سنجش تاب آوری شهری در برابر مخاطره سیل با استفاده از شاخص های ترکیبی (مورد مطالعه: شهر خرم آباد) مقالة

خلاصة:

Highlights: Flooding is one of the most common, widespread, and devastating natural disasters. Strengthening capacities to better prepare for, cope with, and recover from adverse effects is crucial for addressing increasing risks from natural events. This article establishes a framework for building resilience in Khorramabad city. Introduction: Global climate changes, primarily manifested as global warming and rapid urbanization, exacerbate extreme weather events. Statistics indicate that floods are among the most prevalent and catastrophic natural disasters (Safiah Yusmah et al., 2020: 552). Urban floods caused by heavy rainfall have evolved from gradual accumulation to sudden surges (Masozera et al., 2007: 299; Hallegatte et al., 2013: 802). Therefore, urban flood resilience, crucial for flood control and disaster reduction, has garnered increasing research focus (Obrist et al., 2010: 284; Xu et al., 2018: 5298). The Sendai Framework for Disaster Risk Reduction (2015-2030), endorsed by the World Conference on Disaster Risk Reduction in 2015, and the 2018 Beijing Resilient City Development Plan, underscore the importance of enhancing urban resilience to disasters (Sun et al., 2022: 1). To address the growing risk of natural events, it is essential to strengthen capacities that enable vulnerable communities to better prepare for, cope with, and recover from adverse effects. In disaster management literature, this strategy is commonly referred to as resilience. Resilience, when applied to communities, is defined as "the ability of a community to prepare for, plan, absorb, recover, and adapt to actual or potential adverse events in a timely and efficient manner, including rebuilding and improving essential functions and structures." A resilient community incurs fewer losses and recovers more swiftly from hazardous events (Cutter et al., 2014: 65; Abdali et al., 2022: 6). Theoretical Framework: The concept of resilience originated from Holling's seminal work in ecology, aimed at understanding the instability and dynamics of nature. According to Holling, resilience is "the measure of a system's ability to absorb change and disturbance while maintaining the same relationships between populations or state variables." However, resilience is not simply "the ability of a system to return to equilibrium after a temporary disturbance" (Holling, 1973: 14-17). In ecological literature, two definitions of resilience emerged: one that encompasses continuity, change, and unpredictability in a nonlinear and non-equilibrium system (ecological resilience), and another that focuses on efficiency, stability, and predictability in a single equilibrium system (engineering resilience) (Holling, 1996: 25; Folke, 2006: 256). Engineering resilience emphasizes rapid and efficient recovery post-disturbance, while ecological resilience is about absorbing changes and ensuring continuity (Pickett et al., 2004: 373). Methodology: This study employs a combined multi-criteria decision-making approach using the Analytic Network Process (ANP), DEMATEL technique, and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). The DEMATEL-ANP model identifies internal relationships between indicators, allowing for pairwise comparisons and weight evaluation, while PROMETHEE ranks solutions based on their proximity to the ideal solution, with the best solution being closest to the ideal point (Chen et al., 2011: 909; Chiu et al., 2013: 49; Thor et al., 2013: 27; Ju et al., 2015: 348-349). Results and Discussion: Resilience in Khorramabad exhibits a clear spatial pattern, with higher resilience in affluent upper city areas and lower resilience in less affluent lower city areas. This disparity highlights the inequitable distribution of urban facilities and services, emphasizing the need for equitable development and access to vital resources. Economic resilience is surprisingly lower in the city’s economic center due to deteriorated infrastructure and the residence of lower socio-economic strata. Institutional resilience is higher in central areas, benefiting from the concentration of governmental, private, and grassroots organizations. Peripheral areas suffer from inadequate infrastructure, resulting in lower overall resilience. Social capital resilience lacks a specific spatial pattern, with most areas rated as medium to low, indicating weak community connections. Environmental resilience shows that city center areas are more prone to flooding, while higher resilience is observed in different parts of the city, possibly due to land permeability and river positions. Comparative analysis reveals that regions 1, 4, 7, 13, and 17 have the lowest resilience, while regions 23 and 14 rank high. This analysis provides a comprehensive understanding of resilience levels at the city scale, identifying areas requiring further intervention. Conclusion: Mapping the results reveals distinct spatial patterns of resilience and identifies hotspots needing more intervention. Central and western regions, with lower resilience, require more attention. Environmental and infrastructural factors are key, directly relating to land use and planning. The findings can assist Khorramabad’s urban planning organizations in integrating disaster resilience into urban planning, transforming reactive plans into proactive adaptation strategies. Additionally, identifying potential hotspots can aid emergency management institutions in effective disaster risk management. Enhancing social resilience is crucial for community capacity building to prepare for, respond to, and adapt to climate change impacts, guiding local stakeholders in fostering fair development and equitable resource access.