Multivariate Flood Risk Assessment of the Unplanned Semi- Urban Region by Incorporating Flood Hazard, Vulnerability, and Exposure

39 The mapping of flood risk is important to identify areas at risk and to improve flood disaster management and 40 preparedness. Flood risk is often expressed as the product of the hazard and the probable consequences which is 41 determined in terms of direct damages by assessing flood vulnerability and exposure. This study aims to develop 42 the flood risk assessment (FRA) framework for the dense semi-urban region by incorporating flood hazard, 43 topographic and socio-economic vulnerability, along with exposure, which is calculated by considering housing 44 conditions and classification of the damages by different land use and land cover classes. The FRA at the 45 municipal level is challenging due to the spatial resolution of social, economic, and medical indicators therefore 46 this study attempts to map the flood risk of the semi-urban region where the different zones and housing 47 communities are intertwined due to a lack of town planning. This FRA framework is applied to the Kulgoan- 48 Badlapur Municipal Council (KBMC) located at the Ulhas Riverbank, a west-flowing river in Maharashtra, 49 India. The city is located at the riverbank, which receives more than 2000 mm rainfall annually, and as most 50 growing industries and businesses depend on the river itself, the risk associated with flood increases 51 exponentially. The study shows that the spatial distribution of the flood risk is higher in the wards which are 52 densely populated and near the river stream. Despite low population and assets, some neighborhoods are highly 53 susceptible to flood due to their topographical conditions. Over the years, the population has been increasing in 54 the neighborhoods due to the new real estate projects, which will make them more vulnerable to floods, and the 55 overall risk is increasing. Study shows that the 82% of the area of Valavli and Manjarli ward comes under high 56 flood risk due to high topographic vulnerability and exposure. Similarly the few parts of Industrial zone also 57 comes under the high risk because of its location near river bank. The wards like Kulgaon comes under medium 58 flood risk despite its high socio-economic vulnerability and high exposure which proves that the flood risk is 59 majorly depends on the flood inundation. The exposure-based flood risk assessment will help to frame a more 60 practical and reasonable evaluation of risk for growing urban and industrial zones.


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To estimate the flood hazard, few studies proposed the multi-criteria methods, which calculate the hazard based 139 on the different factors associated with it. This type of calculation is more suitable for the spatial analysis of the 140 hazard, where the observed discharge and associated water levels data are not available. Figure

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The HEC-HMS uses the SCS-CN method for calculating the runoff volume in which the rainfall data and the     Table 1 shows the pairwise comparison of 172 different topographic parameters. For example, '1' is for the equally significant, 3 for moderately more 173 significant, 5 for strongly more significant, and 7 for very strongly more significant. And 2, 4, and 6 are the 174 intermediate scores. Table 2 shows the normalized weightage of each topographic parameter.

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The steps involved in the AHP procedure for calculating the weightages is given below:

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The comparison matrix is built with the diagonal elements being equal to 1, using the following expression:

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The consistency of the AHP method is assessed using consistency ratio (CR). Following is the expression for

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The combined vulnerability index (Vul) is calculated by assigning the weightages w 1 and w 2 to the topographic 209 vulnerability index (Vul topo ) and socio-economical vulnerability index (Vul SE ), respectively.

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Along with the vulnerability, the exposure is also incorporated for calculating the flood risk. The exposure helps 212 to narrow down the vulnerability that can predict the state of direct damages due to floods.

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Exposure is as significant as calculating flood hazard and vulnerability for analysing the flood risk. The  of importance based on its operation, economic output, and the number of people associated with it. Considering 220 all factors, the degree of importance is assigned to land use and land cover classes ranging from 0 to 1. For 221 example, the Industrial zone is considered high exposure to flooding due to possible severe direct damages, and 222 therefore the high degree of importance is assigned to it.

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Using the above equation, the spatial distribution of the exposure is calculated across the municipal council.

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After calculating the flood exposure, the flood risk is calculated using the following formula;

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The flood hazard is calculated by determining the flood inundation for the different return periods of rainfall.

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The IDF curve is plotted using Gumbel's equation with the help of hourly rainfall data collected from the Indian

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The flood hazard is the area inundated due to floodwater from the Ulhas River. The hazard is divided into three 336 classes. Figure 7 shows the spatial extent of the flood inundation associated with different return periods. The

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Here the average household income per pixel is considered, and therefore it can be seen that despite high       can be used to enhance overall flood hazard mapping, and the damages can be assessed accordingly.

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In this study the vulnerability is calculated by considering two parameters, topographic vulnerability and socio-     Flow chart depicting different steps involved for ood risk assessment.

Figure 2
Flow chart depicting different steps involved for ood hazard mapping. The ow chart includes the input data for calculating the discharge for different return periods using HEC-HMS model and then the extent of ood inundation using the HEC-RAS model.

Figure 3
Flow chart depicting different steps involved for ood Vulnerability mapping. The vulnerability is calculated by considering topographic vulnerability and socio-economic vulnerability.

Figure 4
The owchart depicting the steps for calculating the ood exposure. The exposure is calculated by considering building and infrastructure exposure, and land use and land cover exposure.

Figure 5
Location map of Kulgoan-Badlapur Municipal Council's (KBMC) area.    The ood exposure maps for the Kulgaon-Badlapur Municipal Council (KBMC) area, obtained by considering (A) the direct damages based on the land use and land cover classes; (B) based on the road network; (C) The ood exposure map, based on the combination of infrastructural exposure which is calculated by considering road density, plinth height, and type of building along with a degree of importance assigned to each land use and land cover class based on the probable direct damages.

Figure 10
The ood risk map of Kulgaon-Badlapur Municipal council (KBMC) area. The risk is calculated by multiplying the ood hazard, vulnerability, and exposure.