Multivariate indicator-based flood hazard mapping using primary drivers of coastal flood for India

被引:0
作者
Singh, Sweta [1 ]
Chakraborty, Ankan [2 ]
Ranjan, Ravi [1 ]
Karmakar, Subhankar [1 ,2 ]
机构
[1] Indian Inst Technol, Environm Sci & Engn Dept, Mumbai 400076, India
[2] Indian Inst Technol, Ctr Climate Studies, Mumbai 400076, India
关键词
Coastal flood; Entropy; IPCC; MADM; Multi-driver hazard; Tropical cyclone; VULNERABILITY; TOPSIS; RISK; FRAMEWORK;
D O I
10.1016/j.jenvman.2025.125477
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Coastal regions are densely populated and economically vital but highly exposed to multiple hazard drivers, including cyclones, storm surges, high tides, and intense rainfall. The IPCC AR6 (2021) emphasizes the need to assess coastal hazards as multi-driver compound hazard events. India, with its extensive coastline of similar to 11,098 km, is particularly prone to these drivers, necessitating a comprehensive multi-driver coastal flood hazard assessment. This study adopts an indicator-based approach employing Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with three objective weight estimation methods: equal weighting, statistical entropy-based weighting, and Principal Component Analysis (PCA)-based weighting, to comprehensively assess coastal flood hazard across India's coastal districts. The key indicators of coastal flood hazard include the total number of cyclones, probable maximum storm surge, probable maximum wind speed, maximum tidal range, and extreme precipitation exceedance probability. Methodological comparisons reveal that entropy-based weighting emphasizes cyclone frequency due to high data dispersion, while PCA-based weighting provides a balanced assessment by capturing overall variance across indicators. The entropy-weighted TOPSIS reflects a more optimistic hazard scenario, whereas the PCA-weighted TOPSIS offers a more conservative perspective. Our findings indicate that North-eastern and North-western coastal districts are highly hazard-prone. Coastal districts in Odisha and West Bengal consistently exhibit high hazard levels across all decades studied, while Kerala and Tamil Nadu generally show low hazard levels. Extreme rainfall and high tides predominantly drive high hazard levels in Gujarat and Maharashtra, whereas frequent cyclones are the primary hazard drivers along the Bay of Bengal coast. These findings provide a scientific basis for region-specific flood mitigation strategies, guiding policymakers in optimizing resource allocation for enhancing coastal resilience.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Compound Effects of Flood Drivers and Wetland Elevation Correction on Coastal Flood Hazard Assessment
    Munoz, D. F.
    Moftakhari, H.
    Moradkhani, H.
    WATER RESOURCES RESEARCH, 2020, 56 (07)
  • [2] Flood vulnerability of rural women - An indicator-based approach
    Matla, Holy Mercy Divina
    Funk, Christoph
    Gopinath, Pratheesh Pradeep
    Sathyan, Archana Raghavan
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2025, 121
  • [3] Assessing Urban Vulnerability in the Context of Flood and Heat Hazard: Pathways and Challenges for Indicator-Based Analysis
    Krellenberg, Kerstin
    Welz, Juliane
    SOCIAL INDICATORS RESEARCH, 2017, 132 (02) : 709 - 731
  • [4] Contextualizing institutional factors in an indicator-based analysis of hazard vulnerability for coastal communities
    Oulahen, Greg
    Chang, Stephanie E.
    Yip, Jackie Z. K.
    Conger, Tugce
    Marteleira, Michelle
    Carter, Christopher
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2018, 61 (14) : 2491 - 2511
  • [5] Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzau River Catchment, Romania
    Popa, Mihnea Cristian
    Peptenatu, Daniel
    Draghici, Cristian Constantin
    Diaconu, Daniel Constantin
    WATER, 2019, 11 (10)
  • [6] Indicator-based approach for fluvial flood risk assessment at municipal level in Slovakia
    Vojtek, Matej
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [7] Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India
    Chakrabortty, Rabin
    Pal, Subodh Chandra
    Rezaie, Fatemeh
    Arabameri, Alireza
    Lee, Saro
    Roy, Paramita
    Saha, Asish
    Chowdhuri, Indrajit
    Moayedi, Hossein
    GEOCARTO INTERNATIONAL, 2022, 37 (23) : 6713 - 6735
  • [8] A geospatial approach to flash flood hazard mapping in the city of Warangal, Telangana, India
    Bandi, Aneesha Satya
    Meshapam, Shashi
    Deva, Pratap
    ENVIRONMENTAL & SOCIO-ECONOMIC STUDIES, 2019, 7 (03): : 1 - 13
  • [9] Prioritizing flood drivers: an AHP-based study of physical factors in Digha's coastal belt, East Coast, India
    Nath, Anindita
    Koley, Bappaditya
    Choudhury, Tanupriya
    Biswas, Arkoprovo
    SPATIAL INFORMATION RESEARCH, 2025, 33 (02)
  • [10] Application of a fuzzy, indicator-based methodology for investigating the functional vulnerability of critical infrastructures to flood hazards
    Binesh, Negin
    Aronica, Giuseppe T.
    Hadzic, Emina
    Sulejmanovic, Suada
    Milisic, Hata
    Deda, Miranda
    Koxhai, Halim
    Mccarthy, Simon
    Rossello, Laura
    Viavattene, Christophe
    Mujic, Fehad
    Brigandi, Giuseppina
    Gabellani, Simone
    Masi, Rocco
    JOURNAL OF FLOOD RISK MANAGEMENT, 2025, 18 (01):