Extreme Hazards Research Articles

Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks

Abstract The objective of this research is to propose a novel framework for assessing the consequences of hazardous events on a water resources system using dynamic resilience. Two types of hazardous events were considered: a severe flood event and an earthquake. Given that one or both hazards have occurred and considering the intensity of those events, the main characteristics of flood dynamic resilience were evaluated. The framework utilizes an artificial neural network (ANN) to estimate dynamic resilience. The ANN was trained using a large, generated dataset that included a wide range of situations, from relatively mild hazards to severe ones. A case study was performed on the Pirot water system (Serbia). Dynamic resilience was derived from the developed system dynamics model alongside the hazardous models implemented. The most extreme hazard combination results in the robustness of 0.04, indicating a combination of an earthquake with a significant magnitude and a flood hydrograph with a low frequency of occurrence. In the case of moderate hazards, the system robustness has a median value of 0.2 and a rapidity median value of 162 h. The ANN's efficacy was quantified using the average relative error metric which equals 2.14% and 1.77% for robustness and rapidity, respectively.

Frightened or familiarised? Permanent residents' and second‐home owners' risk perceptions of extreme weather events

AbstractThe number and severity of extreme weather events have been increasing globally. Given the vulnerabilities of second homes to natural disasters, it is important to learn how their owners consider the related risks. This paper investigates the extreme weather‐event risk perceptions and their preconditions between second‐home owners and local people in the Little Beskid mountains in Poland. The results show that, despite significant differences in social, demographic and presence–absence terms, the two populations were very similar with respect to risk perception. It then lays the ground for community preparedness and successful recovery from extreme weather hazards.

Bioconversion of Floral Waste into Biocompost by using Microbial Consortium from Cow Dung

In the majority of the developing nations like India, the flower waste age happens to a great extent during capacities, loves, services, celebrations, and so on. Debasement of floral waste is an extremely sluggish interaction. Flower squander debasement likewise expands the interest for agro-based items. In India, a large amount of flowers are offered to sacred places, and many flowers are wasted. Abandoned sanctuaries are carried into the sea or dumped in accessible locations in the country, causing extreme environmental pollution and health hazards. Thus the current study was embraced to foster an effective microbial consortium from cow manure for degradation of blossom squander. Cow compost harbors a different gathering of microorganisms that might be useful to people because of their capacity to deliver a scope of metabolites. This assists with corrupting profoundly complex natural mixtures and converts it into straight forward stable final result Bio-Compost. Therefore, in the current work rather than individual disengages an endeavor is made to foster microbial consortium from cow dung for debasement of floral waste. Also in this research microbial consortia developed from cow dung which is very effective for degradation of floral waste within 45 days and helps to produce effective biocompost speedily from floral waste and this biocompost are much better than commercial available biocompost and chemical fertilizer.

Progress of research on compound extreme event and hazard assessment

Progress of research on compound extreme event and hazard assessment

The role of social institutions in community resilience following extreme natural hazard events

Social institutions such as hospitals and schools are among the main pillars of community stability. A drop in the functionality of hospitals and schools is likely to have short-term and long-term effects on a community, including a reduction in medical interventions, an increase in unschooled children, and population outmigration in search of essential social services. However, comprehensive community resilience models that consider the role played by social institutions in community stability following natural disasters are scarce at the present time. This paper provides a literature review and critical appraisal of previous studies on the resilience of hospital and school systems and their impact on community well-being. The review encompasses existing resilience models for single hospitals and schools, their role when connected with other hospitals and schools in a network, their reliance on each other as interdependent systems, and their role in community resilience and stability. Different mitigation strategies and policies to enhance hospital and school systems’ resilience after extreme natural hazards are also summarized. The paper concludes with a series of recommendations to improve current models for social institutions, enhance the connection between existing hospital and school resilience models and community resilience frameworks, and develop social stability indices that policymakers can use in preparing and mitigating future extreme events.

Transport infrastructure risk management in the context of climate change: policies, challenges, and opportunities

Climatic events and their effects reinforce concern about global warming. Since climate change influences the frequency and intensity of natural hazards, resilience and risk mitigation research is growing worldwide. The main goal is to prepare communities for the effects of increasingly extreme hazards. The interaction between academia and asset owners and operators has made it possible to develop practical tools and risk assessment methodologies seeking effective decisions on asset management in face of these events. The challenge is complex and a solution will require knowledge from different fields. This work presents some existing research projects, methodologies, and policies, their successes, and the challenges arising from their application. The future of risk management research is discussed in this document with emphasis on the need to join the efforts of all stakeholders.

Severe Socioeconomic Exposures Due to Enhanced Future Compound Flood-Heat Extreme Hazards in China

As the climate warms, a new hazard, compound flood-heat extreme (CFH) events, characterized by the rapid succession of devastating floods and deadly heat (or vice-versa), are becoming increasingly frequent, threatening infrastructure and ecosystems. However, how this CFH hazard will change under future anthropogenic warming in China and their potential population and economic exposures remains unexamined. Here, we systematically quantify the projected changes in bivariate CHF hazards for 187 catchments in China during the 2071–2100 period relative to the 1985–2014 period and investigate the potential population and gross domestic product (GDP) exposure, by developing a climatic-hydrological-socioeconomic modelling chain. We find that there is a nationwide increase in CFH hazards and the historical 30-year CFH episodes are projected to increase by 10 times in southern catchments. Under the synergistic impacts of changing CFH episodes and population (GDP), a mass of people in southern (0.79–2.13 thousand/km2) and eastern (1.68 thousand/km2) catchments and an enormous sum of GDP in eastern catchments (400–912 million/km2) will be exposed to increasing CFH hazards. Our results highlight the necessity of improving both societal resilience and mitigation solutions to address such weather-related hazards.

Impacts of Different Socioeconomic Development Levels on Extremely Wet/Dry Events in Mainland China

The impacts of human activity (denoted by population), economic, and social development (denoted by gross domestic product–GDP) on extremely wet/dry (or drought) events are important for humans to tackle extreme hazards. This research aims to investigate the variations in maximum values (SPEI_MAX) and minimum values (SPEI_MIN) of a 12 month standardized precipitation evapotranspiration index (SPEI12-month) for the selected 525 sites at different socioeconomic development levels (SDLs) (classified by population and GDP) in China between 2000–2018, and to analyze the impacts of increased population/GDP/SDLs on extremely wet/dry events. The linear correlations between SPEI12-month/SPEI_MAX/SPEI_MIN and population/GDP were conducted for all the sites. The relationship between linear slopes of population (PopuLS)/GDP(GDPLS) and SPEI_MAX (SPEI_MAXLS)/SPEI_MIN (SPEI_MINLS) were further studied. The results show that the extremely wet events denoted by SPEI_MAX become worse and the extreme drought events denoted by SPEI_MIN tend to be milder over time. The years 2016 and 2011 were extremely wet and extremely dry in China. There were general increasing trends in SPEI_MAX and decreasing trends in SPEI_MIN as the SDL increased from 1 to 6. This gradual, continuous increase/decrease potentially affected levels 5 and 6. Moreover, extremely wet events were more severe in developed big municipal cities of higher SDLs and extreme drought events were more severe for lower SDLs. This research can supply references for policy makers to prevent extreme disasters.

Evaluation of Ecosystem Services in Macao Based on InVEST Model

Global climate change leads to the frequent occurrence of Extreme climatic hazards such as flooding, high temperature and storm surges. High-density coastal cities have high disaster vulnerability due to the geographical location and agglomeration of social and economic resources. Therefore, it is urgent to improve resilience to ensure sustainable urban development. Ecosystems can significantly improve the resilience of cities due to their functions of carbon sinks, flood regulation, improving UHI and optimizing air quality. Therefore, this paper takes Macao, a typical high-density coastal city, as an example. Firstly, InVEST is used to construct an ecosystem services evaluation model including habitat quality, carbon storage and water supply. Secondly, the ecosystem services of Macao in 2010, 2015 and 2020 were evaluated to identify the spatial and temporal variation characteristics. Finally, core ecological protection zones, general ecological protection zones and ecological restoration zones were defined to provide a basis for improving the ecosystem service value and climate resilience of Macao.

An Incentive Based Road Traffic Control Mechanism for Covid-19 Pandemic Alike Emergency Preparedness and Response

The Covid-19 pandemic has hit hard on the highly-organised yet risk-vulnerable modern societies, and has introduced new characteristics to large-scale emergencies, which feature long persistence in duration, high frequency in occurrence, large sensitivity to individual behaviours, and extreme high hazard propagation rate owing to the highly-efficient transport networks. This has raised new challenges on long-term emergency preparedness of urban transportation systems in terms of safety, efficiency, robustness and sustainability. Non-cooperative behaviours of transport participants could result in severe performance degradation in emergency preparedness, and mandatory restrictions in human activities can be economical costly and difficult in operation. In addition, current arrangement models for the disaster financial assistance have not been elaborately designed for civilian behaviour optimisation although with great potential as an economical instrument. Hence, in this paper, we propose a reward based traffic control mechanism to generate cooperative behaviours and optimise resource allocation in an urban transportation system for emergency preparedness via distributing credit coins, which can also be treated as a financial assistance approach during long-term disasters. A queueing theory based analytic model is employed to mimic the behaviours of civilians in the transportation system under the emergency preparedness state and a probability choice model is utilised to optimise the emergency preparedness strategies of the system. The experimental results show that the introduction of the incentive based traffic control mechanism can significantly reduce hazard response time, travel delay as well as the energy usage of the urban transportation system at the expense of monetary rewards.

Penerapan Kesehatan dan Keselamatan Kerja dengan Metode Hazard Operability Study di Industri Mebel Kabupaten Sukoharjo

The furniture industry is one of the largest industries in Sukoharjo Regency. Indeed, this industry is able to penetrate the international market share so that it has great potential. Behind this great potential, it is possible that there are potential hazards and work risks that arise in the manufacture of furniture. This study aims to determine the application of occupational health and safety in the furniture industry in Sukoharjo Regency. This research uses data analysis method with hazard operability study method. Based on the results of the study stated that there are five stages of work in the furniture industry in Sukoharjo Regency. The first step is sanding and then painting. The third stage is followed by drying and drying then packing and the last is the transportation of goods. Based on the results of the study, it can be seen that the potential for extreme work hazards is 10%, low risk is 40% and the rest is moderate and high risk.

Thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects

Global warming has altered the thermodynamic and dynamic environments of climate systems, affecting the biogeochemical processes between the geosphere and atmosphere, which has significant impacts on precipitation extremes and the terrestrial carbon budget of ecosystems. Existing studies have reported a hook structure for precipitation extreme-temperature relationships but have rarely examined the underlying physical mechanisms. Previous studies have also failed to quantify the impact of precipitation on ecosystem productivity, hindering the assessment of future extreme climatic hazards and potential ecosystem risks. To reveal the thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects, this study utilizes over ten multisource datasets (i.e., satellite, reanalysis, climate model, land surface model, machine learning reconstruction, and flux tower measurements). We first assess the response of water-heat-carbon flux to precipitation extremes and explain the underlying physical mechanisms behind the hook structures in terms of atmospheric thermodynamics and dynamics. Based on outputs from five global climate models (GCMs) under ISIMIP3b, we project future changes in the hook structures as well as their impacts on precipitation extremes. Finally, we discuss the impact of precipitation on the terrestrial carbon budget by using outputs from the CLM4.5 model. The results show that precipitation extremes are usually accompanied by strong exchanges of water and heat and demonstrate a nonlinear relationship between precipitation and ecosystem productivity. The intensity (duration) of extreme precipitation is intensifying (decreasing) over most areas of the globe, whereas three-dimensional precipitation events are becoming more concentrated. Atmospheric dynamics play a key role in shaping the hook structure. The structure is not stable; it shifts under climate change and is projected to result in a 10–10% intensification in precipitation by the end of this century. Moderate levels of precipitation contribute to carbon assimilation in ecosystems, and the response of the carbon budget to precipitation is relatively stable under climate change.

An Experimental Study on the Cell Balancing Parameters for Faulty Cell Detection in a Battery Module

Along with global efforts to reduce the carbon footprint, electrification of powertrains is occurring in various applications, certainly including transportation systems. One of the most important components is an electric energy storage system, i.e., a battery pack. Regardless of battery form factors, such as cylindrical, pouch and prismatic type, it is critical to maintain the safety of the battery module/pack by monitoring the conditions of each and every battery cell of the battery pack. It becomes even more critical as the battery cells are used over many charging and discharging cycles. Thermal runaways of the battery packs can even be triggered by a single faulty battery cell which degrades in an unexpected manner and speed compared to the neighboring battery cells, resulting in extreme fire hazards. Typically, this faulty cell with an abnormally increased internal resistance can be detected using a voltage sensor or a temperature sensor. However, in this study, instead of depending on those sensors, activities of cell balancing switching devices are used to identify a degraded cell compared to other cells in a relative manner. A currently proposed faulty cell detection algorithm was developed through multiple simulations with Matlab Simulink®, then, a simple BMS prototype was built and tested as a proof of concept.

Probabilistic simulation of big climate data for robust quantification of changes in compound hazard events

Understanding changes in extreme compound hazard events is important for climate mitigation and policy. By definition, such events are rare so robust quantification of their future changes is challenging. An approach is presented, for probabilistic modelling and simulation of climate model data, which is invariant to the event definition since it models the underlying weather variables. The approach is based on the idea of a ‘moving window’ in conjunction with Generalised Additive Models (GAMs) and Bayesian inference. As such, it is robust to the data size and completely parallelizable, while it fully quantifies uncertainty allowing also for comprehensive model checking. Lastly, Gaussian anamorphosis is used to capture dependency across weather variables. The approach results in probabilistic simulations to enable extrapolation beyond the original data range and thus robust quantification of future changes of rare events. We illustrate by application to daily temperature, humidity and precipitation from a regional climate model.

Policy implementation for extreme hazard events in Caribbean Small Island Developing States: a case study – Trinidad and Tobago and Grenada

PurposeExtreme natural hazard events in the Caribbean continue to result in major adverse consequences. Studies of disaster experiences have identified operational deficiencies that limited the effectiveness of disaster management policies in live emergencies. This paper reports on a study of the implementation characteristics of specific public disaster risk reduction and response measures in two Caribbean Small Island Developing States (SIDS), Trinidad and Tobago and Grenada, which may impact the success of these measures. The purpose of this paper is to examine these characteristics and their potential impacts.Design/methodology/approachThe authors collected data on specific aspects of disaster risk management (DRM) policy implementation from policy documents and interviews with public DRM agencies. A sample of business entities also provided data on their interactions with public risk management measures. The data focussed on operational aspects of implementation to identify likely impacts on hazard event outcomes.FindingsThe study identifies implementation deficiencies that may hamper achievement of risk reduction objectives and limit the effectiveness of emergency response.Research limitations/implicationsThe findings may be instructive for other Caribbean SIDS which share similar economic and social characteristics, natural hazard exposures and potential catastrophic outcomes.Practical implicationsThe findings suggest tactical areas of focus to enhance the operationalisation of policy.Social implicationsImproved operational effectiveness will support the efforts of Caribbean SIDS to reduce the scale of adverse outcomes on people and property.Originality/valueThe findings of this study broaden the scope of Caribbean disaster studies to provide an insight into operational weaknesses that may be recognised and addressed prior to hazard events.

Flash Flood Hazard Mapping Using Remote Sensing and GIS Techniques in Southwestern Saudi Arabia

Flash flooding is one of the most significant natural disasters in arid/hyperarid regions and causes vast property damage and a large number of deaths. For mitigating and reducing flood risks, data from several remote sensing satellite images—Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), Landsat 8 Operational Land Imager (OLI), and Tropical Rainfall Measuring Mission (TRMM)—were prepared and combined through a GIS-based multicriteria decision-making technique to test and delineate the flash flood vulnerable areas of Wadi Hali in southwestern Saudi Arabia. Several flash flood thematic layers representing topographic, geomorphic, climatic, and hydrological conditions were prepared, normalized, and combined through a GIS- based analytic hierarchy process (AHP) technique to obtain flash flood hazard zones (FFHs). This method successfully presented a satisfactory output map that revealed six zones of flood risk, and areas of extreme hazard covered about 13% of the entire basin. Landsat 8 band composite 7, 5, and 3 and field data validated the FFHs. This map considered a key requirement for sustaining safe settlements downstream of Wadi Hali. Overall, the integration of remote sensing and GIS techniques revealed significant areas of flash flood zones in an arid region.

Plasticity in Compensatory Growth to Artificial Defoliation and Light Availability in Four Neotropical Understory and Forest Edge Herb Species.

Simple SummaryFor monocot herbs growing in the understory of wet tropical forests face an extreme hazard in falling branches and debris from the canopy. We compared the response of two species of understory herbs to two other species of herbs growing at the forest edge or in large gaps. We made the prediction that the forest edge herb species would be better able to compensate for damage because of compensatory growth made possible in the higher light environment than that experienced by the shade-tolerant understory herbs. Our experimental studies showed that both groups of species were tolerant of defoliation under high and intermediate light conditions, but under low light growth conditions the forest edge species showed higher mortality. This finding suggests that a variety of functional growth traits may be structuring post-damage response in understory and forest edge herbs.Defoliation from falling branches is a major factor in the survival of understory herbs in tropical rainforests. Experimental studies of defoliation under three levels of light environment compared responses to partial and total defoliation in four species of tropical rainforest understory herbs. We predicted that elevated levels of light availability would help compensate for damage to through compensatory growth in both understory and forest edge species and that forest edge species would more effectively compensate under high light conditions than shade-tolerant species from the forest understory All species showed a high tolerance to defoliation under high and intermediate light conditions. Under low-light conditions survival differed dramatically with minimal mortality in forest-edge species compared to high mortality in completely defoliated understory species. Defoliation, and light × defoliation interactions, impacted multiple growth traits in understory species. In contrast, forest-edge species showed no effect of defoliation except on total biomass, and only one light × defoliation interaction was observed. Our results indicate that differences in biomass allocation, leaf ecophysiology, and other growth parameters between forest understory and edge species may be structuring post-damage response in understory and forest edge herbs.

Assessment of Chemical Risks Associated with Hydrometeorological Phenomena in a Mexican Port on the Gulf of Mexico

Accidents in port areas in the Gulf of Mexico have had great economic costs, since this is an area exposed to extreme phenomena. Tropical cyclones or cold fronts, also known as Tehuantepecers, result in intense winds and waves that impact the coastal infrastructure. The chemical risk associated with extreme winds and waves for the fuel storage tanks of the facility of the Port of Veracruz, the main Mexican port in the Gulf of Mexico, was evaluated with a historical analysis of accidents as a tool to identify significant factors in disasters and establish risk acceptance criteria. It was found that the critical hazard threshold for Veracruz corresponds to winds stronger than 160 km/h (44 m/s) that may result in coastal waves of more than 5 m high. The vulnerability to these phenomena was calculated with the vulnerability index (VI), considering the structural, functional, and chemical factors in the infrastructure, including exposure levels. By means of a risk matrix, it was determined that gasoline storage tanks have a moderate chemical risk, since exposure to the extreme wind wave hazard is low, and diesel tanks are at low risk. These assessments are important elements to consider in the expansion plans for the Port of Veracruz.

Sensitivity of simulating Typhoon Haiyan (2013) using WRF: the role of cumulus convection, surface flux parameterizations, spectral nudging, and initial and boundary conditions

Abstract. Typhoon (TY) Haiyan was one of the most intense and highly destructive tropical cyclones (TCs) to affect the Philippines. As such, it is regarded as a baseline for extreme TC hazards. Improving the simulation of such TCs will not only improve the forecasting of intense TCs but will also be essential in understanding the potential sensitivity of future intense TCs with climate change. In this study, we investigate the effects of model configuration in simulating TY Haiyan using the Weather Research Forecasting (WRF) Model. Sensitivity experiments were conducted by systematically altering the choice of cumulus schemes, surface flux options, and spectral nudging. In addition to using the European Centre for Medium-Range Weather Forecasts Reanalysis fifth-generation (ERA5) single high-resolution realization as initial and boundary conditions, we also used 4 of the 10 lower-resolution ERA5 data assimilation system (EDA) ensemble members as initial and boundary conditions. Results indicate a high level of sensitivity to cumulus schemes, with a trade-off between using Kain–Fritsch and Tiedtke schemes that have not been mentioned in past studies of TCs in the Philippines. The Tiedtke scheme simulates the track better (with a lower mean direct positional error, DPE, of 33 km), while the Kain–Fritsch scheme produces stronger intensities (by 15 hPa minimum sea level pressure). Spectral nudging also resulted in a reduction in the mean DPE by 20 km, and varying the surface flux options resulted in the improvement of the simulated maximum sustained winds by up to 10 m s−1. Simulations using the EDA members initial and boundary conditions revealed low sensitivity to the initial and boundary conditions, having less spread than the simulations using different parameterization schemes. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in the track and intensity of simulating intense tropical cyclones.

Climate change threats to cultural and natural heritage UNESCO sites in the Mediterranean

The study presents a time-dependent analysis of threats from man-made climate change at 244 UNESCO cultural and natural heritage sites in the Mediterranean. The hazards in our research are estimated by indices based on extremes of heat, fire weather conditions, heavy rainfall days, frost days, changes in mean sea level and aridity at each site. These indices were calculated from regional EUROCORDEX simulations, cover the period 1971–2100 and refer to two IPCC emission scenarios, namely RCP4.5 and RCP8.5. A combined threat index was next calculated, as explained in the text, together with its synergy with local exposure geophysical threats, such as seismicity, topography and proximity to forests and seas. All indices related to man-made climate change show an overall increasing trend from present to the end of the twenty-first century. Some of these increasing trends are intensified after the 2030s and 2040s, except for the case of the days with frost. As the global warming evolves, in both IPCC scenarios studied, the combined threat to the majority of UNESCO sites studied increases. Notable is the amplification of the threat at sites vulnerable to seismic activity and to other local or regional topography and geophysical regional characteristics. Our conclusion is that the majority of heritage sites in the Mediterranean are vulnerable to an increasing rate of threats from man-made global warming and extreme events. Seismic activity is magnifying these threats only at the sites in which that additional hazard applies. Based on the proposed combined threat index, for the worst-case scenario (RCP8.5) 35 monument sites fall within the “high hazard” and 12 sites fall under the category “extreme hazard”.