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Identification of flash-floods-prone river reaches in Beas river basin using GIS-based multi-criteria technique: validation using field and satellite observations

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Abstract

In view of an exponential increase in the negative impacts of flash-floods globally, the present work aims at the identification of flash-floods-prone river reaches in the Beas river basin, Himachal Pradesh, India using a multi-criteria indexing technique. The flood hazard index (FHI) was computed by implementing analytical hierarchy process (AHP) model on 6 hydrologic parameters influencing flood hazard, namely rainfall intensity, curve number (CN) grid, time of travel, slope, Manning's roughness coefficient and drainage density. The CN grid (empirical parameter to estimate direct surface runoff) was used as one of the parameters which depend upon the land use, hydrologic soil group and hydrologic conditions. It is imperative to mention that remote sensing and geographical information system (GIS) techniques played a crucial role in the preparation of these 6 parameter layers. The AHP model calculates the normalized weights for each parameter using pair-wise comparison matrices. The rainfall intensity and curve number were the factors having the highest normalized weight of 34.52 each. Subsequently, the estimated weights of the parameters and hazard level-wise rating scores were used in a GIS environment to generate FHI. The generated FHI raster was masked using floodplain layer within geomorphology map and river buffer to identify flash-floods-affected river reaches. The generated flash-floods map was validated by historical flash-floods ground points, field observations and remote sensing data. The results depicted that the river reaches in the north and east of the Beas basin are susceptible to flash-floods which are mainly governed by heavy rainfall intensity and high runoff characteristics. The river stretches namely Bahang–Manali (Beas), Kullu–Bhuntar (Beas) and Manikaran–Kheer-Ganga (Parvati) have been categorized into very high and high flash-floods zones. Decreasing trend of normalized differential vegetation index (NDVI) was observed for river reaches falling within the very high and high zones indicating the vegetation loss post successive flash-floods events. The river order 2 lies in the very high and high flash-floods zones, indicating the fact that the contribution of tributaries is significant to flood events. Flash-floods map will serve as catastrophic product, which will help policymakers to take suitable measures to reduce the risk of flash-floods.

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Acknowledgements

We are thankful to Dr. Prakash Chauhan, Director, IIRS for providing all the required infrastructure facilities and valuable suggestions, support and encouragement for completion of this work. We are grateful to Bhakra Beas Management Board, Sundernagar, India, for providing required hydrometric data. We acknowledge the efforts of scientists associated with the National Remote Sensing Centre, Alaska Satellite Facility, Google Earth, Google Earth Engine and Environmental Systems Research Institute (ESRI) for providing LULC, topographic data and high-resolution base layers. This work is partially funded under ISRO-TDP project ‘Flood-prone areas identification and flood risk assessment using integrated process-based modelling and geospatial techniques’.

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Correspondence to Pankaj R. Dhote.

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The authors declare that they have no known conflict of interests that could have appeared to influence the work reported in this paper.

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Singh, S., Dhote, P.R., Thakur, P.K. et al. Identification of flash-floods-prone river reaches in Beas river basin using GIS-based multi-criteria technique: validation using field and satellite observations. Nat Hazards 105, 2431–2453 (2021). https://doi.org/10.1007/s11069-020-04406-w

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  • DOI: https://doi.org/10.1007/s11069-020-04406-w

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