IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v121y2025i8d10.1007_s11069-025-07143-0.html
   My bibliography  Save this article

Flood susceptibility mapping using geospatial techniques: a study of the Kashmir Basin in the Northwest Himalaya

Author

Listed:
  • Rabbya ul Qalab

    (University of Kashmir)

  • M. Sultan Bhat

    (University of Kashmir)

  • Akhtar Alam

    (University of Kashmir)

  • Mussadiq Hussain Qureshi

    (Department of Higher Education)

  • Mohd Saleem Wani

    (University of Kashmir)

  • Nahida Yousuf

    (University of Kashmir)

Abstract

Floods are frequently occurring natural hazard experienced globally, causing substantial damage to several sectors and disruption to the socioeconomic functioning of the society. The Kashmir Basin is frequently hit by flooding due to the combined effects of various geomorphic, meteorological, and human-induced factors. The purpose of the current study is to assess the flood susceptibility of the Kashmir Basin. The objective of the study was accomplished with the coupled application of Frequency Ratio (FR) Model and GIS. The study considered 18 conditioning factors for flood susceptibility mapping and prediction. The relative flood frequency ratio was used to determine the correlation between flood conditioning factors and flood occurrences. A total of 153 flood locations reported in the past were considered; of which 70% were used for data training and susceptibility mapping and the remaining 30% were utilized for the validation of simulated results. The Receiver Operating Characteristic (ROC) curve was generated to depict the accuracy of generated flood susceptibility maps and with an observed success rate of 0.92, the predictions were treated a reliable. The findings reveal that out of the total land area, about 11.51% exhibits 'very high' susceptibility, whereas 18.44% and 18.12% of the land areas show 'high' and 'moderate' susceptibility levels respectively. The identification and classification of flood susceptibility zones has practical implications for decision-makers to develop effective flood mitigation measures and enhance the efficiency of flood disaster management in the region.

Suggested Citation

  • Rabbya ul Qalab & M. Sultan Bhat & Akhtar Alam & Mussadiq Hussain Qureshi & Mohd Saleem Wani & Nahida Yousuf, 2025. "Flood susceptibility mapping using geospatial techniques: a study of the Kashmir Basin in the Northwest Himalaya," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(8), pages 9067-9101, May.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:8:d:10.1007_s11069-025-07143-0
    DOI: 10.1007/s11069-025-07143-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-025-07143-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-025-07143-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xin Huang & Hongzhuan Tan & Jia Zhou & Tubao Yang & Abuaku Benjamin & Shi Wen & Shuoqi Li & Aizhong Liu & Xinhua Li & Shuidong Fen & Xinli Li, 2008. "Flood hazard in Hunan province of China: an economic loss analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 47(1), pages 65-73, October.
    2. Hamid Pourghasemi & Biswajeet Pradhan & Candan Gokceoglu, 2012. "Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 965-996, September.
    3. Hamideh Nouri & Sattar Chavoshi Borujeni & Sina Alaghmand & Sharolyn J. Anderson & Paul C. Sutton & Somayeh Parvazian & Simon Beecham, 2018. "Soil Salinity Mapping of Urban Greenery Using Remote Sensing and Proximal Sensing Techniques; The Case of Veale Gardens within the Adelaide Parklands," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    4. Huaijun Wang & Zhi Li & Lei Cao & Ru Feng & Yingping Pan, 2021. "Response of NDVI of Natural Vegetation to Climate Changes and Drought in China," Land, MDPI, vol. 10(9), pages 1-24, September.
    5. Hameeda Sultan & Jinyan Zhan & Wajid Rashid & Xi Chu & Eve Bohnett, 2022. "Systematic Review of Multi-Dimensional Vulnerabilities in the Himalayas," IJERPH, MDPI, vol. 19(19), pages 1-20, September.
    6. Gowhar Meraj & Shakil Romshoo & A. Yousuf & Sadaff Altaf & Farrukh Altaf, 2015. "Assessing the influence of watershed characteristics on the flood vulnerability of Jhelum basin in Kashmir Himalaya: reply to comment by Shah 2015," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(1), pages 1-5, August.
    7. Y. Liu & F. Smedt, 2005. "Flood Modeling for Complex Terrain Using GIS and Remote Sensed Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(5), pages 605-624, October.
    8. Yi-Ru Chen & Chao-Hsien Yeh & Bofu Yu, 2011. "Integrated application of the analytic hierarchy process and the geographic information system for flood risk assessment and flood plain management in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(3), pages 1261-1276, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bosy A. El-Haddad & Ahmed M. Youssef & Hamid R. Pourghasemi & Biswajeet Pradhan & Abdel-Hamid El-Shater & Mohamed H. El-Khashab, 2021. "Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 83-114, January.
    2. Khabat Khosravi & Ebrahim Nohani & Edris Maroufinia & Hamid Reza Pourghasemi, 2016. "A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making techn," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 947-987, September.
    3. Ishfaq Hussain Malik & Rayees Ahmed & James D. Ford & Mir Shahid Ahmad Shakoor & Shahid Nabi Wani, 2024. "Beyond the banks and deluge: understanding riverscape, flood vulnerability, and responses in kashmir," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 13595-13616, November.
    4. Shanshan Hu & Xiangjun Cheng & Demin Zhou & Hong Zhang, 2017. "GIS-based flood risk assessment in suburban areas: a case study of the Fangshan District, Beijing," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1525-1543, July.
    5. Ebrahim Ahmadisharaf & Alfred Kalyanapu & Eun-Sung Chung, 2015. "Evaluating the Effects of Inundation Duration and Velocity on Selection of Flood Management Alternatives Using Multi-Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2543-2561, June.
    6. Abdulwaheed Tella & Abdul-Lateef Balogun, 2020. "Ensemble fuzzy MCDM for spatial assessment of flood susceptibility in Ibadan, Nigeria," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 2277-2306, December.
    7. Moumita Palchaudhuri & Sujata Biswas, 2016. "Application of AHP with GIS in drought risk assessment for Puruliya district, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(3), pages 1905-1920, December.
    8. Zahra Ganji & Alireza Shokoohi & Jamal Samani, 2012. "Developing an agricultural flood loss estimation function (case study: rice)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 405-419, October.
    9. Txomin Bornaetxea & Juan Remondo & Jaime Bonachea & Pablo Valenzuela, 2023. "Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (Spain)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(3), pages 2513-2542, September.
    10. Gökhan Demir & Mustafa Aytekin & Aykut Akgün & Sabriye İkizler & Orhan Tatar, 2013. "A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1481-1506, February.
    11. Mónica de Castro-Pardo & Pascual Fernández Martínez & Amelia Pérez Zabaleta & João C. Azevedo, 2021. "Dealing with Water Conflicts: A Comprehensive Review of MCDM Approaches to Manage Freshwater Ecosystem Services," Land, MDPI, vol. 10(5), pages 1-32, April.
    12. Rui Yuan & Jing Chen, 2022. "A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(2), pages 1393-1426, November.
    13. Viet-Ha Nhu & Ataollah Shirzadi & Himan Shahabi & Sushant K. Singh & Nadhir Al-Ansari & John J. Clague & Abolfazl Jaafari & Wei Chen & Shaghayegh Miraki & Jie Dou & Chinh Luu & Krzysztof Górski & Binh, 2020. "Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms," IJERPH, MDPI, vol. 17(8), pages 1-30, April.
    14. Wen-Chun Lo & Ting-Chi Tsao & Chih-Hao Hsu, 2012. "Building vulnerability to debris flows in Taiwan: a preliminary study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(3), pages 2107-2128, December.
    15. Sadhan Malik & Subodh Chandra Pal & Biswajit Das & Rabin Chakrabortty, 2020. "Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5651-5685, August.
    16. Shuang Liu & Rui Liu & Nengzhi Tan, 2021. "A Spatial Improved-kNN-Based Flood Inundation Risk Framework for Urban Tourism under Two Rainfall Scenarios," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    17. Subhankar Chakraborty & Sutapa Mukhopadhyay, 2019. "Assessing flood risk using analytical hierarchy process (AHP) and geographical information system (GIS): application in Coochbehar district of West Bengal, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 247-274, October.
    18. Santos Daniel Chicas & Heng Li & Nobuya Mizoue & Tetsuji Ota & Yan Du & Márk Somogyvári, 2024. "Landslide susceptibility mapping core-base factors and models’ performance variability: a systematic review," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 12573-12593, November.
    19. Mengmeng Gao & Nan Yang & Qiong Liu, 2024. "What Drives Vegetation Evolution in the Middle Reaches of the Yellow River Basin, Climate Change or Human Activities?," Sustainability, MDPI, vol. 16(22), pages 1-21, November.
    20. Kibeom Kwon & Minkyu Kang & Dongku Kim & Hangseok Choi, 2023. "Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory," Sustainability, MDPI, vol. 15(15), pages 1-15, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:121:y:2025:i:8:d:10.1007_s11069-025-07143-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.