Likelihood Of Hazard Research Articles

Assessing NOAA Rip-Current Hazard Likelihood Predictions: Comparison with Lifeguard Observations and Parameterizations of Bathymetric and Transient Rip-Current Types

Abstract Rip currents, fast offshore-directed flows, are the leading cause of death and rescues on surf beaches worldwide. The National Oceanic and Atmospheric Administration (NOAA) seeks to minimize this threat by providing rip-current hazard likelihood forecasts based on environmental conditions from the Nearshore Wave Prediction System. Rip currents come in several types, including bathymetric rip currents that form when waves break on sandbars interspersed with channels and transient rip currents that form when there are breaking waves coming from multiple directions. The NOAA model was developed and tested in an area where bathymetric rip currents may be the most prevalent type of rip current. Therefore, model performance in regions where other types of rip currents (e.g., transient rip currents) may be more ubiquitous remains unknown. To investigate the efficacy of the NOAA model guidance in the context of different rip-current types, we compared modeled rip-current probabilities with physical-based parameterizations of bathymetric and transient rip-current speeds. We also compared these probabilities to lifeguard observations of bathymetric and transient rip currents from Salt Creek Beach, California, in summer and fall 2021. We found that the NOAA model skillfully predicts a wide range of hazardous parameterized bathymetric speeds but generally underpredicts hazardous transient rip-current speeds and the hazardous rip currents observed at Salt Creek Beach. Our results demonstrate how wave parameters, including directional spread, may serve as environmental indicators of rip-current hazard. By evaluating factors that influence the skill of modeled rip-current predictions, we strive toward improved rip-current hazard forecasting. Significance Statement The purpose of this study is to evaluate how well the NOAA rip-current hazard model predicts different rip-current types. Accurate forecasting of rip currents is important because rip currents are the leading cause of death and rescues at surf beaches worldwide. By comparing the performance of the NOAA model to parameterized rip-current speed and lifeguard observations of rip-current strength, we highlighted the model’s decreased ability to predict hazardous transient rip currents compared to hazardous bathymetric rip currents. Because bathymetric and transient rip currents are driven by different environmental conditions, an improved hazard model must be sensitive to these different conditions to predict a greater range of hazardous rip currents.

Metals profile of milled shrimps and the potential risk associated with their consumption

The presence of metals in milled shrimps sold on some major markets in Kumasi were investigated to ascertain their levels and the potential health risk they may pose to humans when ingested, due to the level of pollution in the marine environment where these shrimps are obtained from. The samples, which comprised of 30 composites, were analysed using x-ray florescence spectrometry and found to contain Co, Cr, Cu, Fe, K, Mo, Ca, Zn, As, Sr, and Zr with average concentrations of 4.09 mg kg− 1, 5.17 mg kg− 1, 25.14 mg kg− 1, 351.47 mg kg− 1, 9050.74 mg kg− 1, 4.08 mg kg− 1, 21984.48 mg kg− 1, 696.89 mg kg− 1, 8.99 mg kg− 1, 328.54 mg kg− 1, and 9.86 mg kg− 1 respectively. Non-carcinogenic risk indicators analysed suggested a likelihood of health hazard when the milled shrimps are ingested, particularly concerning is the levels of arsenic determined. The arsenic may, however, be in organic form which will make it less of a concern. The levels of the metals could not be linked statistically to the milling process after comparing them to procured controls, which may suggest that these metals may have been picked up in the aquatic environment and/or prior to milling. There is a need, therefore, for action to reduce pollution and remediate the aquatic environment.

Optimizing safety performance through risk-based modeling in Nigeria’s oil and gas sector

The Nigerian oil and gas sector is fraught with safety challenges that undermine operational integrity and worker welfare. Addressing these issues requires a nuanced risk-based intervention and modeling approach to improve safety performance. This study investigated the safety challenges in Nigeria's oil and gas sector, focusing on identifying and addressing hazards to enhance operational integrity and worker welfare. A semi-quantitative approach was used to develop a comprehensive hazard checklist, aligned with ISO standards and expert insights. Data on hazard likelihood and severity were gathered through questionnaires distributed among a diverse group of industry experts, workers, and stakeholders. The analysis highlighted key risks like inadequate infrastructure, valve and seal failures, security concerns, and oil spill risks, underscoring the need for targeted interventions to promote a safer working environment and reduce accident risks.

Development of flood forecasting and warning system using hybrid approach of ensemble and hydrological model for Dharoi Dam

Abstract The most frequent natural disaster is flooding. Advanced forecasting systems are lacking in developing countries. The majority of urban areas are located close to flood plains for rivers. Accurate flood forecasting is necessary for reservoir planning and flood management. The Sabarmati River's atmospheric-hydrologic ensemble flood forecasting model has been developed using TIGGE data. Precipitation can be reliably predicted by TIGGE's global ensemble numerical weather prediction (NWP) systems. By using NWP data, flood forecasting systems may be extended from hours to days. Ensemble weather forecasts are produced using the European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction together with 5-day lead times from TIGGE. The flood occurrences from 2015, 2017, and 2020 were used for the calibration and validation of the ensemble flood forecasting model. Bias was corrected using Bayesian model averaging (BMA), heterogeneous extended linear regression, censored non-homogeneous linear regression (cNLR), and other statistical downscaling techniques. Forecasted and downscaled precipitation data were checked using the Brier score and rank likelihood score. For cNLR, Brier's score performed admirably. The specificity vs. sensitivity performance of the cNLR and BMA approaches is 91.87 and 91.82%, respectively, according to receiver operating characteristic and area under the curve diagrams. Models with the hybrid hydrologic coupling approach accurately predict floods. Users may predict peak time and peak discharge hazard likelihood with reliability using peak time and flood warning probability distributions.

A semiautomated risk assessment method for consumer products.

In this study, we develop a model that assesses product risk using online reviews from Amazon.com. We first identify unique words and phrases capable of identifying hazards. Second, we estimate risk severity using hazard type weights and risk likelihood using total reviews as a proxy for sales volume. In addition, we obtain expert assessments of product hazard risk (risk likelihood and severity) from a sample of high- and low-risk consumer products identified by a computerized risk assessment model we have developed. Third, we assess the validity of our computerized product risk assessment scoring model by utilizing the experts' survey responses. We find that our model is especially consistent with expert judgments of hazard likelihood but not as consistent with expert judgments of hazard severity. This model helps organizations to determine the risk severity, risk likelihood, and overall risk level of a specific product. The model produced by this study is helpful for product safety practitioners in product risk identification, characterization, and mitigation.

Predictors of Dengue Preventive Practices Based on Precaution Adoption Process Model among Health Care Professionals in Northwest of Iran.

Dengue fever as a mosquito-borne disease, has rapidly spread due to climate change, globalization, and human behavior. Iran is prone to dengue fever, as its vector recently has been found in the country. This study aimed to assess predictors of dengue preventive practices based on Precaution Adoption Process Model (PAPM) factors in West Azerbaijan province, northwest of Iran. This cross-sectional study conducted on 405 health professionals of communicable disease sector who were interested in study participation. Data-gathering instrument was an online researcher-made questionnaire consisting of demographic characteristics (11 items), questions based on PAPM, and dengue preventive practices (85 items). Content validity and reliability of the instrument, content validity ratio, content validity index, and Cronbach α were utilized, respectively. Descriptive, analytical, and regression analysis using SPSS and STATA were examined. Regression analysis revealed that awareness of appropriate actions for dengue prevention was a stronger predictor of preventive practice in borderline and appropriate categories (β= 4.09, p< 0.001) and (β= 4.42, p< 0.001), respectively. Among factors of PAPM, beliefs about precaution effectiveness and difficulty in borderline (β= 1.04, p= 0.04) and appropriate (β= 1.12, p= 0.03) groups had direct and significant relation with dengue preventive practice. The highest mean score of beliefs about hazard likelihood and severity factor was related to dengue prevention. Therefore, theory-based interventions that address beliefs about precaution effectiveness and difficulty can lead to assistance in acting. To improve dengue preventive practices, a well-designed promotive intervention that addresses associated factors in a context-specific manner is essential.

Prediction of Groundwater Arsenic Hazard Employing Geostatistical Modelling for the Ganga Basin, India

Elevated arsenic concentrations in groundwater in the Ganga–Brahmaputra–Meghna (GBM) river basin of India has created an alarming situation. Considering that India is one of the largest consumers of groundwater for a variety of uses such as drinking, irrigation, and industry, it is imperative to determine arsenic occurrence and hazard for sustainable groundwater management. The current study focused on the evaluation of arsenic occurrence and groundwater arsenic hazard for the Ganga basin employing Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) models. Furthermore, arsenic hazard maps were prepared using a Kriging interpolation method and with overlay analysis in the GIS platform based on the available secondary datasets. Both models generated satisfactory results with minimum differences. The highest hazard likelihood has been displayed around and along the Ganges River. Most of the Uttar Pradesh and Bihar; and parts of Rajasthan, Chhattisgarh, Jharkhand, Madhya Pradesh, and eastern and western regions of West Bengal show a high arsenic hazard. More discrete results were rendered by the AHP model. Validation of arsenic hazard maps was performed through evaluating the Area Under Receiver Operating Characteristics metric (AUROC), where AUC values for both models ranged from 0.7 to 0.8. Furthermore, the final output was also validated against the primary arsenic data generated through field sampling for the districts of two states, viz Bihar (2019) and Uttar Pradesh (2021). Both models showed good accuracy in the spatial prediction of arsenic hazard.

A simulation analysis of the effects of government policy and changing discount and surcharge rate on the crop insurance purchase rate: Focusing on the rice farm

In this study, the most effective policy direction is proposed by comparing the simulation results on the change in farmers crop insurance purchase rate. We set the base scenario reflecting the current level of crop insurance purchase rate under adverse selection and evaluate the effect of additional policies through Monte Carlo simulations. As a result of the analysis, the most influential policy is identified to be lowering the surcharge rate. Decreasing the surcharge rate is expected to increase the likelihood of moral hazard and adverse selection. This causes a loss of insurance company in the mid-term. On the other hand, policy that provides an additional discount of insurance premium to low-risk farms have relatively low effectiveness in the short-term. However, this policy is expected to increase the insurance purchase rate of a low-risk farm, thereby reducing a loss of insurance company. This will lower insurance premium for crop insurance in the mid-term.

Anti‐Learning Behavior Toward Safety Risk: The Roles of Internal Context and Social Contagion

ABSTRACTManaging safety has become increasingly important in global operations. Surprisingly, the literature provides limited clues on what influences future accident hazards after the happening of a recent minor operational incident (MOI) in an organization. We examine the impacts of internal context (direct MOI experience) and external context (indirect MOI experience) on a focal organization's future serious accident hazard. Using an archival incident dataset from the liner shipping industry and drawing upon normalized deviation and social contagion theory, we find that after a recent MOI in a focal organization, the direct (internal context) and indirect (contagion source) MOI experience “increase” the likelihood of accident hazard. Furthermore, within the indirect MOI experience, there is “no” differential impact between related (same type and same region) and unrelated experience, whereas within related experience, spatial (region) and social (type) proximity do not differ in influencing the chance of future serious accident hazard happening. Our findings provide important implications for theory, practice, and policy‐making in safety management.

Methodology for the Study of Near-Future Changes of Fire Weather Patterns with Emphasis on Archaeological and Protected Touristic Areas in Greece

This work introduces a methodology for assessing near-future fire weather pattern changes based on the Canadian Fire Weather Index system components (Fire Weather Index (FWI), Initial Spread Index (ISI), Fire Severity Rating (FSR)), applied in touristic areas in Greece. Four series of daily raster-based datasets for the fire seasons (May–October), concerning a historic (2006 to 2015) and a future climatology period (2036–2045), were created for the areas under consideration, based on high-resolution climate modelling with the Representative Concentration Pathway (RCP), PCR 4.5 and RCP 8.5 scenarios. The climate model data were obtained from the European Coordinated Downscaling Experiment (EURO-CORDEX) climate database and consisted of atmospheric variables as required by the FWI system, at 12.5 km spatial resolution. The final datasets of the abovementioned variables used for the study were processed at 5 km spatial resolution for the domain of interest after applying regridding based on the nearest neighbour interpolating process. Geographic Information Systems (GIS) spatial operations, including spatial statistics and zonal analyses, were applied on the series of the derived daily raster maps in order to provide a number of output thematic layers. Moreover, historic FWI percentile values, which were estimated for Greece in the frame of a past research study of the Environmental Research Laboratory (EREL), were used as reference data for further evaluation of future fire weather changes. The straightforward methodology for the assessment of the evolution of spatial and temporal distribution of Fire weather Danger due to climate change presented herewith is an essential tool for enhancing the knowledge for the decision support process for forest fire prevention, planning and management policies in areas where the fire risk both in terms of fire hazard likelihood and expected impact is quite important due to human presence and cultural prestige, such as archaeological and tourist protected areas.

Exposure Risk Assessment of the Municipal Waste Collection Activities during Covid-19 Pandemic

An increasing amount of waste concurrently further extends the risk of exposure to hazardous material among waste collectors. In light of the COVID-19 crisis, municipal waste collectors are one of the most at-risk groups of SARS-Cov-2 exposure. Risk assessment included hazard identification, evaluation of existing control level at the workplace, estimation of likelihood and severity of hazard, risk determination, and control measure recommendations. Five waste collection activities were identified and reviewed. High-risk exposure includes collection of garbage, mechanical manipulation of compactor lorries and unloading of garbage at the disposal site. There is poor practice of personal hygiene and unestablished continuous monitoring of personal protective equipment supplies. The preventive measures in the waste collection industry are influenced by several factors. Until the preventive measures are adopted into practice and adapted according to each company’s requirements, biological agents continue to be risk factor to the health workers.Significance for public healthInfectious diseases among waste collectors can provoke significant detrimental consequences and mortality if left untreated. Comprehensive analysis of waste collection activity is unavailable to pinpoint the potential uncertainty of transmission of infectious agents from polluted environment. The decrees of this study are crucial for the Public Health Division and Municipal Council to evaluate the strength of health promotion and level of prevention measures at the workplace. This knowledge is pivotal for the organization to focus on the precise issues and execute necessary risk control measures. In due time, morbidity and mortality due to occupational exposure to possible infectious agents in the working environment can be averted and dwindled.

Stochastic comparisons of parallel systems with generalized Kumaraswamy-G components

This paper treats the problem of stochastic comparisons of two parallel systems with independent heterogeneous components having lifetimes following exponentiated Kumaraswamy-G model. The cases of same and different parent distribution functions are considered. Majorization type partial orders-based sufficient conditions in comparing the largest order statistics in terms of the usual stochastic order, reversed hazard rate order and likelihood ratio order are obtained. The likelihood ratio order among largest order statistics is established for the heterogeneous multiple-outlier exponentiated Kumaraswamy-G models. Several numerical examples are presented for illustrations as well.

Use of time-varying and time-constant coefficient in hazard event analysis of Girl’s child marriage: A study from the Empowered Action Group (EAG) states of India

IntroductionPractice of child marriage in India still is not an uncommon event and considered as one of the social evil that should be addressed properly. Enactment of law is still far from eliminating the practices of girl child marriage and it remains a widespread practice in the Empowered Action Group (EAG) states in India. ObjectiveThe study examines the effect of selected time varying and time constant coefficients on the prevalence of girl child marriage in the EAG states. In this regard the study has incorporated 4th round (2015–2016) of National Family Health Survey data. MethodsCox regression hazard model were employed to assess how likelihood of hazard (girl’s child marriage) vary in different socio-economic domains. Girls’s are susceptible to get marriage prior to completion of 18 years age, considered as a hazard or failure otherwise survived from the hazard. ResultsFindings consolidated and revealed the ground truth that there has a significant association between girl child marriage and respondent’s wealth status, level of education, place of residence, as well as their religious belief and caste/tribe affiliation. Girls with no education or primary level of education, living in rural areas belong to poorest or poorer wealth quintile are more likely to be married at an early age. The likelihood of marriage of girl child is also higher among those girls whose religious belief is Hindu and affiliated to general category. ConclusionFindings suggest that by facilitating the educational opportunity for girls, economic support to families belongs to poorest categories, increasing awareness in rural area about the adverse effect of early childhood marriage are the key and effective steps to mitigate the issue with a coordinated way.

Analyzing corn and cotton producers optimal prevented planting decision on moral hazard

AbstractThe prevented planting provision U.S. crop insurance programs protects producers from financial losses and risk associated with delayed planting. This provision has recently undergone some changes due to concerns about moral hazard in this provision. However, little is known about the likelihood of moral hazard in prevented planting and how these changes impact this possibility. We compared the net returns and variability of net returns for the four prevented planting options available for a corn (Zea mays L.) and upland cotton (Gossypium hirsutum L.) producer assuming soybean [Glycine max (L.) Merr.] as a viable second crop. We determine the optimal prevented planting option using the current prevented planting coverage factor at three crop insurance coverage levels. We also show how reductions in the prevented planting coverage factor would change the optimal selection and moral hazard in prevented planting. Data were collected from non‐irrigated corn, upland cotton, and soybean planting date experiments located in Tennessee. Yield response functions to planting date for corn, cotton, and soybean were estimated and incorporated into simulation models to generate distributions of net returns. Risk neutral, profit maximizers would choose a late planting option over the full prevented planting payment, but as risk aversion increases, the full prevented planting payment was preferred. Reduction in prevented planting coverage factors will likely reduce the likelihood an insured producer chooses to not produce a crop and take the full prevented planting indemnity payment, despite planting during the late planting period or switching crops being more profitable options.

Constituting safety in hunter’s education: An analysis of safety messages in Texas hunter’s training discourse

Risk communication includes safety messages to reduce the likelihood of hazard and increase the likelihood of reliability. Hunter’s education in the state of Texas uses safety messages to reduce fatal or injurious incidents and to promote a positive image of hunting as a safe, leisure sport. Analysis of Texas’ hunters education training materials and messages related to safety reveals that safety messages construct an image of hunters as practicing safety first, conservationists, ethical, law abiding, and other-oriented. Given Texas safety record, much is to be learned about safety messaging that adopts a positive or ideal image that the trainee identifies.

Earthquake slip surfaces identified by biomarker thermal maturity within the 2011 Tohoku-Oki earthquake fault zone

Extreme slip at shallow depths on subduction zone faults is a primary contributor to tsunami generation by earthquakes. Improving earthquake and tsunami risk assessment requires understanding the material and structural conditions that favor earthquake propagation to the trench. We use new biomarker thermal maturity indicators to identify seismic faults in drill core recovered from the Japan Trench subduction zone, which hosted 50 m of shallow slip during the Mw9.1 2011 Tohoku-Oki earthquake. Our results show that multiple faults have hosted earthquakes with displacement ≥ 10 m, and each could have hosted many great earthquakes, illustrating an extensive history of great earthquake seismicity that caused large shallow slip. We find that lithologic contrasts in frictional properties do not necessarily determine the likelihood of large shallow slip or seismic hazard.

Exponentiated models preserve stochastic orderings of parallel and series systems

In this paper, we establish that the usual stochastic, hazard rate, reversed hazard rate, likelihood ratio, dispersive and star orders are all preserved for parallel systems under exponentiated models for lifetimes of components. We then use the multiple-outlier exponentiated gamma models to illustrate this result. Finally, we consider the dual family with exponentiated survival function and establish similar results for series systems. The results established here extend some well-known results for series and parallel systems arising from different exponentiated distributions such as generalized exponential and exponentiated Weibull, established previously in the literature.

Emotion provides feedback about thinking styles to influence natural hazard likelihood and perceived response preparedness

Making judgments about whether one is prepared for a natural hazard (e.g., tornado, earthquake) involves processing information, experiencing emotions, and considering the short-term and long-term tradeoffs. However, few experimental investigations exist of momentary social cognitive factors that influence natural hazard likelihood and perceived response preparedness. Drawing on the Affect-as-Cognitive-Feedback approach, in which positive emotions (and anger) tend to validate thinking styles whereas negative emotions tend to invalidate them, the current work investigates how emotion and thinking styles interact to influence natural hazard judgments. In Study 1, participants completed a task to induce abstract or concrete thought and wrote about a happy or sad memory before making natural hazard likelihood and preparedness judgments. As expected, those under abstract thought and feeling happy judged natural hazards as more likely than those feeling sad. The opposite pattern emerged under concrete thought. Emotion and thinking styles also interacted to indirectly influence perceived preparedness via likelihood judgments. Study 2 participants under abstract or concrete thinking styles watched a happy, sad, or neutral video before completing the same judgments from Study 1 and rating their judgment confidence. High confidence individuals replicated the findings from Study 1, whereas low confidence individuals demonstrated the opposite pattern. In Study 3, a US national sample completed a global or local prime and wrote about an angry or sad memory before making the same judgments from Study 1. After controlling for age and prior natural hazard experience, emotion and thinking style interacted to influence perceived response preparedness.

Impact of Asymmetric Information in Islamic Financial contract: An Empirical Analysis

A primary source of asymmetric information arises from banks’ uncertainty about borrowers’Creditworthiness. This can generate two types of barriers to efficient credit allocation in the loan market: ad-verse selection in the likelihood of repayment and moral hazard in the riskiness of firms’ business decisions, also affecting repayment. This study investigated the consequences of asymmetric information on Islamic financial contracts in the Pakistani market for small and medium enterprise (SME) business lines of credit. Islamic bank’s main financial contracts were discuss the two of them which are Istisna and Murabah .The methods of’ T test’ was conducted to ascertain the difference in means of both forms of financing, whereas Multiple Regression Analysis using panel data to assess the relationship of critical variables with Disbursed amount, profit rate, spread, tenor. Data of three year i.e. from 2016 to2018 of 35 firms, with 105 number of observations having istisna and murabah contract, were taken. The results suggested that both the means of murabah and istisna financing are significantly different in major performance indicators, implicating companies that have taken these two financing have performed differently. Secondly, in most of the ratio that mattered like efficiency and profitability, murabah based financing have yielded more efficient results and better performed as compared to istisna.

Probabilistic hazard assessment of contaminated sediment in rivers

We propose a probabilistic framework rooted in multivariate and copula theory to assess heavy metal hazard associated with contaminated sediment in freshwater rivers that provide crucial ecosystem services such as municipal water source, eco-tourism, and agricultural irrigation. Exploiting the dependence structure between suspended sediment concentration (SSC) and different heavy metals, we estimate the hazard probability associated with each heavy metal at different SSC levels. We derive these relationships for warm (spring-summer) and cold (fall-winter) seasons, as well as stormflow condition, to unpack their nonlinear associations under different environmental conditions. To demonstrate its efficacy, we apply our proposed generic framework to Fountain Creek, CO, and show heavy metal concentration in warm season and under stormflow condition bears a higher hazard likelihood compared to the cold season. Under both warm season and stormflow conditions, probability of exceeding maximum allowable threshold for all studied heavy metals (Cu, Zn, and Pb, in recoverable form) at a standard hardness of 100 mg/lCaCo3 and at a high level of SSC (95th percentile) is consistently more than 80% in our study site. Moreover, a longitudinal study along the Fountain Creek demonstrates that urban and agricultural land use considerably increase likelihoods of violating water quality standards compared to natural land cover. The novelty of this study lies in introducing a probabilistic hazard assessment framework that enables robust risk assessment with important policy implications about the likelihood of different heavy metals violating water quality standards under various SSC levels.