ارزیابی تاب‌آوری شهری در برابر خطر سیل با استفاده از روش IHWP با تأکید بر قطعات ساختمانی؛ مطالعه موردی: محله کن شهر تهران

ABSTRACT
In recent decades, flood management in large cities has become one of the most difficult aspects of urban governance. Uncoordinated physical development, land impermeability, destruction of river and valley paths, and inefficiency of drainage systems have increased the vulnerability of Tehran city to heavy rainfall. The main goal of this study is to investigate the resilience of the Kan neighborhood of Tehran against flood risk and present an efficient model. Therefore, in this study, first, using library resources and interviews with the expert community, indicators affecting urban resilience against floods were extracted. Then, using the IHWP method, the weight of each indicator was obtained. 18 layers were selected to assess the resilience of this area against floods, and then using the ARC GIS database, resilience against floods was calculated with an emphasis on the building parcel. The results show that 17.07 percent of the neighborhood is in the very low resilience range, which is in the eastern part of the neighborhood and around the Kan River. 32.52 percent of the neighborhood is in the low resilience range, which includes large parts of the northwest and southwest of the neighborhood. 26.02 percent of the neighborhood is in the medium resilience range, concentrated in the east and southeast parts of the neighborhood. 12.99 percent of the neighborhood is in the high resilience range, which includes the northeast parts of the neighborhood. 10.81 percent of the neighborhood is in the very high resilience range, which includes the northeast of the neighborhood.
Extended Abstract
Introduction
Urban flooding is a complex and recurring phenomenon that poses a significant challenge to cities worldwide, especially those experiencing rapid urbanization. For instance, some causes of flooding in cities such as Tehran include rapid population growth, uncontrolled land transformation, increased impervious surface area, occupation of waterways, and insufficient stormwater drainage infrastructure. In essence, flooding in cities such as Tehran has shifted from a hydrological phenomenon to a complex, multidimensional one that triggers cascading effects.
The geomorphological characteristics of Tehran City, together with its high level of urbanization and extensive river-valley systems, make some of its neighbourhoods highly vulnerable to flash flooding. To be more specific, areas along river valleys are more affected by direct exposure to flooding and sediment transport. Under such conditions, the effectiveness of traditional approaches to flood management, which are primarily based on structural measures and disaster response, has proven limited. As such, the concept of urban resilience has been proposed as a holistic approach to addressing this issue by focusing on the system’s ability to absorb changes, adapt to new conditions, and restore its basic functions within a given time frame.
Urban flood resilience transcends hazard mitigation and involves various physical, social, economic, and institutional aspects. Despite the growing research on flood resilience assessment, existing studies have mostly examined urban- or district-scale flood resilience, failing to consider micro-scale characteristics at the parcel or building level. This is a significant limitation, particularly since flood damage and recovery are local processes influenced by parcel-level characteristics, such as building quality, building materials, building elevation, proximity to flood sources, and surrounding land cover.
With the aforementioned gap in mind, the current research aims to assess the concept of flood resilience at the building parcel scale. To achieve this objective, the Kan Neighbourhood in Tehran has been chosen as a study area. The Kan Neighbourhood lies in the north-western part of Tehran and is bordered by the Kan River. The Kan River has historically been a flood-prone drainage area. The overall objective of the current research is to apply the Inverse Hierarchical Weighting Process (IHWP) to assess the concept of flood resilience using a multi-criteria decision-making approach coupled with Geographic Information Systems (GIS).
 
Methodology
This research is considered applied research, as it is descriptive and analytical in nature. The research methodology is descriptive-analytical, combining both qualitative expert judgment and quantitative spatial analysis. The methodological framework is divided into three main stages:
(1) Identifying and classifying flood resilience indicators;
 (2) Weighting the indicators through the application of the IHWP method, which is based on expert consensus;
 (3) Spatial implementation and mapping of resilience at the parcel level through geographic information systems.
The original set of indicators was established through an exhaustive review of the scientific literature related to urban resilience, flood risk, and disaster management. Expert opinions from subject matter specialists supplemented this review. The pool of experts comprised specialists in urban planning, civil engineering, disaster management, and environmental science. Consequently, 84 indicators related to flood resilience were identified and grouped into five major dimensions:

Physical–spatial,
Social–cultural,
Safety and security,
Economic,
Institutional–organizational.

The exhaustive set of indicators captures the multidimensional nature of resilience and can be refined based on the level of applicability and the availability of information. To improve the set of indicators and reach consensus on their importance, the Delphi method was used. Experts assessed the relevance and significance of each indicator on flood resilience through various rounds of feedback. Indicators were scored and deliberated upon until a stable level of agreement was reached. This phase resulted in a validated set of indicators with relative importance scores assigned by experts, which were used to weigh the indicators in the subsequent process. The Inverse Hierarchical Weighting Process (IHWP) was used to determine the relative weights of the indicators. The IHWP technique is particularly useful in decision-making situations where mixed qualitative and quantitative data integration is required and where uncertainty exists in expert judgments. The technique also differs from other traditional hierarchical weighting methods in that it emphasizes the use of inverse ranking logic to ensure that more important indicators play a greater role in the final assessment. The expert judgments obtained through the Delphi technique were used in IHWP calculations to produce normalized weights for each indicator. The weights were then used in the spatial analysis process. The technique's flexibility makes it particularly useful for assessing resilience at finer scales. Following the weighting phase, spatial data layers for the selected indicators were developed and standardized in a geographic information system (GIS) environment. Based on the availability of the data and their relevance to parcel-scale analysis, a total of 18 spatial layers were selected for use in the model, covering slope, aspect, elevation, geology, river and channel buffers, green spaces, population distribution, age of buildings, quality of constructions, building materials, and urban texture. Using ArcGIS software and related tools (e.g., Raster Calculator), a composite flood resilience score for each parcel was calculated as a weighted sum of selected indicators. The final output is a flood resilience zoning map that distinguishes five classes of flood resilience as very low, low, moderate, high, and very high. To test the consistency and reliability of IHWP-derived weights, a comparative analysis was conducted using the Analytic Hierarchy Process (AHP) approach. The indicator weights were recalculated using the same hierarchy, and the results were compared using correlation analysis. The results showed a high degree of consistency between the two methods, which proved the reliability and credibility of IHWP.
 
Results and discussion
The results of the weighting analysis suggest that the physical-spatial dimension has the most impact on flood resilience, followed by the social-cultural dimension. The safety-security and economic dimensions are the next two dimensions, while the institutional-organizational dimension has the least impact. This reflects the direct and immediate impact of the physical characteristics of the landscape on the impact of floods at the parcel scale. Among the specific indicators, proximity to rivers and channels has the greatest impact, followed by vegetation cover, site location, and building structural quality. Overall, the results suggest the importance of both exposure and resistance indicators. The topography of the Kan Neighbourhood is complex, with steep slopes and proximity to the Kan River. Past floods and observations in the Neighbourhood are clear manifestations of the risks associated with flash flooding, particularly during intense precipitation. Additionally, the Neighbourhood has old, vulnerable buildings that pose a threat in the event of a flood. The analysis from the GIS results shows that there is considerable spatial heterogeneity in flood resilience in the Kan Neighbourhood. The proportion of each class of flood resilience is as follows:
- Very low resilience: 17.07% (along the river corridor);
- Low resilience: 32.52% (northwest and southwest areas)
- Moderate resilience: 26.02%;
- High resilience: 12.99%;
- Very high resilience: 10.81% (north-eastern areas).
The results indicate that nearly half of the population in the Kan Neighbourhood is in the low or very low flood resilience class. The identified spatial patterns can be explained by the combined effects of three major factors. First, the spatial distribution of parcels relative to the river and flood channels significantly affects resilience, as parcels closer to the Kan River are more prone to overflow and debris flow. Second, the natural environment's conditions, such as slope and soil permeability, affect the dynamics of flood intensity. Third, the characteristics of the built environment, such as the age and materials of buildings, affect their ability to withstand flood intensity and to recover from it. The high significance of the physical dimension in the results should not be considered to exclude the role of social, economic, and institutional factors; rather, it indicates the level of analysis. In parcel-level analysis, the role of physical attributes is easier to capture and has a more significant short-term impact. This indicates opportunities for short-term improvements in flood resilience through interventions in the physical environment.
 
Conclusion
The current study aims to present and implement an integrated approach to assess urban flood resilience at the building-parcel scale, combining expert-based weighting techniques with GIS spatial analysis. The results show that flood resilience in the Kan Neighbourhood is unevenly distributed, and many building parcels exhibit low resilience.
The key factors are proximity to rivers, vegetation cover, parcel location, and the quality of structures. The physical-spatial element was found to be the major influencing factor, which highlights the importance of spatial design.
Based on these results, the following recommendations have been made:
- Enforce stringent land use and development controls in river buffer zones;
- Upgrade and improve green infrastructure to reduce surface runoff;
- Upgrade stormwater management facilities in high-risk zones;
- Retrofit and structurally reinforce vulnerable building clusters;
- Regulate incompatible land uses in flood-prone zones.
The key contribution of this research lies in its parcel-scale analysis and application of the IHWP method to derive transparent and accurate indicator weights. The spatial results provide valuable insights for urban planners and decision-makers, enabling the precise prioritization of flood-resilience strategies. The framework appears flexible and applicable to other flood-prone areas of Tehran and similar urban settings, helping inform evidence-based approaches to disaster risk reduction and resilient urban development strategies.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.