Frequent Natural Hazards Research Articles

Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India)

Floods are one of the frequent natural hazards occurring in Kerala because of the remarkably high annual rate of rainfall. The objective of this study is to prepare the flood susceptibility maps of Ernakulam district by integrating remote sensing data, GIS, analytical hierarchy process (AHP), and fuzzy-analytical hierarchy process methods. Ernakulam is one of Kerala's most flood-prone districts. The development of this map can help to raise awareness about the risks of flooding. Factors such as slope angle, soil types (texture), land use/land cover, stream density, water ratio index, normalized difference built-up index, topographic wetness index, stream power index, aspect, and sediment transport index have been selected. The area of the final maps is grouped into five flood susceptible zones, ranging from very low to very high. The major reasons for flood occurrence in Ernakulam district are the combined effect of multiple factors such as excess silting, reduction of stream width due to anthropogenic activities, and changes in land cover and land-use pattern, lower slope, higher soil moisture content, lower stream capacity, and poor infiltration capacity of soils. The prepared map was validated using the receiver operating characteristic (ROC) curve method. The area under the ROC curve (AUC) values of 0.75 and 0.81 estimated by the ROC curve method for the AHP and F-AHP methods are considered acceptable and excellent, which confirms the prediction capability of the prepared maps. The very high susceptible zone constitutes around 19% of the district. This map is useful for land-use planners and policymakers to adopt strategies that will reduce the impact of flood hazards and damage in the future.

Assessing coastal vulnerability and governance in Mahanadi Delta, Odisha, India

The geo-climatic setting of the Odisha coast is prone to natural calamities like cyclones, storm surges, inundation, along with changing sea level, which indicates a higher level of coastal vulnerability. Climate-induced natural hazards are frequent on the Odisha coast, which leads to adverse impacts on life and property and intensive crop damage. The frequent natural hazards and sea-level rise (SLR) are accelerating the probable impact from severe storm surges and high waves in the future. The futuristic projection of the cyclone, storm surge, inundation and SLR has been estimated. Also, their probable impact on the coastal community has been portrayed.

The legacy of vulnerability to floods in the Tana River, Kenya

Floods are the most recurring, widespread, disastrous, and frequent natural hazards in the world. This paper aims to understand vulnerability among ethnic groups living in areas prone to floods because of historical development and implementation of laws and policies. I use the Tana River County in Kenya as a case study to answer the question: what role have economic development policies, laws, and their implementation played in the propagation of drivers of vulnerability through history? I apply the Integrated Approach to Natural Hazards by establishing the previous and current influence of economic development policies on physical, structural, and social dimensions of floods among the region's vulnerable inhabitants. Vulnerability to floods is the long-term culmination of enacted economic development policies and laws that can be ascertained through a review of historical records. To explore the historical narrative of Tana River County, I searched through archived county-specific historical records. To determine the present narrative, I collected data from inhabitants of purposively sampled villages of Tana Delta Sub-County using focus group discussions and I administered key informant interviews to government and non-governmental organizations located in Tana River County. I report that the implementation and institution of economic development policy and legal frameworks under both colonial and post-colonial governments have directly influenced physical, structural, and social dimensions of floods by both increasing vulnerability and producing new forms of vulnerability for floodplain inhabitants. This understanding is vital to local, national, and regional administrators involved in development and implementation of current and future hazard management strategies.

A comprehensive analysis method of spatial prioritization for urban flood management based on source tracking

Flooding is one of the most frequent and disastrous natural hazards that can have catastrophic impacts on human society and urban infrastructure. Increasing the incidence of urban flooding highlights the need for reliable flood mitigation strategies that can effectively minimize losses owing to disasters. The strategic placement of flood mitigation measures is undoubtedly the key to achieving maximum effectiveness of flood reduction schemes. The physical characteristics of the site and knowledge of regional relevance play an important role in determining the location of appropriate flood mitigation measures. In the case of limited resources, it is crucial to prioritize areas for installation of flood mitigation measures. Therefore, an indicator-based method was developed in this study to identify and prioritize sites to concentrate limited resources where they are needed the most. Based on the source tracking method, a tracer-aided urban flood model was developed to study the impact of direct and indirect connections between urban systems, explore their relative importance in the network, and prioritize related risks to improve resource allocation efficiency. Longkungou drainage district of Haikou City was selected as the study area to determine the prioritization of catchments for flood mitigation. The results indicated that high prioritization sites are in the upstream of the urban areas with prioritization decreasing downstream, and the prioritization of interventions presents a spatial trend of “high south and low north”. This study demonstrates the novelty of a tracer-aided urban flood model in flood management and highlights the spatial connectivity between flood source areas and flood hazard areas. The prioritization scheme of urban catchment flood mitigation measures proposed in this study provides valuable guidance for policy makers and urban planners who wish to exploit the approach for flood mitigation.

Low-Cost Sensor-Based and LoRaWAN Opportunities for Landslide Monitoring Systems on IoT Platform: A Review

Landslides are a frequent natural hazard during the rainy season, causing infrastructural and economic damage globally. Several studies on landslide monitoring techniques have been conducted in order to reduce various types of losses. There is an extensive review in this article of the ground monitoring method that uses a variety of sensors and some of the primary advances that help to enhance architecture and fulfill user needs. Study of cost-effective ground monitoring technique analysis in different landslide warning systems and some known cases in research article based on coverage area and energy harvesting methods also discussed. Moreover, WSN architecture identified and creates classes according to their benefits and drawbacks as well as performance is evaluated such as efficiency, reliability, quality of service, and network lifetime.

A standardised inventory for New Zealand's stopbank (levee) network and its application for natural hazard exposure assessments

AbstractFlooding is New Zealand's most frequent natural hazard, responsible for the highest number of declared civil defence emergencies and greatest regular economic loss. Stopbanks (levees) perform a critical flood protection function in all regions of the country. However, there have been limited and inconsistent records on the location and physical attributes of these stopbanks at a national level. Through collaboration with regional government representatives, we provide the first standardised national inventory of stopbanks, the New Zealand Inventory of Stopbanks (NZIS). The NZIS provides a standardised geospatial overview of New Zealand's 5284 km long stopbank network, enabling spatial reviews and comparisons of flood protection characteristics at national and regional scales. Around 64% of New Zealand's total stopbank length is situated within five regions (Canterbury, Waikato, Southland, Manawatū‐Whanganui and Bay of Plenty), while the nation's most densely population region, Auckland, accounts for just 1.9% of the total national stopbank length. Our research uses the NZIS geospatial dataset to conduct a preliminary exposure assessment of New Zealand's stopbank network to seismic and co‐seismic hazards; including proximity to known active earthquake faults, ground shaking intensities and susceptibility to liquefaction and landslides. Preliminary exposure assessments provide an example of how the NZIS can be adopted and applied.

Assessment of Flood Risks in Ifo Local Government Area of Ogun State

The most frequent natural hazards and the most costly in terms of property damage in study area is Flood. The purpose of this work is use Geographic Information Systems (GIS) Hydrological tools to model and map flood event in Ifo Local Government Area of Ogun state, Nigeria using Shuttle Radar Topographic Mission ( SRTM) data and land use maps as input data layers. In this study, flood inundation depth is calculated with GIS in order to understand the temporal, spatial scale and transition. Flood inundation map and 3D views of the hydrological modelling results are provided for a better understanding of the severity of flooding in the location. It is recommended that the processed data from this study be used as input for future research and the development of flood warning systems for the area. It will also be a base study for future study when rainfall data will be available.

Prediction of flood using optimized neural network with Gray wolf algorithm (Maroon River case study)

Floods, as one of the most frequent natural hazards, cause irreparable damage to infrastructure and agriculture, and housing every year. In order to avoid financial and human losses, the importance of flood forecasting seems inevitable. Considering that floods are caused by many natural and anthropogenic factors and also have limitations such as lack of complete information. In this study, artificial neural networks have been used as an efficient method for flood prediction. The neural network inputs include the Dubai River and the Eshel River, this data was collected over 8 Years from the Maroon River. The network used is a multilayer perceptron, also the neural network weights are optimized by the Gray wolf algorithm and the results are compared with other common methods. Analysis of the output results shows that the neural network with the Gray Wolf algorithm has better results than neural network and Genetic algorithms and the error of this method is 0.53%, which indicates high accuracy and precision for flood prediction compared to other evolutionary algorithms. This method is used to obtain the best amount of data for testing and training. As the results, the best rate is 80% for training and 20% for testing. Obtained results show the neural network error squares with 80% of the training data and 20% of the test data.

Understanding the Impacts of the October 2017 Portugal Wildfires on Cultural Heritage

In a changing world where the frequency of natural hazards is increasing, the consequences of disasters on cultural heritage assets are still not well understood. This can be attributed to shortcomings in existing risk management practices and to the fact that disaster consequences in the cultural sector are seldom recorded in a structured manner. On 15 October 2017, an extreme wildfire event took place in Portugal, causing significant human and material losses. However, little information is available about its impacts on cultural heritage. This article describes a study that was carried out to identify cultural heritage assets affected by the event in inland central Portugal, and the types of impacts that they withstood, based on local information collected from a sample of municipalities estimated to have been the most affected. The municipalities were selected based on a geospatial analysis supported by maps of estimated burnt areas and national datasets of cultural heritage. The information provided by the municipalities is comprehensively reported and discussed. Although the consequences of the wildfires on cultural heritage were not particularly severe, relevant direct and indirect damage occurred, and further indirect consequences may arise in the future as a result of the event. Improved knowledge and awareness regarding wildfire risk management for cultural heritage assets, supported by research initiatives such the one presented here, are called for.

Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico.

Landslides are frequent and damaging natural hazards that threaten the people and the natural and built environments of Puerto Rico. In 2017, more than 70,000 landslides were triggered across the island by heavy rainfall from Hurricane María, prompting requests by local professionals for landslide education and outreach materials. This article describes a novel collaborative risk communication framework that was developed to meet those requests and shaped the creation of a Spanish- and English-language Landslide Guide for Residents of Puerto Rico. Collaborative risk communication is defined here as an iterative process guided by a set of principles for the interdisciplinary coproduction of hazards information and communication products by local and external stakeholders. The process that supports this form of risk communication involves mapping out the risk communication stakeholders in the at-risk or -disaster-affected location-in this case Puerto Rico-and collaborating over time to address a shared challenge, such as landslide hazards. The approach described in this article involved the formation of a core team of government and university partners that expanded in membership to conduct collaborative work with an informal network of hazards professionals from diverse sectors in Puerto Rico. The following principles guided this process: cultural competence, ethical engagement, listening, inclusive decision -making, empathy, convergence research, nested mentoring, adaptability, and reciprocity. This article contributes to the field of risk communication and emergency management by detailing these principles and the associated process in order to motivate collaborative risk communication efforts in different geographic and cultural contexts. While the work described here focuses on addressing landslides, the principles and process are transferable to other natural, technological, and willful human-caused hazards. They may also serve as a roadmap for future partnerships among government agencies and university researchers to inform the cocreation of science education and outreach tools.

Nature-based solutions for flood risk reduction: A probabilistic modeling framework

<h2>Summary</h2> Flooding is the most frequent and damaging natural hazard globally. While nature-based solutions can reduce flood risk, they are not part of mainstream risk management. We develop a probabilistic risk analysis framework to quantify these benefits that (1) accounts for frequent small events and rarer large events, (2) can be applied to large basins and data-scarce contexts, and (3) quantifies economic benefits and reduction in people affected. Measuring benefits in terms of avoided losses enables the integration of nature-based solutions in standard cost-benefit analysis of protective infrastructure. Results for the Chindwin River basin in Myanmar highlight the potential consequences of deforestation on long-term flood risk. We find that loss reduction is driven by small but frequent storms, suggesting that current practice relying on large storms may underestimate the benefits of nature-based solutions. By providing average annual losses, the framework helps mainstream nature-based solutions in infrastructure planning or insurance practice.

High-resolution dynamical downscaling for regional climate projection in Central Asia based on bias-corrected multiple GCMs

Central Asia (CA) is among the most vulnerable regions to climate change due to the fragile ecosystems, frequent natural hazards, strained water resources, and accelerated glacier melting, which underscores the need to achieve robust projection of regional climate change. In this study, we applied three bias-corrected global climate models (GCMs) to conduct 9 km-resolution regional climate simulations in CA for the reference (1986–2005) and future (2031–2050) periods. The regional climate model (RCM) and GCM simulated daily temperature and precipitation are evaluated and the results show that both the bias-correction technique and dynamical downscaling method obtain numerous added values in reproducing the historical climate in CA, respect to the original GCMs. The former contributes more to reducing the biases of the climatology and the latter contributes more to capturing the spatial pattern. The RCM simulations indicate significant warming over CA in the near-term future, with the regional mean increase of annual mean temperature in a range of 1.63–2.01 ℃, relative to the reference period. Pronounced warming is detected north of ~ 45° N in CA from autumn to spring, which can be explained by the snow-albedo feedback. Enhanced warming projected in many mountains in the world is not found in CA, which is consistent with the study based on the reanalysis datasets during the past. Heatwave day frequency, number and maximum duration are expected to become more severe by 2031–2050. Changes in precipitation and Standard Precipitation Index (SPI) shows a wetter condition in CA in the coming decades. However, a fairer assessment of the wet/dry change with Standard Precipitation Evapotranspiration Index (SPEI) which takes into account of both precipitation and potential evapotranspiration reveals a drier condition. The climate change projections presented here serve as a robust scientific basis for assessment of future risk from climate change in CA.

Preference Heterogeneity of Coastal Gray, Green, and Hybrid Infrastructure against Sea-Level Rise: A Choice Experiment Application in Japan

Coastal zones are bearing the brunt of an increase in the likelihood of extreme events, coupled with sea-level rise (SLR). Conventionally, gray infrastructures, such as seawalls, have been constructed to reduce risks in limited coastal zone spaces. Nature-based approaches, known as green infrastructure, have been used in coastal defense, and their ecosystem-based disaster risk reduction functions (Eco-DRR) have received growing attention. However, both gray and green infrastructure alone have limitations in responding to an ongoing increase in the intensity and frequency of natural hazards. To overcome these issues, hybrid infrastructure, which combine gray and green components, is needed, and they have been receiving growing attention. Meanwhile, a large-scale coastal development requires stakeholder agreement; thus, it is imperative to understand people’s demands and build a consensus between municipalities and coastal citizens in coastal development for long-term resilience. The author administered the online survey across Japan, applying it to the choice experiment, and obtained 840 valid responses. Therefore, this paper clarified the heterogeneities in coastal people’s preferences for coastal ecosystem services provided by gray, green, and hybrid structures in intertidal zones in Japan, recognizing seawalls as gray and coastal pine forests as green infrastructure. Consequently, while coastal citizens acknowledged gray’s coastal defense function, the diverse perceptions toward seawalls for SLR preparation were notable as its scenarios became severe. Another remarkable finding is that nearly 60% of respondents preferred Eco-DRR functions provided by coastal forests with JPY 695 in willingness-to-pay for expanding 100 m in width, even though there are uncertainties in their performances.

Evaluation of Humanitarian Supply Chain Resilience in Flood Disaster

Frequent natural hazards such as flooding and the devastating consequences of severe events make the humanitarian supply chain particularly important in alleviating the suffering of those communities impacted by such events. However, the ambiguity of information and the different goals of stakeholders demand that the humanitarian supply chain must be resilient. This research adopts the use of literature review and expert opinions to identify the indicators that affect the resilience of the humanitarian supply chain using the flood event in Hechuan District, China in 2020 as an example. Based on the combination of fuzzy Decision-making Trial and Evaluation Laboratory and Analytic Network Process (fuzzy-DEMATEL-ANP), the interrelationships between the indicators and the weights of each indicator are calculated. The research results indicate that decision-makers in the humanitarian supply chain should vigorously coordinate the cooperation among stakeholders, ensure the effective transmission of information, and formulate forward-looking strategic plans. At the same time, these key decision makers should also be aware of the need to adjust their strategies at different stages of the flooding event in order to achieve a flexible humanitarian supply chain that responds to the varying demands over the course of a flooding event. The results of this study will help professionals involved in humanitarian supply chains to develop strategies and plans to become more resilient thus helping to reduce losses from natural hazards such as floods.

Assessment of kinematic rock slope failures in Mudurnu Valley, Turkey

Slope instabilities are one of the most frequent natural hazards capable of causing severe failures both at regional and large scales. Mudurnu, which is settled on a steep valley, is affected by regional rock slope instabilities. These instabilities constitute a hazard and create an important risk to the community since they threaten human lives, settlement areas, and historically-important structures. In order to minimize the hazard and risk associated with slope instabilities, rock masses along the valley were characterized and the potential failure mechanisms were defined. The west side of the valley, which is the focus of the research, is characterized by Cretaceous pelagic discontinuous limestone, and is prone to complex failures. The aim of the study is to characterize the rock mass along the valley, divide the area into geomechanically-uniform sectors, define possible modes of failure (kinematics) and ultimately quantify the potential failure (kinetics) and the associated risk. For the study, in addition to the field work and scan-line survey measurements, an Unmanned Aerial Vehicle (UAV) was utilized to collect high-resolution images from problematic locations that were not accessible. Then, a point cloud of the area was generated. The images were interpreted and the resulting structural representation of the rock mass was compared with information gathered from the scan-line survey in the field. Afterwards, it was used to identify the possible modes of failure along the valley. Since seismic activity in the area is significant due to the proximity of the North Anatolian Fault Zone (NAFZ), which is the most active fault system in Turkey, dynamic loading was also considered for the stability analyses.

Quantifying climate change-relevant humanitarian programming and spending across five countries with high vulnerability to disaster.

Climate change is increasing the severity and the frequency of natural hazards and associated disasters worldwide, yet there is little data tracking how and whether it is being addressed by humanitarian assistance initiatives. Drawing on publicly available United Nations programme data and vulnerability indexes, this study pilots a novel approach to identifying and quantifying the prevalence of climate change‐related humanitarian programmes from 2016–18 in five disaster‐affected countries. The funding levels of proposed and undertaken interventions were analysed within specific programmatic sub‐areas and across clusters. The study found that 1.8 per cent (99 of 5,558) of projects included in humanitarian proposals reviewed during the research have a climate change‐related component. Of 1,361 funded projects, 40 of these were climate change‐related and received funding. The methodologies tested here to assess and classify climate change‐related humanitarian programmes could be expanded to support further tracking of humanitarian responses to climate change across operational contexts.

Assessing the economic impacts of future fluvial flooding in six countries under climate change and socio-economic development

Floods are among the most frequent and costliest natural hazards. Fluvial flood losses are expected to increase in the future, driven by population and economic growth in flood-prone areas, and exacerbated in many regions by effects of climate change on the hydrological cycle. Yet, studies assessing direct and indirect economic impacts of fluvial flooding in combination with climate change and socio-economic projections at a country level are rare. This study presents an integrated flood risk analysis framework to calculate total (direct and indirect) economic damages, with and without socio-economic development, under a range of warming levels from < 1.5 to 4 °C in Brazil, China, India, Egypt, Ethiopia, and Ghana. Direct damages are estimated by linking spatially explicit daily flood hazard data from the Catchment-based Macro-scale Floodplain (CaMa-Flood) model with country- and sector-specific depth-damage functions. These values input into an economic Input-Output model for the estimation of indirect losses. The study highlights that total fluvial flood losses are largest in China and India when expressed in absolute terms. When expressed as a share of national GDP, Egypt faces the largest total losses under both the climate change and climate change plus socio-economic development experiments. The magnitude of indirect losses also increased significantly when socio-economic development was modelled. The study highlights the importance of including socio-economic development when estimating direct and indirect flood losses, as well as the role of recovery dynamics, essential to provide a more comprehensive picture of potential losses that will be important for decision makers.

Impact of Natural Hazards on Forest Ecosystems and Their Surrounding Landscape under Climate Change

In the last decades, the increasing frequency of natural hazards has impacted forest ecosystems and their surroundings [...]

Assessing the spatiotemporal socioeconomic flood vulnerability of agricultural communities in the Potomac River Watershed

Flood events are one of the most destructive and yet increasingly frequent natural hazards causing a considerable amount of economic losses in the United States (US). The agricultural sector is particularly vulnerable to flood hazards. The representation of spatiotemporal distributions of the agricultural damage and the vulnerability of the agricultural communities are essential for flood risk management. Therefore, this study investigates spatiotemporal Socioeconomic flood vulnerability of the agricultural communities in the Potomac River Watershed (PRW), where corn and soybeans cultivation are one of the important agricultural activities. In this context, a combination of the widely used flood damage estimation tool HAZUS-MH and the county-based Social Vulnerability Index (SOVI) were utilized for the vulnerability assessment. The spatial distribution of agricultural communities vulnerable to flood was evaluated for the extreme and average damage conditions for 365 days along with the monthly average damage from a 100-year flood event. The maximum crop damage and most likely months to experience major flood events were found in the same temporal periods. The spatial distributions of damage and SOVI assessments suggested that the most vulnerable agricultural communities (Highland (VA) and Prince George’s (MD)) did not experience high flood damages in any scenario. The agricultural community in Shenandoah County was the most vulnerable in September and October, which has the highest flood probability. This high risk that is spatiotemporally highlighted can aid decision-makers regarding the resource allocation for mitigation efforts in the PRW. Our method can potentially be replicated throughout the country, thus protecting vulnerable agricultural communities.

RESILIENCE COVERAGE OF GLOBAL SUSTAINABILITY ASSESSMENT FRAMEWORKS: A SYSTEMATIC REVIEW

ABSTRACTSustainable development has been a popular concept since 1987 and the issuance of the Brundtland report. A diverse number of sustainability assessment frameworks are available to examine the environmental performance of buildings and communities. With the current pace of climate change and the increasing threat of stronger, more frequent natural hazards, however, there are doubts that sustainability alone is an effective response. Sustainability assessment frameworks in recent years have been criticized for not incorporating hazard resilience. To better understand the current level of emphasis put on resilience to natural hazards in green building rating systems, this study aims to assess the level of resilience integration in existing sustainability assessment frameworks. The results demonstrate an overall lack of resilience coverage in the frameworks with only four frameworks, CASBEE, LEED, Green Globes, and DGNB having resilience coverage of 27.5%, 15%, 2.6%, and 1.1% respectively. This confirms a need for more systematic integration of resilience indicators into sustainability rating systems to create combined frameworks for sustainability and resilience.