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<p>The present study performed a comprehensive assessment on the vulnerable villages in the landfall region of Cyclone Phailin (2013) using hazard, exposure, and vulnerability indices derived from major influencing factors, that include storm surge, inundation, land use, geomorphology, population density, infrastructure, and coastal protection works. Phailin formed over the Bay of Bengal (BoB) and rapidly intensified into a Category-5 storm with wind speeds attaining 215&#xa0;km/h before making landfall near the coast of Gopalpur, Odisha, on 12 October 2013, causing severe damage to agriculture, housing, and infrastructure facilities. An integrated storm surge model (Coupled Atmosphere-Ocean Model with Hydrodynamic model as CAOM + HD) was configured with high-resolution multiple meshes (50&#xa0;m over land, 150&#xa0;m nearshore, approximately 45&#xa0;km offshore) to predict surge and inundation characteristics. Two scenarios were simulated in this study: (i) real case of Phailin cyclone and (ii) considering a + 11% increase in wind intensity under the SSP-8.5 climate projection. Predicted storm surges were ~ 1.2&#xa0;m (existing) and ~ 1.45&#xa0;m (SSP-8.5), validated against tide gauge and IMD observations with correlation coefficient of 0.85. Maximum inundation depths were 0.9&#xa0;m and 1.5&#xa0;m, with an inland extent of ~ 2&#xa0;km and ~ 5&#xa0;km, respectively. Inundation was most severe along the right side of landfall location, damaging critical infrastructure and existing agricultural zones. Vulnerable villages in the risk zone were delineated using a GIS-based Analytic Hierarchy Process (AHP) and major/minor influencing factors. A total of 114 villages were identified in the risk zone, including 11 high-risk, 35 medium-risk, and 68 low-risk villages covering the Ganjam and Puri districts. Under the SSP-8.5 scenario, about 2–4 times more moderate- and low-vulnerable villages on the right side of the cyclone track shifted to the highly vulnerable category (31 high-risk, 68 medium-risk, and 15 low-risk villages). The outcome of this study is very useful to develop a framework for designing and implementing mitigation strategies to protect the life of coastal communities and reduce property loss under climate change.</p>

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Assessment of vulnerable villages on the landfall regions of intense cyclonic storms along the East Coast of India using an integrated storm surge modelling system - a case study for Cyclone Phailin

  • 期刊论文

  • 发表日期：

    2025年11月25日

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  • Koteshwaramma Thatiparthi ,
  • Subbareddy Bonthu,
  • Muruganandam R,
  • Venkata Ramu Ch.,
  • Prasad K. Bhaskaran,
  • Tirumaleswara Reddy N.,
  • Kuvar Satya Singh

摘要

The present study performed a comprehensive assessment on the vulnerable villages in the landfall region of Cyclone Phailin (2013) using hazard, exposure, and vulnerability indices derived from major influencing factors, that include storm surge, inundation, land use, geomorphology, population density, infrastructure, and coastal protection works. Phailin formed over the Bay of Bengal (BoB) and rapidly intensified into a Category-5 storm with wind speeds attaining 215 km/h before making landfall near the coast of Gopalpur, Odisha, on 12 October 2013, causing severe damage to agriculture, housing, and infrastructure facilities. An integrated storm surge model (Coupled Atmosphere-Ocean Model with Hydrodynamic model as CAOM + HD) was configured with high-resolution multiple meshes (50 m over land, 150 m nearshore, approximately 45 km offshore) to predict surge and inundation characteristics. Two scenarios were simulated in this study: (i) real case of Phailin cyclone and (ii) considering a + 11% increase in wind intensity under the SSP-8.5 climate projection. Predicted storm surges were ~ 1.2 m (existing) and ~ 1.45 m (SSP-8.5), validated against tide gauge and IMD observations with correlation coefficient of 0.85. Maximum inundation depths were 0.9 m and 1.5 m, with an inland extent of ~ 2 km and ~ 5 km, respectively. Inundation was most severe along the right side of landfall location, damaging critical infrastructure and existing agricultural zones. Vulnerable villages in the risk zone were delineated using a GIS-based Analytic Hierarchy Process (AHP) and major/minor influencing factors. A total of 114 villages were identified in the risk zone, including 11 high-risk, 35 medium-risk, and 68 low-risk villages covering the Ganjam and Puri districts. Under the SSP-8.5 scenario, about 2–4 times more moderate- and low-vulnerable villages on the right side of the cyclone track shifted to the highly vulnerable category (31 high-risk, 68 medium-risk, and 15 low-risk villages). The outcome of this study is very useful to develop a framework for designing and implementing mitigation strategies to protect the life of coastal communities and reduce property loss under climate change.