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Flood susceptibility and flood frequency modeling for lower Kosi Basin, India using AHP and Sentinel-1 SAR data in geospatial environment

Author

Listed:
  • Vikash Shivhare

    (CII-Triveni Water Institute)

  • Alok Kumar

    (University of Delhi)

  • Reetesh Kumar

    (GLA University)

  • Satyanarayan Shashtri

    (Nalanda University)

  • Javed Mallick

    (King Khalid University)

  • Chander Kumar Singh

    (TERI School of Advanced Studies)

Abstract

The Lower Kosi Basin (LKB) in North Bihar is highly prone to floods and is influenced by upstream hydrology. A flood susceptibility index has been modelled by integrating eleven flood conditioning parameters (precipitation, elevation, slope, drainage density, distance from the river, ruggedness index, topographic wetness index, stream power index, curvature, normalized difference vegetation index, land use and land cover) derived from the satellite data, using a weighted linear summation model. The study uses Sentinel-1 synthetic aperture radar data to estimate flood frequency over a temporal scale of 2016–2020. The flood frequency was used to validate the flood susceptibility derived using multi-criteria decision making methods combined with geographical information system (MCDM-GIS). The study shows that ~ 66% of the area in LKB is susceptible to high to moderate flooding while the remaining ~ 34% is falls in the low flooding category. 15.24% of the area has high frequency (> 3 flood occurrences) of the flood, 9.66% has moderate (2 flood occurrences) and 9.72% of the area faced one-time flood during five years of period (2016–2020). The accuracy of MCDM-GIS derived flood susceptibility map was assessed using area under curve, confusion matrix, precision, recall, F1 score, weighted F1 score and overall accuracy.

Suggested Citation

  • Vikash Shivhare & Alok Kumar & Reetesh Kumar & Satyanarayan Shashtri & Javed Mallick & Chander Kumar Singh, 2024. "Flood susceptibility and flood frequency modeling for lower Kosi Basin, India using AHP and Sentinel-1 SAR data in geospatial environment," 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(13), pages 11579-11610, October.
  • Handle: RePEc:spr:nathaz:v:120:y:2024:i:13:d:10.1007_s11069-024-06614-0
    DOI: 10.1007/s11069-024-06614-0
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