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E.E.R. 2024, 14(1): 121-138 |
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Mohammadi Issaabad S, Safari A, Ahmadabadi A, Darabi Shahmari S. Flood vulnerability assessment, Case study: Cheshmekile Tankabon river. E.E.R. 2024; 14 (1) :121-138
URL: http://magazine.hormozgan.ac.ir/article-1-812-en.html
URL: http://magazine.hormozgan.ac.ir/article-1-812-en.html
Department of Geomorphology, Khwarazmi University, Tehran, Iran , saffari@khu.ac.ir
Abstract: (1728 Views)
1- Introduction
Flood is one of the most common and widespread natural disasters that occur frequently around the world (Patra et al, 2016). In recent years, the damages and casualties caused by floods have been affected by various factors. However, increased population, land use change, and the development of residential areas are considered to be the boosters for the increase in damages. The decrease in the active width of rivers by different factors especially human interventions has increased the vulnerability facing floods. The damages are classified into tangible or intangible types. Tangible damages, including the destruction of buildings, agricultural lands, roads and transportation systems, infrastructures, environmental ecosystems, and human casualties impose a major negative emotional burden on the target society (Tiryaki and Karaca, 2018). Among the natural disasters, floods cause the most damage to the agriculture, fisheries, housing, and infrastructure sectors and severely affect economic and social activities. Despite the natural cause of the floods in Iran, the main cause of the damages may be due to the human settlement in the high-risk areas (Mustafa et al, 2018, Nga et al, 2018). In recent years, about 70% of the annual budget dedicated to decreasing natural disasters have been allocated to recovering the damages by flood and this trend is increasing, so the 250% growth of flood damages in the last five decades confirms this claim (Demir and Kisi, 2016).
3- Results
This applied quantitative research was carried out in the Cheshme kile river, located in Tonekabon City in 2021-2022. In the first stage, indicators affecting flood vulnerability were prepared using the study of the research background. In this regard, the data of 6 indicators of aging ratio, sex ratio, youth ratio, land use, population density, structure quality, and material quality were prepared as effective indicators of flood vulnerability. Data were collected using the statistical yearbooks by referring to the National Statistics Center of Iran, which was recorded in the last census in 2016. In the next step, the relationships defined according to Table 1 were used to prepare each index. Zoning the floodplain area is applicable to detect the vulnerable area. The map of floodplain zoning is the result of modeling based on the HEC-RAS model (Saffari et al, 2023). The data of each of the indicators was overplayed with the layer of urban blocks of Tonekabon using ArcGIS 10.3 software. Then, the Vikor method was used to prepare flood vulnerability zoning maps. The data normalization was carried out due to the different data spectrums. Then, the weight of each index and sub-index was prepared using the AHP method. After determining the weight of each index, positive and negative ideals were determined. Positive ideals are the highest values of each index and negative ideals are the lowest values of each index. The result of subtracting the positive ideal from other sub-indices is the index of usefulness, and the result of subtracting the negative ideal from each of the sub-indices is the regret index (Table 2). The regret and usefulness indicators were classified (very high, high, medium, low, and very low) for each of the layers using the reclassify tool through ArcGIS software. (Figures 2 and 3). The classification spectrum for each of the layers is presented in Table 2. After calculating the indices of usefulness and regret, a flood vulnerability map was prepared for the study area using Equation 5 (Figure 3). In this map, values close to zero show the highest vulnerable area, and values close to one show the lowest vulnerable area conditions. To better understand the distribution of risk zones, the target map was classified into 5 spectrums of very high risk, high risk, medium risk, low risk, and very low. According to the findings, the area of risk zones in very high, high, medium, low, and very low classes were 0.36, 0.26, 0.34, 0.28, and 0.19 kilometers, respectively. The largest and lowest area of risk zones were observed in the very high and very low classes.
4- Discussion & Conclusions
The aim of this study was to investigate the vulnerability of the Cheshme Kile River in the area of Tonekabon City facing floods using the Vikor multi-criteria decision-making method based on the geographic information system (GIS). Effective criteria in flood vulnerability included land use, population density, youth ratio, aging ratio, gender ratio, and quality of structures and materials. The findings show the low vulnerability facing floods in the southern areas on the left side and the northern areas on the left and right sides of the Cheshme kile river due to the low population density, the low active width of the river channel, and the presence of green spaces. On the other hand, the density of the population and the dense building texture on the left banks in the western and northwestern margins have led to a decrease in soil permeability levels and an increase in the volume of urban runoff. Therefore, these areas are more vulnerable to floods and urban runoff. According to the findings, the highest and lowest areas were observed at very high risk and very low zones.
The width channel of the river has increased downstream, while the slope of the river has decreased, which
increases the water level and the possibility of financial and human losses. As can be seen in Figure 4, areas with high vulnerability can be seen on the left and right banks in the downstream section of the river. In these layers, factors such as population density at the range of 192-67 and 192-408, youth ratio in the ranges of 19.21-26-43 and 14.19-21, structure quality in the very unfavorable range, the aging ratio in the range 9-18, the gender ratio in the range of 27.56-44.74 and building and industrial lands have increased the risk of flood vulnerability in this area. Naturally, by reducing the range of investigated indicators, the risk of flood vulnerability also decreases. For example, in a factor such as the youth ratio, the lower the relative spectrum, the greater the risk of flood damage.
Flood is one of the most common and widespread natural disasters that occur frequently around the world (Patra et al, 2016). In recent years, the damages and casualties caused by floods have been affected by various factors. However, increased population, land use change, and the development of residential areas are considered to be the boosters for the increase in damages. The decrease in the active width of rivers by different factors especially human interventions has increased the vulnerability facing floods. The damages are classified into tangible or intangible types. Tangible damages, including the destruction of buildings, agricultural lands, roads and transportation systems, infrastructures, environmental ecosystems, and human casualties impose a major negative emotional burden on the target society (Tiryaki and Karaca, 2018). Among the natural disasters, floods cause the most damage to the agriculture, fisheries, housing, and infrastructure sectors and severely affect economic and social activities. Despite the natural cause of the floods in Iran, the main cause of the damages may be due to the human settlement in the high-risk areas (Mustafa et al, 2018, Nga et al, 2018). In recent years, about 70% of the annual budget dedicated to decreasing natural disasters have been allocated to recovering the damages by flood and this trend is increasing, so the 250% growth of flood damages in the last five decades confirms this claim (Demir and Kisi, 2016).
3- Results
This applied quantitative research was carried out in the Cheshme kile river, located in Tonekabon City in 2021-2022. In the first stage, indicators affecting flood vulnerability were prepared using the study of the research background. In this regard, the data of 6 indicators of aging ratio, sex ratio, youth ratio, land use, population density, structure quality, and material quality were prepared as effective indicators of flood vulnerability. Data were collected using the statistical yearbooks by referring to the National Statistics Center of Iran, which was recorded in the last census in 2016. In the next step, the relationships defined according to Table 1 were used to prepare each index. Zoning the floodplain area is applicable to detect the vulnerable area. The map of floodplain zoning is the result of modeling based on the HEC-RAS model (Saffari et al, 2023). The data of each of the indicators was overplayed with the layer of urban blocks of Tonekabon using ArcGIS 10.3 software. Then, the Vikor method was used to prepare flood vulnerability zoning maps. The data normalization was carried out due to the different data spectrums. Then, the weight of each index and sub-index was prepared using the AHP method. After determining the weight of each index, positive and negative ideals were determined. Positive ideals are the highest values of each index and negative ideals are the lowest values of each index. The result of subtracting the positive ideal from other sub-indices is the index of usefulness, and the result of subtracting the negative ideal from each of the sub-indices is the regret index (Table 2). The regret and usefulness indicators were classified (very high, high, medium, low, and very low) for each of the layers using the reclassify tool through ArcGIS software. (Figures 2 and 3). The classification spectrum for each of the layers is presented in Table 2. After calculating the indices of usefulness and regret, a flood vulnerability map was prepared for the study area using Equation 5 (Figure 3). In this map, values close to zero show the highest vulnerable area, and values close to one show the lowest vulnerable area conditions. To better understand the distribution of risk zones, the target map was classified into 5 spectrums of very high risk, high risk, medium risk, low risk, and very low. According to the findings, the area of risk zones in very high, high, medium, low, and very low classes were 0.36, 0.26, 0.34, 0.28, and 0.19 kilometers, respectively. The largest and lowest area of risk zones were observed in the very high and very low classes.
4- Discussion & Conclusions
The aim of this study was to investigate the vulnerability of the Cheshme Kile River in the area of Tonekabon City facing floods using the Vikor multi-criteria decision-making method based on the geographic information system (GIS). Effective criteria in flood vulnerability included land use, population density, youth ratio, aging ratio, gender ratio, and quality of structures and materials. The findings show the low vulnerability facing floods in the southern areas on the left side and the northern areas on the left and right sides of the Cheshme kile river due to the low population density, the low active width of the river channel, and the presence of green spaces. On the other hand, the density of the population and the dense building texture on the left banks in the western and northwestern margins have led to a decrease in soil permeability levels and an increase in the volume of urban runoff. Therefore, these areas are more vulnerable to floods and urban runoff. According to the findings, the highest and lowest areas were observed at very high risk and very low zones.
The width channel of the river has increased downstream, while the slope of the river has decreased, which
increases the water level and the possibility of financial and human losses. As can be seen in Figure 4, areas with high vulnerability can be seen on the left and right banks in the downstream section of the river. In these layers, factors such as population density at the range of 192-67 and 192-408, youth ratio in the ranges of 19.21-26-43 and 14.19-21, structure quality in the very unfavorable range, the aging ratio in the range 9-18, the gender ratio in the range of 27.56-44.74 and building and industrial lands have increased the risk of flood vulnerability in this area. Naturally, by reducing the range of investigated indicators, the risk of flood vulnerability also decreases. For example, in a factor such as the youth ratio, the lower the relative spectrum, the greater the risk of flood damage.
Received: 2023/07/21 | Published: 2024/04/8
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