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Downloaded from the USGS Website Proceedings on International Conference on Disaster Risk Management, Dhaka, Bangladesh, January 12-14, 2019 DEVELOPING LOCAL LEVEL DISASTER RISK REDUCTION STRATEGIES CONSIDERING THE SPATIAL VARIATION OF STORM SURGE RISK: A CASE STUDY ON GABURA UNION, SYAMNAGAR UPAZILA R. Hassan1 and S.M. Haque2 Abstract Storm surge is one of the most disastrous natural hazards in the coastal regions of Bangladesh. Very often disaster risk reductions (DRR) strategies to minimize risks stemming from this hazard are ineffective due to the gross aggregation and have been found taken without considering spatial variations of risk profiles at local levels. This study aims to find out the spatial variations of storm surge risk at the local level and formulation of DRR strategies according to the variations of local level storm surge risk profile. For risk profiling, a GIS- based multi-criteria approach (MCA) has been adopted with four hazard indicators along with eleven vulnerability indicators. Gabura, a coastal union of Syamnagar upazila (sub-district) of Bangladesh has been selected as the study area. Data and information have been derived from administering a questionnaire survey and relevant searching of secondary sources. Analytical hierarchical process (AHP) has been used for selecting weights of the indicators. Findings suggest that the risk profile of the study area vary spatially since hazard exposure and vulnerability indicators showed significant variations across nine wards (smallest administrative units) of the study area. By analyzing DRR strategies of different Government agencies and non-governmental organizations, it has been observed that such variations in risk situations across the study area have largely been ignored while taking DRR strategies for the study area. Therefore, some new DRR strategy guidelines incorporating variations in the risk profile of the study area have been proposed. Keywords: Storm Surge Risk Profile, Spatial Variation, Multi-Criteria Approach, GIS, Disaster Risk Reduction Strategy. Introduction Bangladesh is one of the most vulnerable countries to different natural disasters due to its geographic location. Cyclone and storm surges are the most disastrous natural hazards in the coastal regions as it frequently damages the life and properties of the people of these localities (Hossain, Paul, Roy, & Hasan, 2014). Natural hazards cannot be stopped fully but the risk of these hazards can be substantially reduced. Risk reduction strategies are very much important to minimize future risks. Historically, the disaster management of Bangladesh is confined to relief and rehabilitation. But, at present, it is more oriented to risk reduction from the previously practiced after a disaster response. In risk management literature, there is a growing consensus that only the reduction of the probability of the occurrence is not enough. The reduction of the consequence of the hazard event is also important. However, there exists a serious understanding gap in risk management policies and local level strategies currently practiced in Bangladesh. The spatial variation of risk is not considered in the risk reduction strategies. Therefore, a widespread misallocation of resources is prevalent. Therefore, this study focuses on assessing the spatial variation of storm surge risk by considering two components of risk formulation, viz., hazard and vulnerability. GIS-based indexing has been conducted to assess the spatial variation of storm surge risk. It is expected that the assessment technique of this study would be an exemplary model for further risk assessment studies, especially in the coastal areas of Bangladesh. Study area This study has been conducted in Gabura union, Syamnagar upazila of Satkhira district of Bangladesh. This union is situated between latitude 22̊ 13.2 to 22̊ 18.1 north and longitude 89̊14.9.2 east. The union has an area of 33 sq. km. (BBS, 2011). Cyclone and storm surges are prea dominant natural hazard in this area and cause significant damages to life and properties of people. There are nine wards in the Gabura union. Methodology For developing the storm surge risk profile of the nine wards of Gabura union, risk index has been calculated 1 Student, Urban and Rural Planning Discipline, Khulna University, Khulna-9208, Bangladesh 2 Professor, Urban and Rural Planning Discipline, Khulna University, Khulna-9208, Bangladesh Email of Corresponding Author – [email protected] Page | 530 Proceedings on International Conference on Disaster Risk Management, Dhaka, Bangladesh, January 12-14, 2019 by the following equation developed from (Islam, Swapan, & Haque, 2013) and (Wang, Li, Tang, & Zeng, 2011). Risk Index (0-2 score) = Hazard Index (0-1) + Vulnerability Index (0-1) ……………….………..(1) Hazard Index= Reclassify the hazard indicators *Weights……………………………......……….(2) Vulnerability Index= IVSP+IVS/2…………………………..……………………………..………(3) Spatial Vulnerability Index= GIS multi-criteria analysis score Clip raster by ward boundary Reclassify*Weight…(4) IVS= Reclassify the social vulnerability indicators* Weight……………………..…………..……(5) Here, from the equation (1), risk index has been calculated by combining the hazard and vulnerability index scores. Risk index has been calculated in 0-2 scale and both hazard and vulnerability indices have been calculated in 0-1 scale. The hazard index has been calculated from equation 2 with reclassify the hazard indicators into three categories and then multiply those with weights. Equation 3 has been used to calculate the combined vulnerability index which is the summation of social and spatial vulnerability index and then divided by 2. GIS multi-criteria analysis has been conducted in Arc-GIS 10.3. The spatial risk index map is then clipped by ward boundary shape file and then reclassify it according to the reclassification score and multiplied it by weight (Equation-4). The social vulnerability index has been calculated by equation 5 by reclassifying the social vulnerability indicators into three categories and multiply it with weight. The weights of the indicators have been calculated by the analytical hierarchical process (AHP) developed by (Saaty, 1990). The comparative score of AHP has been calculated from FGD with local people and expert opinion. The hazard and vulnerability indicators, their reclassification and weight are as follows (Table-1). The reclassification score is for low risk=.3, medium risk=.6, and high risk=1. The data has been collected by administering a questionnaire survey of 117 sample households of nine wards with 13 households each. For determining the future threat of storm surge in different wards of the study area, the future surge height has been calculated by using the following Gumbel distribution equation- Qt= Qav + K Here, Qt=t years’ highest surge level, Qav=Average surge height of previous storm surge, =Standard deviation. K=-√6/π(λ-ln(ln(T-ln(T-1))) Where, λ is the return period; in this study 10 years return period of the historical surge height data (Table- 2), surge height will be=9.21m. Then, the Digital Elevation Model (DEM) of the study area has downloaded from the USGS website. After conducting the unsteady flow analysis in HEC-RAS, clip the raster file by the ward boundary and the percentage of inundated area in each ward have been calculated. Table 2. Historic surge height data Year Surge height (Meter) 1988 13 1996 9 2002 11 2009 15 Source: FGD Data analysis The collected data has been analyzed through SPSS, ARC-GIS, and HEC-RAS. The Arc-GIS model builder tool has been used to conduct the multi-criteria analysis by buffering, reclassification and weighted overlay operation. The HEC-RAS has been used to determine the future inundated area. The data has been analyzed and the hazard, vulnerability, and risk index have been calculated in excel. Page | 531 Proceedings on International Conference on Disaster Risk Management, Dhaka, Bangladesh, January 12-14, 2019 Table 1. The indicators, their reclassification, and weight Indicators Low Moderate High Weight Hazard 0.056 Frequency of hazard 0 1-3 >3 Duration of stagnated 0-6 0.456 6 months-1 year 1-3 years water months 0.308 Inundated area (%) 0-20 20-50 >50 Average damages of 0.181 3500m 1000m 500m households Spatial Vulnerability 0.106 Proximity to river 2000m 1000m 500m 0.260 Proximity to road 200m 400m 800m 0.6334 Proximity to cyclone center 3500m 1000m 500m Socio-economic Vulnerability Average monthly income of the 1000- 5000-10000 <5000 0.167 household (BDT) 2000 50+ 30-50 <30 0.108 Literacy rate (percentage) 5-10 10-13 0.175 No. of kutcha households 0-5 0-15 15-25 25+ 0.137 Unemployment (% Less than 500-700 >700 0.133 Population density 500 50-80 80+ 0.071 Training on disaster management (%) 50 25 25-40 >40 0.081 % of people use the sanitary latrine 0-.5km 5-1.5km >1.5km 0.129 The distance of drinking water source Page | 532 Proceedings on International Conference on Disaster Risk Management, Dhaka, Bangladesh, January 12-14, 2019 Results and Discussions The hazard map does not show significant variations for a small study area and the impact of hazard is almost similar across the nine wards of Gabura union (Fig-2) The union is situated in a low-lying area. Therefore, almost all the areas of the union will be inundated due to the surge height of 9.21m in 10 years return period (Fig-1). However, the vulnerability map shows significant variations across the nine wards (Fig-3) Therefore, the final risk map shows variations too (Fig-4). Existing DRR interventions have been analyzed through a thorough review of the information gathered from secondary sources. The Government interventions are mainly income generating activities like VGD, VGF, LGSP. KABITA, KABIKHA etc. Moreover, there are 8 local and international NGO’s are working there and they have taken several interventions like providing disaster management training, providing economic support to the people, repair the road and embankment etc. Both Government and NGO.s interventions have taken across the whole union. However, from the risk profiling, it has been observed that ward number 1 and ward number 8 possesses a higher risk than the other 6 wards.
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