Disaster Risk Reduction Research Articles

Advancements in Fire Safety Technology: A Automatic Fire Extinguishing Robot

Fire security which is a lasting and persistent issue requires the continuous development of technology to reinforce protection and inhibition of the fires which are regular event that often leads to emergencies in many sectors. This research endeavors to delve deeply into the realm of fire safety technology, focusing keenly on two innovative approaches: the Chai roof closers security policy, after house-closers protection process, and a matted fire extinguisher robot that notifies about the fire. Through scrupulously examining their technical detail, experiments, operational patterns, and potential outcomes and impact, the paper in this order to fulfills its objective of giving the reader a comprehensive and all-encompassing understanding of the extent and the take of these types of fire systems in the total field of fire safety. Relying on a broad review of journal articles, experiments, and also a proactive approach to these technological advancements that might contribute to averting fire disasters and on preserving both human lives and valuable properties, this research undertakes a mission to explore the emergence of these technological advancements and how much they instill change in the conduct of disaster response and risk mitigation.

Multi-Objective Evcuation Planning Model Considering Post-Earthquake Fire Spread: A Tokyo Case Study

As an integral part of the 2030 Agenda for Sustainable Development, Disaster Risk Reduction (DRR) is essential for human safety and city sustainability. In recent years, natural disasters, which have had a tremendous negative impact on economic and social development, have frequently occurred in cities. As one of these devastating disasters, earthquakes can severely damage the achievements of urban development and impact the sustainable development of cities. To prepare for potential large earthquakes in the future, efficient evacuation plans need to be developed to enhance evacuation efficiency and minimize casualties. Most previous research focuses on minimization of distance or cost while ignoring risk factors. We propose a multi-objective optimization model with the goal of reducing the risk during the evacuation process, which is called the risk reduction model (RRM). Problem-specific indicators for screening optimal solutions are introduced. The research selects the Ogu area in Tokyo as a case study, where there is a relatively high density of wooden structures, increasing the risks of building collapse and fire spread after an earthquake, and is based on a two-phase evacuation flow that considers secondary evacuation for fire response. The results indicate that, in this case, RRM can, in most situations, reduce the risk level during the evacuation process and improve evacuation efficiency and success rate without significantly increasing the total evacuation distance. It proves to be superior to the traditional distance minimization model (DMM), which prioritizes minimizing the total distance as the objective function.

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

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

DRR pioneers: interview with Ben Wisner

PurposeThe transcript provides an overview of the development of the field and changing paradigms in this regard.Design/methodology/approachThe transcript was developed in the context of a United Nations Office for Disaster Risk Reduction (UNDRR) project on the history of disaster risk reduction (DRR).FindingsThe transcript traces the initial discussions of how the At Risk book was conceived and presents new dimensions and challenges within the field.Originality/valueThe interview highlights the importance of the need to document the transitions, developments and paradigm changes in the field over time.

Can geomorphic flood descriptors coupled with machine learning models enhance in quantifying flood risks over data-scarce catchments? Development of a hybrid framework for Ganga basin (India).

Quantifying flood risks through a cascade of hydraulic-cum-hydrodynamic modelling is data-intensive and computationally demanding- a major constraint for economically struggling and data-scarce low and middle-income nations. Under such circumstances, geomorphic flood descriptors (GFDs), that encompass the hidden characteristics of flood propensity may assist in developing a nuanced understanding of flood risk management. In line with this, the present study proposes a novel framework for estimating flood hazard and population exposure by leveraging GFDs and Machine Learning (ML) models over severely flood-prone Ganga basin. The study incorporates SHapley Additive exPlanations (SHAP) values in flood hazard modeling to justify the degree of influence of each GFD on the simulated floodplain maps. A set of 15 relevant GFDs derived from high-resolution CartoDEM are forced to five state-of-the-art ML models; AdaBoost, Random Forest, GBDT, XGBoost, and CatBoost, for predicting flood extents and depths. To enumerate the performance of ML models, a set of twelve statistical metrics are considered. Our result indicates a superior performance of XGBoost (κ = 0.72 and KGE = 82%) over other ML models in flood extent and flood depth prediction, resulting in about 47% of the population exposure to high-flood risks. The SHAP summary plots reveal a pre-dominance of Height Above Nearest Drainage during flood depth prediction. The study contributes significantly in comprehending our understanding of catchment characteristics and its influence in the process of sustainable disaster risk reduction. The results obtained from the study provide valuable recommendations for efficient flood management and mitigation strategies, especially over global data-scarce flood-prone basins.

STUDY OF FLOOD VULNERABILITY IN HIMALAYAN REGION: A CASE OF UTTRAKHAND

India's Himalayan area is well known for its magnificent scenery and abundant wildlife. However, because of its complicated geology, delicate ecosystems, and unpredictable climate, it is also extremely vulnerable to catastrophic calamities. The causes, effects, and mitigation techniques of the common natural catastrophes that affect India's Himalayan region—such as earthquakes, landslides, floods, and glacial lake outburst floods (GLOFs)—are briefly summarised in this summary. Because of the collision of the Indian and Eurasian tectonic plates, earthquakes are one of the most dangerous natural disasters in the Himalayan region. Major seismic events, like the one that struck Nepal in 2015, demonstrate how vulnerable the region's heavily inhabited areas are to devastating destruction and high fatality rates. Effective disaster preparedness and resilient infrastructure are crucial for minimizing casualties and damage. Another common risk in the Himalayan region is landslides, which can be brought on by unstable slopes, strong rains, and seismic activity. The region's susceptibility is exacerbated by these occurrences, which represent a major threat to natural ecosystems, transportation networks, and towns, particularly during the monsoon season. In the Himalayan region, floods are a common occurrence that are exacerbated by glacial melt, heavy rainfall, and glacier lake outbursts. Flash floods, like the ones that occurred in Uttarakhand in 2013, highlight the terrible effects on infrastructure, communities, and the environment. Reducing flood risks and increasing resilience requires community-based adaptation strategies, early warning systems, and sustainable land use planning. A unique hazard in the Himalayan region, glacial lake outburst floods (GLOFs) are caused by the rapid melting of glaciers and the creation of unstable glacial lakes. The communities, infrastructure, and ecosystems downstream are seriously threatened by these catastrophes, which calls for careful observation and risk assessment techniques. One of the worst natural catastrophes to have hit the state in recent memory is the flash floods in Uttarakhand. Because to the state's distinctive geography, which is made up of small valleys and steep hills, heavy rainfall events have a greater effect, especially during the monsoon season. 2013's devastating flash floods, brought on by abnormally high rainfall, caused extensive environmental damage, infrastructure ruin, and a great deal of fatalities. The abrupt influx of water, rubble, and silt caused great destruction to isolated communities, tourist attractions, and places of worship, underscoring the precariousness of human habitation in the foothills of the Himalayas. The incident also brought attention to the relationship between unplanned development, environmental deterioration, and the likelihood of disasters, spurring calls for more land use planning, early warning systems, and sustainable development techniques future flash floods in Uttarakhand. In conclusion, the broad range of natural hazards that the Himalayan area of India faces calls for multifaceted methods to disaster risk reduction and management. In this dynamic and vulnerable setting, scientific research, community participation, and sustainable development practices are critical components of effective resilience-building efforts. Keywords: Hilly areas natural disaster, flash flood, Glacial lake outburst, flash flood in Uttarakhand

Perspectives of environmental health officers on climate change adaptation in Australia: a cross-sectional survey

Abstract Aim Climate change adaptation is critical for reducing and preventing many community health risks. The Environmental Health Profession has decades of experience of effective interventions for reducing and preventing many community health risks. However, in Australia adaptation is not included in the profession’s scope of practice leaving the community health at risk to climate change. The aim of this study was to assess the perspectives of Australian Environmental Health Officers concerning climate change health adaptation and whether this should be included in their role. Subject and methods Eighty-nine (89) eligible participants undertook a mixed method survey between November 2021 and January 2022. These participants were members of Environmental Health Australia and held a relevant degree in environmental health. The questions on the survey were related to six themed items: (1) climate change and health, (2) climate change adaptation, (3) the profession’s role in capacity building for adaptation, (4) hurdles for building adaptive capacity, (5) health awareness as a bridging concept and finally, (6) disaster risk reduction. Results The findings from this study indicate that the majority of participants were concerned for their community health from climate change impacts. A system thinking approach is required to effectively address and understand complex health risks. There was also an overwhelming support for the profession to integrate approaches of disaster risk reduction and climate change adaptation in health. However, the environmental health profession is facing some significant hurdles to building adaptive capacity to climate change. Conclusion This study demonstrates the environmental health profession does want to have a role in climate change adaptation in Australia. These findings, with further qualitative research, could bolster the preventive public health approach in building community health resilience to climate change and related disasters.

Extreme rainfall and landslides as a response to human-induced climate change: a case study at Baixada Santista, Brazil, 2020

AbstractIn March 2020, an extreme rainfall in Baixada Santista, Brazil, led to a series of landslides affecting more than 2800 people and resulting losses exceeding USD 43 million. This attribution study compared extreme rainfall in two large ensembles of the UK Met Office Hadley Centre HadGEM3-GA6 model that represented the event with and without the effects of anthropogenic climate change. Antecedent rainfall conditions on two different timescales are considered, namely extreme 60-day rainfall (Rx60day) which relates to the soil moisture conditions and extreme 3-day rainfall (Rx3day) which represents landslide triggering heavy rainfall. In the scenario including both natural and human-induced factors the antecedent 60 day rainfall became 74% more likely, while the short-term trigger was 46% more likely. The anthropogenic contribution to changes in rainfall accounted for 20–42% of the total losses and damages. The greatest economic losses occurred in Guarujá (42%), followed by São Vicente (30%) and Santos (28%). Landslides were responsible for 47% of the homes damaged, 85% of the homes destroyed, all reported injuries, and 51% of the deaths associated with heavy rainfall. Changes in land cover and urbanization showed a pronounced increase in urbanized area in Guarujá (107%), São Vicente (61.7%) and Santos (36.9%) and a reduction in farming area. In recent years, the region has experienced an increase in population growth and a rise in the proportion of irregular and/or precarious housing in high-risk areas. Guarujá has the highest number of such dwellings, accounting for 34.8%. Our estimates suggest that extreme precipitation events are having shorter return periods due to climate change and increased urbanization and population growth is exposing more people to these events. These findings are especially important for decision-makers in the context of disaster risk reduction and mitigation and adaptation to climate change.

Does willingness to pay for the traditional flood control measures kasumitei vary by river section of residential area?

Kasumitei (open levees) comprise a traditional flood mitigation measure used in Japan. Kasumitei allow floodwater to flow into surrounding paddy fields, which act as temporary flood mitigation basins. After flooding, debris accumulated in paddy fields often brings crop damage and debris removal costs. Therefore, in some areas, the disaster mitigation functions of kasumitei may bring about conflicts between beneficiaries (downstream residents) and burden bearers (midstream residents). Ensuring the continued use of kasumitei in the future requires a mechanism to support the burden bearers. This study aimed to test the hypothesis that the willingness to pay (WTP) for maintaining the kasumitei would be lower for midstream residents (potential burden bearers) than for upstream (irrelevant) and downstream residents (potential beneficiaries). The results showed that contrary to the hypothesis, WTP for maintaining kasumitei was not affected by the river sections of the respondents' residence. Thus, a financial support scheme for maintaining kasumitei might be acceptable regardless of the beneficiary or bearer in the surveyed respondents. In addition, respondents with higher interest in ecosystem conservation tended to have higher WTP. Therefore, to gain support for the maintenance and use of the kasumitei (a type of ecosystem-based disaster risk reduction), the authorities would promote awareness of the measure's contribution to ecosystem conservation. Based on the results, we discussed the potential financial support schemes for maintaining the kasumitei.

Soft computing machine learning applications for assessing regional-scale landslide susceptibility in the Nepal Himalaya

PurposeThis research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.Design/methodology/approachUsing the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).FindingsThe validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.Research limitations/implicationsLand cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.Practical implicationsIt helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.Social implicationsThe social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.Originality/valueLandslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

Multi-criteria comparison analysis of spatial equity for emergency shelters in old and new urban districts: A case study in Wuhua District and Chenggong District of Kunming City, China

With the progression of urbanization and the concentration of populations in urban areas, cities are increasingly exposed to disaster risks. Emergency shelters play a critical role in disaster prevention and mitigation, as they are vital for providing temporary refuge and protection during and after catastrophic events. Assessing the spatial equity of these shelters is conducive to enhancing emergency relief capabilities and aiding in disaster risk reduction. However, there remains a lack of clarity regarding the comparative and quantitative disparities between new and old urban areas, particularly in developing countries like China, where urbanization is rapid and populations are dense. To address this issue, this study employed a combination of multi-source data and GIScience technology to analyze the spatial equity of emergency shelters in Wuhua District and Chenggong District of Kunming City, China. We evaluated the overall spatial equity of emergency shelters in both the old urban area (Wuhua District) and the new urban area (Chenggong District) using a comprehensive evaluation model with three criteria: evacuation population capacity, spatial accessibility, and the level of per capita effective shelter area. The results revealed that the old urban area suffers from insufficient effective emergency shelter capacity due to saturated construction land. More than 67 % of the shelters are short-term emergency shelters located close to buildings, which compromises spatial accessibility during earthquake disasters. The level of per capita effective shelter area, as indicated by SSTD, is 24.42 in Wuhua District, suggesting that the effective shelter area in each subdistrict is consistently low, regardless of its urban or suburban classification. In contrast, the new urban district boasts substantial effective emergency shelter capacities, both in the long-term and short-term types, surpassing the reference capacities. The rational spatial layout of various types of emergency shelters ensures that most regions with concentrated buildings are enveloped in accessibility time layers within a 25-min range. The SSTD index of Chenggong District is 349.23, underscoring the significant disparity in the level of per capita effective shelter area at the subdistrict scale, particularly in the district's urban villages and suburban regions. The findings of this study serve as a scientific reference for emergency management and urban planners to reasonably plan or upgrade shelter facilities, thereby improving urban resilience and promoting spatial equity in resource allocation among subdistricts, communities, and residents.

Enhancing Urban Resilience: Strategic Management and Action Plans for Cyclonic Events through Socially Constructed Risk Processes

Cities will face increasing challenges due to the impacts of global climate change, particularly in the form of cyclonic events, necessitating a deeper understanding and the establishment of effective response mechanisms at both institutional and citizen levels. In this research, we tested the efficiency of crowdsourcing in fostering participatory resilience and improving urban management. The main aim was to design novel and accurate proactive response strategies and mitigate the adverse effects of cyclonic wind events through volunteerism, citizen science, and urban science. To achieve this goal, as a case study, the municipality of Soledad, Colombia was used. This research employed a two-phase methodological approach: (i) initially evaluating the spatial distribution of emergency response resources, and (ii) developing a geo-referenced survey to map, systematize, and categorize data and outcomes. A total of three hundred and seventy-eight residents across five neighborhoods in Soledad, which have experienced a high frequency of atmospheric wind phenomena over the past two decades, were surveyed. The results indicate that the crowdsourcing mechanism effectively enhanced the empirical understanding of atmospheric wind events in Soledad, facilitating the establishment of a geo-referenced volunteer network for real-time responses. Additionally, this study shed light on previously undocumented challenges, in terms of reducing the number of people affected, and the actions that would lead to improved urban development to reduce the impacts of cyclonic events, emphasizing the significance of citizen science in the social construction of risk and disaster risk reduction (DDR) efforts.

Modelled effectiveness of NbS in reducing disaster risk: evidence from the OPERANDUM project

The use of nature-based solutions (NbS) to address the risks posed by hydro-meteorological hazards have not yet become part of the mainstream policy response, and one of the main reasons cited for this, is the lack of evidence that they can effectively reduce disaster risk. This paper addresses this issue, by providing model-based evidence from five European case studies which demonstrate the effectiveness of five different NbS in reducing the magnitude of the hazard and thus risk, in present-day and possible future climates. In OAL-Austria, the hazard is a deep-seated landslide, and the NbS analysed is afforestation. Modelling results show that in today's climate and a landcover scenario of mature forest, a reduction in landslide velocity of 27.6% could be achieved. In OAL-Germany, the hazard is river flooding and the NbS analysed is managed grazing with removal of woody vegetation. Modelling results show that the NbS could potentially reduce maximum flood water depth in the near-future (2031-2060) and far-future (2070-2099), by 0.036m and 0.155m, respectively. In OAL-Greece, the hazard is river flooding, and the NbS is upscaled natural storage reservoirs. Modelling results show that in a possible future climate the upscaled NbS show most potential in reducing the total flooded area by up to 1.26 km2. In OAL-Ireland, the hazard is surface and river flooding, and the NbS is green roofs. Results from a modelled upscaling analysis under two different climate scenarios show that both maximum flood water depth, and total flooded area were able to be reduced. In OAL-UK, the hazard is shallow landslides, and the NbS is high-density planting of two different tree species. Modelling results under two different climate scenarios show that both tree species were able to improve slope stability, and that this increased over time as the NbS matured. The significance of these results is discussed within the context of the performance of the NbS over time, to different magnitude type events, impact with stakeholders in engendering wider support for the adoption of the NbS in the OALs, and the uncertainty in the modelling analyses.

Model media learning for disaster risk reduction in the Batur UNESCO global Geopark

The development of tourism activities in the Batur UNESCO Global Geopark has brought many tourists to visit the area. Along with increasing tourism activities, the risk of disasters in the geopark area has also increased. One thing that can be done to reduce disaster risk in the Batur UGGp area is to utilize geoheritage as a learning medium for disaster risk reduction. In this study, we described quantitatively geoheritage by looking at its relationship with the priority actions of the Sendai framework. The results of the assessment of geological heritage values that have been carried out in 21 geosites of the geopark area show an interrelated relationship.Scientific, educational, tourism and degradation values of geoheritage sites have an important role in conveying information and messages related to disaster mitigation, which is in line with the objectives of Sendai's priority actions. Geological heritage sites can later be developed as an educational medium because it has accessibility capital, supporting facilities, good geological conditions, geological diversity it also contains geological informationthat can be used for education and research. Developing geological disaster information within geoheritage sites in geopark areas, may be in the form of geotrails and geotourism activities with the theme of disaster mitigation and earth heritage, Picture books for children based on site geoheritage information, especially those related to the introduction of geological disasters is also ideal to develop. A geological information center at the Batur Volcano Museum and are other educational acivities that can be made within the geopark area.

Tinjauan Kebijakan: Evaluasi Efektivitas Upaya Penanggulangan Bencana di Desa Ciwangi

Ciwangi Village in Garut Regency, has the potential for disasters such as earthquakes, floods, and landslides. Therefore, evaluating the effectiveness of disaster management efforts in Ciwangi Village is crucial for mitigating risks and protecting local communities. This research aims to explore the dynamics of disasters that occurred in Ciwangi Village and evaluate the level of effectiveness of mitigation policies, starting from the structural level to the village. This research uses qualitative methods by reviewing Regional Regulations (Perda) related to disaster management in Ciwangi Village, Garut Regency. The review was carried out using in-depth interviews, observations, and document analysis. The analysis was carried out by detailing the implementation of the Sendai Framework for Disaster Risk Reduction (SFDRR) principles at the local level. The results of the analysis are then linked to Chamber Theory to evaluate the effectiveness of policy coordination and implementation at the village level. The research results show that disaster mitigation efforts in Ciwangi Village are still weak in terms of understanding disaster risk, disaster risk management, investment in disaster risk reduction, and disaster preparedness.

Exploring Performance and Challenges Faced by Tanods: A Comprehensive Review of Related Literature

The manuscript offers an in-depth examination of the performance and obstacles faced by barangay tanods, vital civilian volunteers tasked with upholding peace and security in areas where formal law enforcement presence is scarce. The study extensively examines various aspects of barangay tanods' roles, responsibilities, and operational effectiveness, emphasizing their satisfaction levels, training needs, empowerment initiatives, and operational challenges. It underscores the significance of continuous training programs, specialized competencies, and community responses in improving the overall performance of barangay peacekeeping teams. Additionally, the research explores how barangay tanods engage in disaster risk reduction, respond to public health emergencies, and adapt to evolving work environments, demonstrating their resilience and adaptability during crises. While recognizing the effectiveness of barangay tanod across different domains, the study also highlights operational barriers like limited resources and challenges in information dissemination that impede their optimal performance. The study concludes by promoting research initiatives that encompass gender diversity to gain deeper insights into the responsibilities and challenges encountered by female tanods, aiming to improve the tanods' overall success in keeping peace and order. This research significantly adds to the domain of existing knowledge by illuminating the essential function fulfilled by barangay tanods and providing valuable perspectives to direct upcoming researchers in advancing understanding within this critical field.

Economic and social costs of flood disasters in Nigeria: Implications for sustainable national development

Nigeria is susceptible to flood disasters, resulting in significant economic and social costs due to natural and human factors. This paper examines the implications of flood disasters on Nigeria's sustainable national development by identifying drivers, estimating costs, analyzing social dimensions, and discussing policy options. The methodology this paper adopted relied on a range of secondary sources such as government reports, academic studies, and media sources which were analyzed through qualitative methods of content and thematic analysis. The study revealed that flood disasters caused economic losses, including damage to infrastructure, loss of income, and reduced agricultural production, disproportionately affecting vulnerable populations. Effective disaster risk management requires an integrated approach, including investments in flood risk infrastructure, coordination among government levels, and engaging local communities to build disaster reduction capacity. The paper highlights the need for Nigeria to mainstream disaster risk reduction into national development planning for sustainable development.

Profession-Specific Values, Beliefs, and Norms on Environmentalism: The Case of Teaching Disaster Risk Reduction

Profession-Specific Values, Beliefs, and Norms on Environmentalism: The Case of Teaching Disaster Risk Reduction

Drivers of natural disaster risk-reduction actions and their temporal dynamics: Insights from surveys during an imminent hurricane threat and its aftermath.

To improve preparedness for natural disasters, it is imperative to understand the factors that enable individual risk-reduction actions. This study offers such insights using innovative real-time (N = 871) and repeated (N = 255) surveys of a sample of coastal residents in Florida regarding flood preparations and their drivers during an imminent threat posed by Hurricane Dorian and its aftermath. Compared with commonly employed cross-sectional surveys, our methodology better represents relationships between preparedness actions undertaken during the disaster threat and their drivers derived from an extended version of Protection Motivation Theory (PMT). The repeated survey allows for examining temporal dynamics in these drivers. Our results confirm the importance of coping appraisals and show that risk perceptions relate more strongly to emergency protection decisions made during the period of the disaster threat than to decisions made well before. Moreover, we find that several personal characteristics that we add to the standard PMT framework significantly relate to undertaking preparedness actions, especially locus of control and social norms. Significant changes in key explanatory variables occur following the disaster threat, including a decline in risk perception, a potential learning effect in coping appraisals, and a decline in risk aversion. Our results confirm the advantage of the real-time and repeated survey approach in understanding both short- and long-term disaster preparedness actions.

Runoff Hydrograph Analysis of HEC-RAS 2D Flow Hydrodynamics Meteorological Rain-on-Grid on Observed Watershed: A Case Study of Wiroko Sub-Watershed

In contemporary hydrological analysis, numerical models have emerged as an alternative solution for water resources planning and management, particularly in forecasting extreme events and mitigating disaster risks. HEC-RAS 2D flow hydrodynamics enables the modeling of rainfall with input from meteorological boundary condition data. Precipitation within the studied watershed can be modeled as point rainfall or area-averaged rainfall in the rain-on-grid feature of HEC-RAS 2D flow hydrodynamics. In this study, the HEC-RAS 2D flow model utilizes the diffusion wave equations (DWE) for simulating unsteady flow routing. When modeling a complex watershed, the 2D hydrodynamics model has become a viable alternative, especially concerning the watershed's physical characteristics. This study aims to assess the reliability of HEC-RAS 2D flow hydrodynamics and compare its results with the hydrograph data from the observed watershed in the Wiroko Sub-Watershed of the upper Wonogiri Dam. In this research, extreme rainfall events of 100 mm in the first hour are simulated and compared with the hydrograph data from the observed watershed. Based on the numerical model results in the Wiroko Sub-Watershed, it was determined that conforming to the land use with a Manning roughness value of 0.12 (designated as developed area-medium intensity) resulted in a peak discharge (Qp) difference of 0.8%. Meanwhile, the time to peak (Tp) value exhibited a discrepancy of 1.93 hours longer between the numerical model and the observed hydrograph.