Introduction
One of the important steps in the framework of watershed conservation programs and sustainable management of natural resources is the identification of vulnerable areas. This step serves as a solid foundation for the measures needed for environmental management. Vulnerability assessment provides necessary standards for implementation priorities and helps identify and prioritize sensitive and vulnerable areas for sustainable management of natural resources. Among natural hazards at the watershed level, floods are one of the most frequent and destructive types of hazards that cause many human and financial losses. Due to being situated in a vast ecosystem of arid and semi-arid regions, Iran is frequently exposed to the destructive effects of floods. The country's vulnerability to these events is exacerbated by climate change and unsustainable human activities. It is predicted that due to climate changes, rapid unplanned urbanization, expansion of impervious surfaces, changes in land-use patterns, and poor management of watersheds, floods will occur more intensely in the future. Therefore, the study and identification of vulnerable areas, as one of the important variables in flood risk management, is a key part of non-structural measures to prevent and reduce the destructive effects of floods. This research seeks to analyze the spatial vulnerability of the Zarrinehrood Watershed to flood events. By considering vulnerability functions, including exposure, susceptibility, and resilience, the degree of vulnerability of this watershed to flood was investigated, and vulnerable areas were identified.
Materials and Methods
The focus of this research is the Zarrinehrood watershed, located in the provinces of West Azarbaijan and Kurdistan, Iran. To identify flood-prone areas in this region, we first collected relevant data and information on factors contributing to flood vulnerability in the study area. Then, the grid layers of factors were prepared in three sectors including exposure (i.e., factors such as average annual rainfall, frequency of heavy rainfall, maximum daily rainfall, distance from waterways, and frequency of floods), susceptibility (i.e., factors like the percentage of farmer and rancher households, distance from industrial areas and mines, distance from roads, land use, population density, and distance from residential areas), and resilience (i.e., factors such as the number of rural cooperative companies, the number of health and treatment centers, and the number of transportation routes). Next, the importance of the variables was evaluated using the method of Analytic Network Process (ANP), taking into account the internal connections between the variables. The pixel value of the data was then determined by analyzing the relationship of each factor with flood vulnerability and employing fuzzy value functions. Finally, the vulnerability map was prepared and analyzed for the study area by applying the variable weights to the normalized layers.
Results
Examining the importance of variables using the ANP method for each vulnerability function revealed that among the variables used to extract the exposure map, the two variables 'distance from the waterway' and 'frequency of floods' were assigned the highest importance with weights equal to 0.343 and 0.337, respectively. For the susceptibility map, the factors 'population density,' 'distance from residential areas,' and 'percentage of farming and ranching households' held the highest weights (0.361, 0.235, and 0.178, respectively). The resilience study indicated that the 'number of health and treatment centers' held the greatest importance among the variables, with a weight of approximately 65.5%. The exposure map showed that areas located at the watershed outlet were at a higher exposure. Areas near the outlet and in the basin's northeast region exhibited higher susceptibility to floods. Meanwhile, the central areas of the basin showed the highest resilience to floods, while the northern and southern parts had the least resilience. By combining the exposure, susceptibility, and resilience maps, it was found that the most vulnerable areas of the watershed (with a very high vulnerability class) were mainly located at the watershed's outlet, covering about 2.06% of the watershed. These zones exhibit a combination of high exposure to flood hazards, increased susceptibility, and low resilience, which may hinder their ability to recover from flooding events.
Conclusion and discution
Assessing the flood vulnerability map revealed that the southern areas of the Zarrinehrood Watershed, located near the watershed outlet, exhibit the highest vulnerability levels. This can be attributed to the combination of high flood exposure, high susceptibility, and low to moderate resilience in these areas. One of the advantages of this research can be attributed to the use of fuzzy value functions for data pixel valuation instead of classification. The provision of continuous values based on fuzzy functions preserves the data variability, offering a more realistic approach compared to methods such as input classification. Additionally, fuzzy values can help overcome ambiguity and reduce uncertainty. The main limitation of this research lies in the insufficient statistics and information available on flood resilience. Important criteria, such as the number of flood warning systems, rescue centers, past experiences with flood hazard, flood insurance, statistics of flood dams, shelters, and emergency services, were identified as significant factors in previous studies but were not accessible. Therefore, future studies should consider incorporating these factors if they become available. In general, it can be acknowledged that prioritizing the implementation of management policies with an emphasis on preventive and risk-based approach can take a more precise direction in relation to the results of this study and include the protection and restoration of vulnerable areas. |
