Earthquake Risk Management Strategy Plan Using Nonparametric Estimation of Hazard Rate

Amiri, Aflaton; Tabatabaei, R.

doi:10.3844/ajassp.2008.581.585

Cited by 6 publications

(5 citation statements)

References 4 publications

(4 reference statements)

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“…Examples of seismic applications include the use of Bayesian statistics to generate extreme-value distributions of earthquake occurrences (Cambell, 1982;Stavrakakis and Drakopoulos, 1995) in California and Greece, respectively. Additionally, Oh et al (2008) apply Bayesian methods to develop early warning systems for earthquakes, and Amiri and Tabatabaei (2008) use a Bayesian approach in earthquake risk assessment studies. Gritzner et al (2001) employ a Bayesian probability model to help identify which variables are most important in watershedscale landslide risk assessments.…”

Section: Introductionmentioning

confidence: 99%

Predicting coastal cliff erosion using a Bayesian probabilistic model

2010

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a b s t r a c t a r t i c l e i n f oRegional coastal cliff retreat is difficult to model due to the episodic nature of failures and the along-shore variability of retreat events. There is a growing demand, however, for predictive models that can be used to forecast areas vulnerable to coastal erosion hazards. Increasingly, probabilistic models are being employed that require data sets of high temporal density to define the joint probability density function that relates forcing variables (e.g. wave conditions) and initial conditions (e.g. cliff geometry) to erosion events. In this study we use a multi-parameter Bayesian network to investigate correlations between key variables that control and influence variations in cliff retreat processes. The network uses Bayesian statistical methods to estimate event probabilities using existing observations. Within this framework, we forecast the spatial distribution of cliff retreat along two stretches of cliffed coast in Southern California. The input parameters are the height and slope of the cliff, a descriptor of material strength based on the dominant cliff-forming lithology, and the long-term cliff erosion rate that represents prior behavior. The model is forced using predicted wave impact hours. Results demonstrate that the Bayesian approach is well-suited to the forward modeling of coastal cliff retreat, with the correct outcomes forecast in 70-90% of the modeled transects. The model also performs well in identifying specific locations of high cliff erosion, thus providing a foundation for hazard mapping. This approach can be employed to predict cliff erosion at time-scales ranging from storm events to the impacts of sea-level rise at the century-scale.Published by Elsevier B.V.

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Section: Introductionmentioning

confidence: 99%

Predicting coastal cliff erosion using a Bayesian probabilistic model

2010

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“…The United Nations (UN) has designated the last decade of the 20 th century (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000) as the International Decade for Natural Disaster Risk Reduction, as proposed by the General Assembly. Recommendations of global and national documents, such as Iran's general policies to reduce the effects of natural disasters approved by the Expediency Discernment Council are based on the integration of development plans with disaster plans and reducing the effects of natural disasters (7). According to the UN Strategic Plan for Disaster Reduction, all hazards have two main sources, namely natural hazards and hazards caused by technology (hazards caused by human activity) (8 , 9).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Role of Dispersion of Rural Settlements against Natural Hazards in South Khorasan Province

2021

jorar

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INTRODUCTION: Identification of the settlements located in high-risk zones in terms of natural hazards is one of the first steps in risk management and development planning. This study aimed to identify villages exposed to earthquakes and floods in South Khorasan province. METHODS: The present study used the Analytic Hierarchy Process method to evaluate the validity and reliability of measuring instruments through exploratory factor analysis. Since the value of the KMO index was 0.879, the number of samples was sufficient for analysis. Moreover, the significance of the Bartlett test was less than 5% and Cronbach's alpha coefficient was obtained at 0.856; accordingly, the questionnaire was reliable. FINDINGS: Based on the spatial analysis of the seismic vulnerability, 214 and 502 villages were in the zone of very high and high vulnerability, respectively. Moreover, the results of flood vulnerability showed that the southern and northwestern parts of South Khorasan province had the lowest vulnerability. The number of villages located in the very high vulnerable zone was very limited and included only seven villages of Chenesht, Kalateh Abbas, Takti Ti, Tangel Behdan, Ebru, Khankuk, and Ostan Siah, which are located in the east of the province. CONCLUSION: Based on the integrated results of two hazards (i.e., earthquakes and floods), it is observed that 523 rural settlements are in a very high-risk zone, which accounts for 14.7% of the total settlements in the South Khorasan province, compared to the total rural settlements. Furthermore, the highest dispersion frequency of rural settlements is in the zone of moderate vulnerability. This zone with 1,344 settlements includes about 37.7% of the total settlements in the province

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“…Such a disaster happened not only because of the large magnitude of earthquake but also as a result of non-standard structures and weak buildings. However, re-construction cost more than 10 billion dollars [3]. According to our experience from past earthquakes, disordered structures show higher potential for destruction in comparison with other ones.…”

Section: Introductionmentioning

confidence: 99%

Study of Short Column Behavior Originated from the Level Difference on Sloping Lots during Earthquake (Special Case: Reinforced Concrete Buildings)

Ramin¹,

Mehrabpour²

2014

OJCE

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The disorders originated from architectural design in buildings, show in different forms. One of them is the level difference originated from lot's slope which affects structures through short column phenomenon. The great stiffness of short columns enables them to absorb large amounts of structural energy. Inattention of some manuals and regulations such as Earthquake regulations to this phenomenon necessitates paying further attention to it. On this basis, the present study employed experimental modeling and numerical modeling for a four-story reinforced concrete building that involves the analysis of simple 2-D frames of varying floor heights and varying number of bays using a very popular software tool STAAD Pro on both a sloping and a flat lot. Also Sap2000 software had been used to show that the displacement of floors is greater for a flat lot building than a sloping lot building. However, the increase in shear was found to be quite greater in short columns compared to common ones and an enormous moment should be tolerated by sloping lot structures. The greater stiffness of the structure was also revealed by non-linear static (Push-Over) analysis. According to the results, short column are required to have more resistant sections and are suggested to be reinforced with more bars. In addition, more steel should be used as stirrups than as longitudinal bars. Also for existing structures, shear capacity of short columns should be retrofitted by FRP, Steel Jacket or other materials.

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Earthquake Risk Management Strategy Plan Using Nonparametric Estimation of Hazard Rate

Cited by 6 publications

References 4 publications

Predicting coastal cliff erosion using a Bayesian probabilistic model

Predicting coastal cliff erosion using a Bayesian probabilistic model

Analysis of the Role of Dispersion of Rural Settlements against Natural Hazards in South Khorasan Province

Study of Short Column Behavior Originated from the Level Difference on Sloping Lots during Earthquake (Special Case: Reinforced Concrete Buildings)

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