Disaster Risk Reduction Measures Research Articles

Disaster Risk Reduction Measures and Disaster Preparedness of Elementary Schools in Babak District

The study determines the level of disaster risk reduction measures (DRRM) and disaster preparedness, as well as the significant relationship between the two variables in Cogon, San Antonio, and Toril elementary schools in Babak District. A descriptive-correlational research design was employed in this study. Data analysis involved the use of the weighted average mean and the Pearson Product- Moment Correlation Coefficient. A total of forty-five school heads and teachers respondents were selected through total population sampling. The findings of the study revealed that the levels of disaster risk reduction measures (DRRM) and disaster preparedness in the selected schools are very high, suggesting successful integration and implementation of DRRM strategies. Additionally, a significant relationship was found between the two variables, indicating that increased implementation of disaster risk reduction measures (DRRM) corresponds to higher levels of disaster preparedness in the schools. Consequently, incorporating DRRM into school systems improves the readiness of school heads and teachers for unexpected disasters. The school heads and teachers possess more knowledge and skills to handle disasters, as they are responsible for guiding and protecting students during such events.

Geospatial analysis of alarmingly increasing flood vulnerability and disaster risk within the northeast himalaya region of India

Geoenvironmetally the eastern part of the Himalaya region is highly vulnerable to flood and other natural disasters as it consists of fragmented and tectonically active geology and geomorphology, very high monsoon rainfall (>360 cm) and subsequent runoff, rugged hilly terrain with high ranges of elevation and slope, dense drainage density etc. Other hand, the unplanned developmental activities keep going and scaling up this vulnerability and risk to floods and other disasters. Addressing this burning issue, a geospatial technology-based case study of the Kohima district, Nagaland state (India), is presented here. The geospatial "technology-based" analyses employed in the study are thematic GIS mapping of flood hazard, vulnerability and risk controlling factors; and performing overlay operation using the AHP model in GIS software to generate spatio-temporal map layers of flood vulnerability and disaster risk. Results reveal that the region is under a high rate of monsoon climate change (increasing temperature, rainfall, rainy days, rainfall events and flood events with an annual rate of 0.35 %, 1.12 %, 0.36 %, 2.67 % and 4 % respectively), land use degradation (increasing built-up area with 0.60 %, annual rate decreasing forest, shrubs and water bodies with 0.80 % accumulated annual rates respectively) and demographic changes (increasing urban as well and rural population density with 0.53–2.10 % and 0.55–2.14 % respectively). Accumulated impacts of climate change, land use degradation and demographic changes causing an increase in flood hazard, vulnerability and disaster risk. Flood hazard zones and vulnerability zones extending with 0.50 % (4.89 km2) and 0.84 % (8.16 km2) annual rates respectively, subsequently the flood risk zones categorized as a moderate, high and very high potential risk, have been spreading out with a yearly rate of 0.07 % (0.65 km2), 0.13 % (1.31 km2) and 0.03 % (0.33 km2) respectively. It decreases the area under low and very low-risk zones by 0.17 % (1.63 km2) and 0.07 % (0.65 km2) annual rates respectively. Following up on these annual rates, the spatial distribution of flood hazard, vulnerability and risk zones for the next decade (2031–2040) have also been projected, revealing alarming situations, if flood disaster risk reduction (F-DRR) measures were not implemented in timely. It is strongly believed that the proposed study will be very useful for district-level planners and administrators to implement sustainable development planning, for the scientific fraternity to enhance their research work in the field of flood disaster management and for individuals for their safety in terms of life and property.

Disaster risk reduction measures and farmers choices: a discrete choice experiment in Uganda

ABSTRACT Climate change induces high and erratic rainfall which triggers landslides and floods. With the increasing population and food needs, households in mountainous, densely populated areas turn fragile ecosystems into farms. This exacerbates landslide and flood risks requiring Disaster Risk Reduction (DRR) measures. Tree planting and diversion channels are among the recommended measures for farmers but their adoption remains low. Current studies assessing barriers to adoption ignore farmers’ opinions regarding the kind of trees or diversion channels preferred. We apply a Discrete Choice Experiment to evaluate how information delivered through videos impacts preferences for the DRR measures. Plot-level data were collected from 319 farmers from Kasese, Bundibugyo, Bushenyi and Buhweju in Uganda – districts prone to landslides and floods. The mixed logit model reveals a general preference for risk-reducing attributes of DRR measures. Using the conditional logit model to analyze split samples reveals that information influences preferences for tree planting, while preferences for diversion channels were hardly changed. Plot characteristics did not strongly explain the differences in preferences. Our study indicates that information specific to DRR measures in extension programmes would increase the adoption of such measures.

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.

Data-driven modelling of coastal storm erosion for real-time forecasting at a wave-dominated embayed beach

Emergency managers have an increasing need for tools to enhance preparedness to extreme coastal storms and support disaster risk reduction measures. With the emergence of Early Warning Systems (EWSs) for coastal storm hazards, a fundamental challenge is the accurate prediction of sandy beach erosion at lead times of days to weeks corresponding to an approaching storm event. This work presents a data-driven modelling approach to predict storm-driven beach erosion (shoreline change) using a large dataset of 276 individual storm events at Narrabeen-Collaroy Beach, SE Australia. Correlation analysis between individual storm characteristics and shoreline response at three locations along the embayment with varying exposure to the prevailing waves indicates that cumulative storm wave energy is the dominant driver of storm erosion at this site. This is followed by the pre-storm beach width, storm wave direction and to a minimal extent, storm wave period and water levels. A multi-linear regression model of storm erosion is developed and found to accurately predict shoreline change due to individual storm events (RMSE = 3.7 m–6.4 m). This work highlights the value of high-frequency shoreline data for storm erosion forecasting and provides a framework for real-time forecasting applications.

Assessing the district-level flood vulnerability in Bihar, eastern India: an integrated socioeconomic and environmental approach.

States of India like Bihar, Uttar Pradesh, and West Bengal along the Ganga River, endure natural disasters periodically, resulting in repeated trends of economic loss and damages. Especially, most of the districts of Bihar, India, are prone to floods. Based on this background, this study aims to assess the flood vulnerabilities across districts of Bihar, India, employing data from the Central Water Commission from 1953 to 2020. Further, we explore trends and patterns of loss and damage due to flood risks in Bihar. Using the flood vulnerability integrated method and the principal component analysis, the index is constructed by incorporating the three major indicators: exposure, sensitivity, and adaptive capacity. This study is unique, and advances from previous studies in using a greater number of variables in exposure indicator. The proxy variable for each indicator is identified through both inductive and deductive approaches, and the composite index is constructed using all three indicators. Also, we identify the districts with high level of education and per capita income are less likely to expose flood vulnerability. The comparison of the districts reflects wide range of variation in terms of flood vulnerability as per their adaptive capacity and sensitivity. Specifically, these findings align with Target Sustainable Development Goal 11.5. This study addresses the policy for disaster prevention, risk reduction, and mitigation measures, as well as the enhancement of the capability of adaptation to floods by the affected community.

Spatio-temporal trends and variability in extreme temperature and precipitation indices in the Kashmir Valley, North Western Himalayas

ABSTRACT Earth's average air temperature is warming at a substantial rate leading to an increase in the frequency and severity of extremes with major environmental and socio-economic impacts. The present study discusses temperature and precipitation extremes in Kashmir Valley using observational data from six meteorological stations. An Expert Team on Climate Change Detection and Indices (ETCCDI) (http://etccdi.pacificclimate.org/) provides 25 extreme climate indices (15 for temperature and 10 for precipitation) to be used. The absolute extreme temperature indices (TXx, TXn, TNx, and TNn) exhibit increasing tendencies, according to the findings. The number of changes witnessed in daily maximum temperature was greater than the daily minimum temperature which was manifested by increasing diurnal temperature range (DTR; 0.012 °C/year). These changes in extremes have impacts that pose a threat to agriculture, snow day and cover, glaciers, water resources, ecosystem services, etc. of the study region. The region is undergoing significant urban and land system changes making it further vulnerable to natural hazards. The findings are expected to further augment the hazard and risk analysis and the necessary disaster risk reduction measures for climate-related disasters in the region. These analyses will be helpful for the development of strategies for climate risk management in Kashmir.

Disaster risk management of cultural heritage: A global scale analysis of characteristics, multiple hazards, lessons learned from historical disasters, and issues in current DRR measures in world heritage sites

This study focuses on disaster risk reduction (DRR) in World Heritage (WH) sites around the world. The contents of disaster risk management in management plans, maps, and photographs of target WH sites are examined to understand the characteristics and hazards of heritage sites, lessons learned from historical disasters, and the status and issues in current strategies and measures. Through analyzing these results, it is found that there are diversified hazards in groups of buildings and archaeological sites in Asia and Europe. It is also revealed that fires, earthquakes, strong winds, and floods frequently occurred and caused enormous damage to the heritage sites, as well as human-induced disasters such as terrorism and explosions. Moreover, it was identified that heritage sites with wooden construction or construction partially composed of wooden components were more often damaged by fire, heritage sites located on multiple kinds of terrain were affected by a variety of disasters, and especially coastal heritage sites were exposed to shore erosion and sea level rise related to climate change. Through analyzing the damage, the various fire causes and the need for DRR measures against fires, earthquakes, and floods, become clear, and the urgency to investigate and address human-induced disasters is understood. It is further revealed that few surveyed WH sites have adopted intervention measures for earthquakes, storms, and human-induced hazards.

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.

The potential of global coastal flood risk reduction using various DRR measures

Abstract. Coastal flood risk is a serious global challenge facing current and future generations. Several disaster risk reduction (DRR) measures have been posited as ways to reduce the deleterious impacts of coastal flooding. On a global scale, however, efforts to model the future effects of DRR measures (beyond structural) are limited. In this paper, we use a global-scale flood risk model to estimate the risk of coastal flooding and to assess and compare the efficacy and economic performance of various DRR measures, namely dykes and coastal levees, dry-proofing of urban assets, zoning restrictions in flood-prone areas, and management of foreshore vegetation. To assess the efficacy of each DRR measure, we determine the extent to which it can limit future flood risk as a percentage of regional GDP to the same proportional value as today (a “relative risk constant” objective). To assess their economic performance, we estimate the economic benefits and costs of implementing each measure. If no DRR measures are implemented to mitigate future coastal flood risk, we estimate expected annual damages to exceed USD 1.3 trillion by 2080, directly affecting an estimated 11.5 million people on an annual basis. Low- and high-end scenarios reveal large ranges of impact uncertainty, especially in lower-income regions. On a global scale, we find the efficacy of dykes and coastal levees in achieving the relative risk constant objective to be 98 %, of dry-proofing to be 49 %, of zoning restrictions to be 11 %, and of foreshore vegetation to be 6 %. In terms of direct costs, the overall figure is largest for dry-proofing (USD 151 billion) and dykes and coastal levees (USD 86 billion), much more than those of zoning restrictions (USD 27 million) and foreshore vegetation (USD 366 million). These two more expensive DRR measures also exhibit the largest potential range of direct costs. While zoning restrictions and foreshore vegetation achieve the highest global benefit–cost ratios (BCRs), they also provide the smallest magnitude of overall benefit. We show that there are large regional patterns in both the efficacy and economic performance of modelled DRR measures that display much potential for flood risk reduction, especially in regions of the world that are projected to experience large amounts of population growth. Over 90 % of sub-national regions in the world can achieve their relative risk constant targets if at least one of the investigated DRR measures is employed. While future research could assess the indirect costs and benefits of these four and other DRR measures, as well as their subsequent hybridization, here we demonstrate to global and regional decision makers the case for investing in DRR now to mitigate future coastal flood risk.

Whole value at risk for flood damage estimates through spatial data analysis

Effective disaster risk reduction (DRR) for flooding requires a comprehensive estimate of the whole value at risk (WVAR) to inform appropriate and proportionate mitigation expenditure. Conventional flood risk estimation methods focus on the direct effects of inundation on community value and generally ignore collateral effects on assets and populations outside the flooded area. Consequently, conventional methods tend to underestimate the cost of flooding, leading to an underestimate of the return on DRR investment. Using spatial data analysis in an urban case study for Toronto, Canada, we identify and capture the collateral value at risk (ColVaR) to estimate the WVAR more comprehensively. In our case study, ColVaR (mean estimate) amounts to 70% of direct losses (ColVar = $344 M; direct losses = $475 M CAD), ranging from 20%–150% (ColVar $100–$740 M) when spanning the 90% confidence intervals of our Monte Carlo simulations. Thus, we demonstrate that if the collateral value at risk is ignored, WVAR can be significantly underestimated, potentially leading to reduced disaster risk reduction resource allocations and thereby adding risk exposure for communities. We present an accessible, seven-step process using existing spatial analysis tools and techniques that infrastructure stakeholders and planners can use to estimate ColVaR and better formulate DRR measures for their communities.

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.

Suitability Analysis of Tourist Accommodation Locations Towards Landslide Hazard In Malaka Village, North Lombok Regency

Malaka Village is located in the southwest part of North Lombok Regency. The natural beauty of wavy landscape along coastal area has attracted many tourist-accommodation investments took place in this village, although this brings up a dilemma since the potential economic growth in this place faces a complex natural hazard, especially landslides. The purpose of this study is to get an overview of landslide hazard and examine location suitability of tourist accommodation sites in this area, which can later be used as a reference in advocating disaster risk reduction (DRR) measures. The method used in determining landslide hazard index is spatial (GIS) technique that accommodates variables of: slope rise, rock type, land cover, and rainfall. Based on the weighted overlay result, it is concluded that landslides in Malaka can be devastating (dominated by high hazard), which is confirmed by landslide occurrences at the end of 2022 that were very close to the accommodation sites. Also, an occurrence in 2021 has killed a resident in this village. Digital data on tourism-business locations within this area were taken from online platforms and combined with the findings of a geospatial-based landslide analysis. Based on the suitability analysis through an overlay and buffering operation towards accommodation-location and landslide-hazard layer, it is found that 6 of 30 accommodation sites in Malaka are categorized as low suitability accommodation or dominated by a high and very high hazard category. After comparing landslide features on a related literature and characteristics of past landslides in this area, it is suggested that landslides in Malaka are in form of translational-landslide and rockfall type. Collaborative mitigation efforts that are adapted to the landslide hazard problems are urgently needed to prevent high risks in the future.

Building community resilience: The City of Victoria’s approach to climate change adaptation and extreme heat response

The Pacific Northwest heat dome of 2021 exposed the need for increased planning and response measures by local governments, and the value of collaboration in preparedness, planning and response to extreme heat events. Recognising that extreme heat is becoming an increasingly significant threat, the City of Victoria has taken steps to improve its response to future events with a focus on developing strategies that provide resources and support to those most vulnerable in the community. The Province of British Columbia and regional health authorities have since provided crucial direction, resources and expertise to municipalities to support response effort for extreme heat events. In recognition of the vital role of community involvement in adaptation planning, the City of Victoria is taking proactive measures to engage its residents in the development of adaptation strategies and disaster risk reduction measures. Building on the lessons learned from the 2021 heat dome and climate change projections for the region, the City is fostering close collaboration with local businesses, nonprofit organisations and community groups to strengthen efforts and ensure that those most at risk are well prepared. The experience in Victoria offers valuable insights and strategies for other municipalities seeking to develop effective disaster risk reduction and climate change adaptation strategies based on best practice for planning and responding to extreme heat events. This paper provides a case study of how the City of Victoria responded to the 2021 heat dome, the lessons learned, the practices that were adopted for future heat seasons and how working alongside the community will strengthen Victoria’s resilience to the changing climate conditions.

Dairy farming exposure and impacts from coastal flooding and sea level rise in Aotearoa-New Zealand

Globally, episodic coastal flooding is expected to have increasingly severe impacts on agriculture in low-lying coastal areas, as climate change continues to cause relative sea level rise (RSLR). This study analyses dairy farm exposure and impacts from extreme sea levels (ESL) and RSLR in Aotearoa-New Zealand (A-NZ). Spatio-temporal modelling is undertaken using: 1) a dairy production land layer; 2) a static coastal inundation model from 10, 100, 200 and 500-year annual recurrence interval (ARI) ESL events at 0–2 m RSLR (0.5 m increments); and 3) an Impact State (IS) scheme relating percentage of farmland inundated and depth of flooding at milking shed locations to categorise the severity of damage. Through this analysis we highlight the increasing exposure of the dairy industry to coastal flooding, with 472 farms potentially impacted (at or greater than IS 1) by a 10-year ARI event and 1276 farms exposed to a 500-year ARI event at current sea levels, rising to 1276 (10-year ARI) and 1344 farms (500-year ARI) with 2 m RSLR. RSLR is identified as the factor driving this increase in exposure and severity of impacts to dairying, with the increase in the number of farms impacted in a 500-year compared to 10-year event only 5 % greater when considered with 1 m of RSLR, compared to 37 % greater at 0 m RSLR. This has significant implications for A-NZ where the dairy industry is of high economic and social importance, demonstrating the need for industry targeted climate change adaptation and disaster risk reduction measures.

Local government capacity for earthquake disaster risk reduction in Malaysia: Case studies in Bentong and Selayang areas

This paper investigates the status of earthquake disaster risk reduction (DRR) capacity of local governments (LG) in Malaysia, and the factors that influence the LGs’ capacity to reduce earthquake risk. Currently, there is a lack of understanding and systematic study of the capacity of LG to address earthquake DRR even though the LGs in Malaysia are at the forefront of the national agenda to carry out DRR actions at the local level. A qualitative methodology was utilised based on a comparative case study design involving two cases of LG in Malaysia with the risks in dealing with earthquakes i.e. Bentong Municipal Council and Selayang Municipal Council. The study employed semi-structured interviews and documentation analysis as its data collection methods. To ensure a systematic data collection, a capacity assessment framework (CAF) had been developed based on key capacity categories identified according to the powers and responsibilities of the LG as outlined by UNDRR, and components of UNDP capacity building. The findings of this study suggested that inadequacy of LG in Malaysia to address earthquake DRR measures are mainly due to several capacity issues: insufficient financial backing, lack of knowledge and required expertise, lack of specific unit to tackle DRR issues, and low utilisation of existing resources such as inter-agency networking and regulations. The findings highlighted the need to empower the LG with improved capacities and governance structures. This paper concludes with several recommendations on how the LG can address key capacity gaps identified in this study.

Child disaster resilience in action: Post-bushfire qualitative perspectives on a school-based preparedness program

We aimed to explore the acceptability of delivering a child-focused disaster preparedness program in primary schools in a high disaster-risk area and assess community perspectives of young people's application of preparedness skills during a large-scale bushfire in Australia. Fifteen adult community members participated in individual key-informant interviews online and in-person. Interviews were conducted one year following a major bushfire event in the community. Reflexive thematic analysis was conducted to determine community perceptions of the preparedness program's acceptability, applicability and impact. Findings indicated that parents and school staff valued the age-appropriate content and delivery of the preparedness program and viewed it as highly relevant, engaging and applicable for primary school children. Many reported that the program supported child-led decision making in evacuation preparedness, heightened a sense of agency, and enhanced social connectedness. Interviewees described multiple instances of children who had completed the preparedness program later enacting the key response strategies during bushfires. The findings complement calls for child preparedness education and highlight the long-term positive impacts of engaging children in disaster resilience. Accordingly, disaster risk reduction measures should incorporate child-focused strategies to foster whole-of-community resilience in high-risk areas.

The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models

Pluvial floods are increasingly threatening urban environments worldwide due to human-induced climate change. High-resolution, state-of-the-art pluvial flood models are urgently needed to inform climate change adaptation and disaster risk reduction measures but are generally not empirically tested because of the rarity of local high-intensity precipitation events and the lack of monitoring capabilities. Volunteered Geographic Information (VGI) collected by professionals, non-professionals and citizens and made available on the internet can be used to monitor the dynamic extent of a pluvial flood during and after an extreme rain event but is sometimes considered to be unreliable. In this paper, we explore the general utility of VGI to evaluate the performance of pluvial flood models and gain new insights to improve these models. As background for our research, we use the capital city of Budapest, which recently suffered three heavy rainfall events in just five years (2015, 2017 and 2020). For each pluvial flood event, we collected photographic evidence from different online media sources and estimated the associated water depths at various locations in the city from the image context. These were compared with the results of a 2D pluvial flood model that has been shown to provide comparable results to other state-of-the-art inundation models and is easily transferred to other urban areas due to its reliance on open data sources. We introduce a general methodology for comparing VGI with model data by probing different spatial resolutions. Our findings highlight untapped potential and fundamental challenges in using VGI for model evaluation. It is proposed that VGI may become an essential tool and improve the confidence in model-based risk assessments for climate change adaptation and disaster risk reduction.

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.

Does the farmer’s social information network matter? Explaining adoption behavior for disaster risk reduction measures using the theory of planned behavior

Smallholder farmers’ vulnerability to climate-related disasters in Sub-Saharan Africa is increasing, partly due to land-use changes and poor adoption behavior for Disaster Risk Reduction (DRR) measures. Such behavior can be explained by poor beliefs about DRR measures due to limited access to information. Agricultural extension workers are increasingly less trusted because they tend to transfer information less targeted to DRR and have limited spatial coverage. We apply the Theory of Planned Behavior (TPB) to explain the adoption behavior for DRR measures and further investigate whether Social Information Networks (SIN) explain the behavior beyond the TPB determinants. Cross-sectional data were collected from 602 randomly selected households from Rwenzori and Ankole in Western Uganda, the sub-regions that are prone to landslides and floods. Results from the Structural Equation Modeling (SEM) demonstrate that TPB explains the adoption behavior with Perceived Behavioral Control (PBC) as a stronger driver of intentions than subjective norms and attitudes. The intention to apply DRR measures is significantly associated with actual adoption. Farmers’ behavior to control landslides and floods is correlated because the same location is at risk of such interacting disasters. Moreover, SIN also significantly predicts adoption intentions through the three theoretical predictors by playing a moderating role. PBC and professional networks being the main drivers of adoption intentions suggests that the role of extension services cannot be substituted by informal social networks but the two should be complementary. Thus, the study shows the need to build the technical capacity of extension staff and informal networks in DRR measures to share information with farmers.