Case Study for Quantifying Flood Resilience of Interdependent Building–Roadway Infrastructure Systems

Sen, M. K.; Dutta, Subhrajit; Gandomi, Amir H.; Putcha, Chandrasekhar

doi:10.1061/ajrua6.0001117

Cited by 9 publications

(3 citation statements)

References 71 publications

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“…The concept of resilience is used in various domains, but the specific concept of engineering resilience is relatively new Mohammed et al 2020). Resilience is quantified across various infrastructure systems, such as housing (Sen et al 2021a), transportation (Sen and Dutta 2020;Sen et al 2021b), electricity (Panteli et al 2017), water supply (Yung et al 2011;, and telecommunication (Omer et al 2009). Sen and Dutta (2020) quantified system resilience against flood hazards by constructing a roadway model based on a real roadway network.…”

Section: Figure 1 Performance Of Infrastructure During Its Life Spanmentioning

confidence: 99%

“…The authors used a global information system to collect information on each node and used a Bayesian belief network to quantify the posterior probability of system resilience following the failure of a critical node. Sen et al (2021b) modified the model by incorporating housing infrastructure nodes into the existing network and considering the nodes' dependencies. Sharma and Chen (2020) developed a resilience-quantification framework for rural electrical systems against hurricane events using two reduced-order analysis methods.…”

Section: Figure 1 Performance Of Infrastructure During Its Life Spanmentioning

confidence: 99%

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Fuzzy analytic hierarchy process framework for quantifying the flood resilience of housing infrastructure systems

et al. 2022

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Housing constitutes a basic need for all living beings. Unfortunately, natural hazards, including floods, pose a severe threat to housing infrastructure systems. In turn, this paper develops a framework to quantify the resilience of housing infrastructure systems against flood hazards. The parameters for this resilience are based on the literature and knowledge from experts. This paper gauges the significance of each resilience parameter is evaluated using the analytic hierarchy process (AHP) and the fuzzy AHP. The evaluated values are then compared to observe the effectiveness of fuzzy AHP over AHP. The evaluated importance of each parameter will help stakeholders focus on the most important parameters and, in turn, boost the flood resilience of infrastructure. This paper then implements the developed framework in a study area to quantify local flood resilience. This resilience value will help stakeholders in the considered area to understand the resilience of local housing infrastructure.

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Section: Figure 1 Performance Of Infrastructure During Its Life Spanmentioning

confidence: 99%

Section: Figure 1 Performance Of Infrastructure During Its Life Spanmentioning

confidence: 99%

Fuzzy analytic hierarchy process framework for quantifying the flood resilience of housing infrastructure systems

et al. 2022

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“…Based on a digital map made on the Arc View 3.2 and ArcGIS 10 platforms, the most dangerous areas of mudflow manifestations were identified, and settlements located in the area of high mudflow activity were identified [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Assessment of damage during the formation and passage of mudflows in the Tashkent region

Shaazizov

2021

E3S Web Conf.

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Mountainous and largely foothill areas of the Republic of Uzbekistan are mudflow hazardous. In the Tashkent region, there are two mudflow river basins (dangerous concerning the manifestation of mudflows): the Chirchik river basin and the Akhangaran river basin. Based on the results of long-term observations of the Uzhydromet service, a digital map of the mudflow hazard in the Tashkent region for a century was compiled. The method for determining the damage from the action of mudflows on a specific object consists of determining the equivalent mudflow pressure according to its initial parameters. According to the methodology for assessing damage in the event of a natural emergency, the main parameters of the damaging factors were determined during the passage of a mudflow in the event of intense rainfall. The calculations were performed for two scenarios: 1) with dangerous rainfall with an intensity of 30 mm per day; 2) in case of especially dangerous rainfall with an intensity of 60 mm per day. Based on the calculations performed, the amount of damage to the national economy of the Tashkent region was determined during the passage of a mudflow caused by intense rainfall.

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Artificial Intelligence Algorithms in Flood Prediction: A General Overview

Pandey

2024

Geo-Information for Disaster Monitoring and Management

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Case Study for Quantifying Flood Resilience of Interdependent Building–Roadway Infrastructure Systems

Cited by 9 publications

References 71 publications

Fuzzy analytic hierarchy process framework for quantifying the flood resilience of housing infrastructure systems

Fuzzy analytic hierarchy process framework for quantifying the flood resilience of housing infrastructure systems

Assessment of damage during the formation and passage of mudflows in the Tashkent region

Artificial Intelligence Algorithms in Flood Prediction: A General Overview

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