Flood risk assessment for Indian sub-continental river basins
Abstract. Floods are among India's most frequently occurring natural disasters, which disrupt all aspects of socio-economic well-being. A large population is affected by floods during almost every summer monsoon season in India, leaving its footprint through human mortality, migration, and damage to agriculture and infrastructure. Despite the massive imprints of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamical models, we reconstructed sub-basin level observed floods for the 1901–2020 period. Our modelling framework includes the influence of 51 major reservoirs that affect flow variability and flood inundation. Sub-basins in the Ganga and Brahmaputra River basins witnessed the greatest flood extent during the worst flood in the observational record. Major floods in the sub-basins of the Ganga and Brahmaputra occur during the late summer monsoon season (August–September). Beas, Brahmani, upper Satluj, Upper Godavari, Middle and Lower Krishna, and Vashishti sub-basins are among the most influenced by the dams, while Beas, Brahmani, Ravi, and Lower Satluj are among the most impacted by floods and the presence of dams. Bhagirathi, Gandak, Kosi, lower Brahmaputra, and Ghaghara are India's sub-basins with the highest flood risk. Our findings have implications for flood mitigation in India.
Urmin Vegad et al.
Status: open (until 09 Jun 2023)
- RC1: 'Comment on hess-2023-73', Anonymous Referee #1, 04 May 2023 reply
- RC2: 'Comment on hess-2023-73', Anonymous Referee #2, 08 Jun 2023 reply
Urmin Vegad et al.
Urmin Vegad et al.
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This study presents an important national-scale assessment of flood risk in India. The methodology is adequate and the manuscript is well written. I thus recommend its acceptance in HESS after minor review.
My only concern is that it is not clear throughout the text how reservoirs were considered in the study. In some parts of the methodology it is argued that the model is calibrated with dam storage data, and that the model considers the role of dams. Yet later it becomes more clear that actually the C-ratio was used, which is a proxy of storage effects; i.e. dams were actually not simulated by the model. Please clarify it across the text. Also, C-ratio is a proxy of storage effects and has some limitations. RoR dams can sometimes have high C-ratio but low impacts on downstream hydrology. Please add something about it to the discussion.
Line 15-16 This sentence is too vague, please rephrase it: 'Sub-basins in the Ganga and Brahmaputra River basins witnessed the greatest flood extent during the worst flood in the observational record.'
L. 66 This reference on the number of dams is from 2000. Is this number updated?
L. 100 GSW cannot estimate flooded vegetation and is usually limited for flood events because of cloud influence. Furthermore, your analysis is for 1901-2020, yet GSW covers only 1985-present. Please clarify the use of GSW in the text.
L. 121 At this stage, it seems that you've simulated the dam impact on downstream hydrology, but later in paragraph 138-148 you mention that the dam potential impact on hydrology was calculated with the C-ratio. Please clarify it throughout the text.
L. 212-213 To illustrate the fact that ' the worst flood in the same year did not affect all the sub-basins within a river basin', it would be very interesting to see a heat map of the drainage network colored according to the year of the worst flood in the century. It would be easy to make it based on the model outputs.
L. 221 It would be important to present in the larger map the locations of the sub-basins (a to j)
L. 234-234 Are there any references (especially in grey literature) that could be used to support your findings of when the worst flood occurred in the different sub-basins?
L. 279 Change to uppercase: 'C-ratio'
L. 338 Typo: 'Hirabayashi et al. (2013)'
L. 336 I missed in the discussion some comments about which mitigation measures are being undertaken by India at multiple government levels.