Dam overtopping risk using probabilistic concepts – Case study: The Meijaran Dam, Iran

Goodarzi, Ehsan; Shui, Lee Teang; Ziaei, Mina

doi:10.1016/j.asej.2012.09.001

Cited by 14 publications

(4 citation statements)

References 9 publications

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“…To consider uncertainty analysis in seismic damage assessment, the Monte Carlo simulation is used in this study. Monte Carlo simulation, which is based on the iteration and generation of random variables from a specific range, is one of the most widely used numerical methods (Goodarzi et al 2013). This method is mainly applicable to complex problems with a large number of random values when analytical methods are not applicable (Akkar and Cheng 2016).…”

Section: Uncertainty Analysismentioning

confidence: 99%

Sensitivity analysis in seismic loss estimation of urban infrastructures

Eskandari

Omidvar

Modiri

et al. 2018

Geomatics, Natural Hazards and Risk

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Iran, as a seismic country, is situated over the Himalayan-Alpied seismic belt and has faced many destructive earthquakes throughout history. Therefore, it is very important to evaluate the possible damage to the existing infrastructure based on statistical and spatial analysis. In this study, a new model is developed to analyse seismic damages based on seismic hazard assessment and extraction of the vulnerability function for all features of fuel infrastructure. To consider uncertainty analysis in the model, Monte Carlo simulation is used based on 10,000 iterations. The results of hazard analysis indicated that peak ground acceleration is about 0.18 g and there is slight to moderate damages to the desired fuel infrastructure in the study area. Moreover, sensitivity analysis is also performed to determine how median, standard deviation (or beta), grid size, attenuation relationships, liquefaction and landslide susceptibility impact the seismic loss. Last but not least, the effect of input parameters of earthquake scenarios including magnitude, focal depth and focal distance are also analysed in conjunction with regression analysis. The results of the study show that magnitude and focal distance are the most sensitive parameters in which the expected damage to the fuel infrastructure is reduced by about 25% if the epicentre of the earthquake is moved from 10 to 25 km.

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Section: Uncertainty Analysismentioning

confidence: 99%

Sensitivity analysis in seismic loss estimation of urban infrastructures

Eskandari

Omidvar

Modiri

et al. 2018

Geomatics, Natural Hazards and Risk

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“…The PMF is the maximum amount of flooding a logically possible set of meteorological and hydrologic circumstances might possibly expect. In other words, PMF assumes the dependability of zero failure while taking into account the maximum range of flood potential [ 5 ]. PMF is usually estimated by using Probable Maximum Precipitation, which also known as PMP using as an input in hydrologic modeling software.…”

Section: Introductionmentioning

confidence: 99%

“…In order to prevent overtop at the dam crest, a study is conducted for the hydrological evaluation to determine if the dam has the spillway capacity to safely manage the PMF. This typical method for calculating the hydrological risk of dam overtopping is based on a univariate analysis that only takes into account flood peak discharges from the most PMF [ 5 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Hydrological Analysis of Batu Dam, Malaysia in the Urban Area: Flood and Failure Analysis Preparing for Climate Change

Omar

Ariffin

Sidek

et al. 2022

IJERPH

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Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.

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“…Monte Carlo methods are especially useful in modeling systems with many random variables with known probability distributions. Monte Carlo simulation, which is based on the iteration and generation of random variables from a specific range, is one of the most widely-used numerical methods [44]. …”

mentioning

confidence: 99%

Geospatial Analysis of Earthquake Damage Probability of Water Pipelines Due to Multi-Hazard Failure

Eskandari

Omidvar

Modiri

et al. 2017

IJGI

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Abstract:The main purpose of this study is to develop a Geospatial Information System (GIS) model with the ability to assess the seismic damage to pipelines for two well-known hazards, including ground shaking and ground failure simultaneously. The model that is developed and used in this study includes four main parts of database implementation, seismic hazard analysis, vulnerability assessment and seismic damage assessment to determine the pipeline's damage probability. This model was implemented for main water distribution pipelines of Iran and tested for two different earthquake scenarios. The final damage probability of pipelines was estimated to be about 74% for water distribution pipelines of Mashhad including 40% and 34% for leak and break, respectively. In the next step, the impact of each earthquake input parameter on this model was extracted, and each of the three parameters had a huge impact on changing the results of pipelines' damage probability. Finally, the dependency of the model in liquefaction susceptibility, landslide susceptibility, vulnerability functions and segment length was checked out and specified that the model is sensitive just to liquefaction susceptibility and vulnerability functions.

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Dam overtopping risk using probabilistic concepts – Case study: The Meijaran Dam, Iran

Cited by 14 publications

References 9 publications

Sensitivity analysis in seismic loss estimation of urban infrastructures

Sensitivity analysis in seismic loss estimation of urban infrastructures

Hydrological Analysis of Batu Dam, Malaysia in the Urban Area: Flood and Failure Analysis Preparing for Climate Change

Geospatial Analysis of Earthquake Damage Probability of Water Pipelines Due to Multi-Hazard Failure

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