily reliant on user contributions to spatial data. In recent years, OSM has emerged as a fundamental tool in all aspects of DRR, enabling well-informed decision-making and empowering active community contributions. This study aims to review the utilisation of OSM in DRR and proposes recommendations to enhance community resilience. The five-step scoping review method was conducted on 25 selected papers to investigate the current knowledge and uncover the potential applications of OSM within the community for DRR. The review commenced by defining the research questions, identifying pertinent literature sources, selecting relevant literature for inclusion, extracting key themes from the literature, and finally, consolidating, summarising, and reporting the results. The findings revealed that OSM’s worldwide accessibility for various objectives has been instrumental in its widespread adoption and rising prominence. Nevertheless, this review emphasises that despite its rapid expansion into other fields, OSM continues to hold significant importance and widespread usage in the context of DRR. This study presented findings on community involvement in OSM and explored the opportunities for community-led DRR implementation. The paper provides insights into the application of OSM in advanced and developing countries while delving into potential future pathways. OSM places significant emphasis on community-driven, on-the-ground data collection, providing governments with a chance to enhance policy management in DRR. As the incorporation of OSM in decision-making expands, it will garner attention from diverse sectors, demonstrating the platform’s effectiveness on a broader and more impactful level.

Climate change and anthropogenic pressure on Bintan Islands, Indonesia: An assessment of the policies proposed by local authorities

Bintan island is one of Indonesia’s national priority regencies of climate resilience for the marine and coastal sectors. This area also has had the highest frequency of disaster events within the province over the past ten years, where climate-related hazard was dominant. Therefore, it is necessary to receive public support for climate policies within the region. From this point of view, this paper aims to explore the local evidence of climate change, anthropogenic pressure which worsens climate hazards, and the linkage with local policies. The primary data source was a climate data set of observations from 1976–2021, land use change information from 1990–2020, historical climate-related hazards, and related current policy documents. We found that the region’s air temperature has continuously increased over 45 years with the positive standardized precipitation index (SPI) being dominant. Meanwhile the wind speed was tended to decrease since 2015 with the highest extreme record occurred in February 2021. Moreover, climate-related threats occurred more than 70 times in Bintan from 2011 to 2021 where forest fire and flood were tended to worsen. Another anthropogenic source, such as land use change, also puts significant pressure on the part where the open land has increased by 187%, and vegetation area has decreased by 51.1%. This condition creates these small islands vulnerable to climate change, especially climate-related hazards. However, in the regional development plan document 2021–2026, climate change adaptation is not one of the local priority issues, but their concern about disaster mitigation is quite severe. The local authorities work on hard and soft infrastructure to implement disaster risk reduction but less for ecosystem-based solution. However, promoting adaptation efforts in the local policy document is still necessary for sustainable development at the local level.

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.

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.

Implementation of disaster risk reduction management activities in flood-prone communities of a highly urbanized city in Central Visayas

Implementation of disaster risk reduction management activities in flood-prone communities of a highly urbanized city in Central Visayas

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.

Supports for Multi-hazard Risk Reduction in Urban Local Bodies

India’s urban assets and populations are highly vulnerable to a multitude of natural hazards, climate variability and environmental change. This can well impact on the entire nation, as economic output comes primarily from in and around its urban settlements. Empirical evidence from recent disasters, despite some major successes, reinforces the limited preparedness of Indian towns and cities to withstand multiple hazards such as fires, floods, extreme temperatures, earthquakes and strong winds. Unregulated growth and the quality of built environment are among a host of factors that have resulted in this vulnerability to disaster events. The research issue that this paper addresses is that of enabling the Urban Local Bodies (ULB) to implement disaster risk reduction and recovery framework(s) developed and agreed on at the national and sub-national levels. This paper highlights capacity challenges within local government for managing natural disasters amongst wider challenges of service provision. The paper draws upon empirical observations to argue that despite their best intentions ULBs are currently constrained in implementing the extensive comprehensive disaster risk & recovery approach driven by a multiplicity of national and multilateral policies. The paper provides observations from the Kosi River flooding disaster (2008) in Bihar state to illustrate this point. The paper further highlights that while this situation will not change overnight there are a number of practical opportunities to support ULBs in making an immediate start and superimpose risk reduction onto development programmes.

Future perspectives of earthquake-tsunami catastrophe modelling: From single-hazards to cascading and compounding multi-hazards

Probabilistic risk models for natural hazards, or natural catastrophe models, are indispensable tools for forecasting and quantifying the impacts of cascading and compounding earthquake-tsunami hazards. Their applications facilitate improved disaster risk mitigation and management. Uncertainties associated with forecasted multi-hazard impacts can be substantial, and practitioners and policymakers need guidance on implementing disaster risk reduction actions at all levels (local, regional, national, and international). In communicating such broad ranges of possible consequences with stakeholders, disaster scenarios need to be carefully selected and presented. This article reviews the state-of-the-art of earthquake, tsunami, and earthquake-tsunami catastrophe modelling and discusses future perspectives for earthquake-tsunami risk assessments.