Resilience of key buildings in Hamedan against floods using LISREL structural equation modeling

Document Type : Applied Article

Authors

1 PhD Student in Environmental Management, Marine Science and Technology, Islamic Azad University, North Tehran Branch

2 Assistant Professor of Environmental Management, Marine Science and Technology, Islamic Azad University, North Tehran Branch

3 Professor of Geography, Humanities, Islamic Azad University, Imam Khomeini Memorial Branch, City of Ray

4 Assistant Professor of Architectural Engineering - Urban Planning, Islamic Azad University, North Tehran Branch

Abstract

Introduction
Urban floods have been exacerbated by climate change and urbanization, as well as restrictions on the drainage of urban infrastructure, and over the past decade have had many negative effects on cities around the world [4]. As a result, the demand for more resilience has not been successful in many cases [2]. Accordingly, the resilience of key urban buildings is one of the necessities of urban resilience [3]. In this regard, research on urban resilience in events such as floods was reviewed, some of the most important of which are mentioned below. In 2019, Wang and colleagues evaluated the resilience of the urban basin to floods, and the CADDIES model was used to simulate floods. Based on the results, vulnerable basins were identified and strategies were developed to increase the city's resilience to floods [4]. In 2019, Barajas et al. worked on an article on the resilience of urban buildings in the face of flood risk in the Mexican metropolitan area, and addressed the resilience of buildings in Mexico City during the floods of recent decades. Findings show that building resilience is a complex and sequential process that of course depends on social, economic and institutional conditions [1].
Research Methods
In this research, in order to achieve the model of resilience of important buildings against floods, data analysis is performed in several stages, which include the following:
1- Identification of significant assets
2- Modeling river flow using HecRAS software
3- Adaptation of assets and modeling results from rivers in different return periods
4- Counting assets affected by floods
5- Modeling of building resilience components using structural equation modeling of LISREL software
6-Counting and ranking the components extracted from the model using AHP-TOPSIS combined method
7- Ranking of key buildings affected by floods using AHP-TOPSIS combined method
Discussion and conclusion
The asset layers of the city of Hamedan and the rivers of the city have been adapted in the GIS context and five buildings of the University of Technology, the Faculty of Art and Architecture, Payam-e Noor University, the Blood Transfusion Building and the Amiran Hotel have been identified as vulnerable centers of Hamedan.
Conclusion
Components (adaptability-flexibility, connection of failure-safe feedback, dependence on environmental ecosystems, diversity, learning-memory-prediction, performance, response speed, fragmentation redundancy, resourcefulness, and robustness) are effective variables on flood resilience of buildings. In testing the hypothesis using the structural equation model, the software output indicates the suitability of the fitted structural model to test the research hypotheses.
Weighting indicators




Resilience components


Sub-components of resilience


Weight




Compatibility - Flexibility


Change while maintaining or improving performance


0.049




Evolution


0.045




Adopt alternative strategies quickly


0.05




Timely response to changing circumstances


0.027




Open design and flexible structures


0.049




Connection - Feedback - Safety - Failure


Shock absorption


0.007




Absorb the cumulative effects of challenges with a slow start


0.012




Avoid catastrophic failure if you exceed the threshold


0.007




Gradual failure instead of sudden


0.013




Failure without cascading effects (demino effect)


0.024




Parallel analysis of technology system - human


0.005




Identify locking effects and possible discrepancies with reduction


0.014




Identify synergies with other city policies, value added estimation


0.015




Dependence on local ecosystems


Flood control


0.012




Bioclimatic design and management


0.006




 




Resilience components


Sub-components of resilience


Weight




Variety


Spatial diversity - key assets and tasks that are physically distributed and not all of them are affected by a specific event at any time


0.0146




Functional Diversity - Multiple methods of dealing with a particular need


0.021




Balance variation with potential cascading effects


0.013




Learning-Memory - Prediction


Learn from past experiences and failures


0.003




Use information and experience to create fresh compatibility


0.003




Avoid repeating past mistakes


0.005




Collect, store, and share experiences


0.009




Construction based on long-term value and city history


0.007




Integrate resilience into long-term development scenarios


0.02




Function


Performance capacity


0.056




System quality in a suitable and efficient way


0.013




Self-sufficiency - reducing external dependence


0.019




It performs better than other buildings


0.039




Response speed


In taking casualties, including mortality and disease


0.007




Reorganize


0.015




Maintain performance and re-establish it


0.032




Restore structure


0.017




Establish public order


0.013




Prevent disruption in the future


0.005




Redundancy - fragmentation


Systems replacement or systems agents


0.054




Buffer from external shocks or changes in demand


0.013




Replacing components with modular parts


0.026




Balance redundancy with potential cascading effects


0.077




plan


Identify and predict problems


0.013




Prioritize


0.011




Mobilize resources of visualization, planning, collaboration and action


0.014




re-evaluation


0.006




Integrate resilience into work and management processes


0.052




Getting cooperation from citizens


0.03




Strength


Surface resistance to stress


0.003




No degradation and loss of performance


0.015




Capacities that ensure adequate margins


0.006

Keywords


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