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jorar 2026, 18(3): 140-151 |
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Mousavi Dehmordi S M, Arbabi Sabzevari A, Amir Azodi T, Adibi Saadinejad F. Structural Analysis of Flood Consequences and Prioritization of Flood Risk Management Strategies in Ahvaz City. jorar 2026; 18 (3) :140-151
URL: http://jorar.ir/article-1-971-en.html
URL: http://jorar.ir/article-1-971-en.html
Seyed Mehdi Mousavi Dehmordi 
, Azadeh Arbabi Sabzevari * 
, Tuba Amir Azodi , Fatemeh Adibi Saadinejad
, Azadeh Arbabi Sabzevari * , Tuba Amir Azodi , Fatemeh Adibi Saadinejad
Department of Geography and Urban Planning, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran
Abstract: (273 Views)
INTRODUCTION: Urban flooding is a major hazard for cities, and its consequences in Ahvaz involve interacting environmental, physical, infrastructural, social, and managerial conditions. This study aimed to analyze the structural interrelationships among flood consequence and damage-related variables in Ahvaz city and to identify and prioritize flood risk management strategies using structural analysis and expert assessment.
METHODS: This applied study used a sequential exploratory mixed-methods design. Data were obtained through documentary review, semi-structured interviews, and expert assessments from a purposively selected panel of 50 experts. Twenty-eight consequence variables were analyzed using a 28 × 28 cross-impact matrix and MICMAC software. Subsequently, 26 structural and non-structural flood risk management strategies were evaluated through a three-round Delphi process using a five-point Likert scale.
FINDINGS: Of the 784 cells in the cross-impact matrix, 752 were non-zero, yielding a filling rate of 95.92%. The mean influence score was highest for the economic–physical group (36.1), followed by the environmental (35.2) and social groups (33.3). Social variables showed the highest mean dependence (46.7), indicating a greater degree of dependence on other variables within the system. The variables with the greatest direct influence were destruction of the urban sewage system (44), damage to urban housing and clinics and health centers (42 each), and damage to transportation vehicles and drinking-water pollution (41 each). In the second Delphi round, the highest mean importance scores were assigned to cleaning and dredging the Karun River channel (4.94), improving the wastewater and stormwater collection network (4.91), and removing meanders from the Karun River (4.87). In contrast, constructing buildings on elevated, flood-safe sites with restrictions on development in flood-prone areas and preparedness for pre-flood evacuation received the lowest mean scores (3.00 each). In the third round, the assessments showed relative stability, with only limited changes in mean scores.
CONCLUSION: Flood consequences in Ahvaz city are highly interconnected, with wastewater infrastructure, housing, and health facilities among the variables exerting the greatest influence on other consequences. Expert assessments assigned higher importance to river-channel management and drainage infrastructure, whereas land-use control and pre-flood evacuation preparedness received lower importance scores.
METHODS: This applied study used a sequential exploratory mixed-methods design. Data were obtained through documentary review, semi-structured interviews, and expert assessments from a purposively selected panel of 50 experts. Twenty-eight consequence variables were analyzed using a 28 × 28 cross-impact matrix and MICMAC software. Subsequently, 26 structural and non-structural flood risk management strategies were evaluated through a three-round Delphi process using a five-point Likert scale.
FINDINGS: Of the 784 cells in the cross-impact matrix, 752 were non-zero, yielding a filling rate of 95.92%. The mean influence score was highest for the economic–physical group (36.1), followed by the environmental (35.2) and social groups (33.3). Social variables showed the highest mean dependence (46.7), indicating a greater degree of dependence on other variables within the system. The variables with the greatest direct influence were destruction of the urban sewage system (44), damage to urban housing and clinics and health centers (42 each), and damage to transportation vehicles and drinking-water pollution (41 each). In the second Delphi round, the highest mean importance scores were assigned to cleaning and dredging the Karun River channel (4.94), improving the wastewater and stormwater collection network (4.91), and removing meanders from the Karun River (4.87). In contrast, constructing buildings on elevated, flood-safe sites with restrictions on development in flood-prone areas and preparedness for pre-flood evacuation received the lowest mean scores (3.00 each). In the third round, the assessments showed relative stability, with only limited changes in mean scores.
CONCLUSION: Flood consequences in Ahvaz city are highly interconnected, with wastewater infrastructure, housing, and health facilities among the variables exerting the greatest influence on other consequences. Expert assessments assigned higher importance to river-channel management and drainage infrastructure, whereas land-use control and pre-flood evacuation preparedness received lower importance scores.
Keywords: Urban flooding, Flood consequences, Structural analysis, MICMAC, Delphi, Risk management, Ahvaz.
Article Type: Research article |
Subject:
Environmental disasters
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