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Article

Flood Forecasting in Large River Basins Using FOSS Tool and HPC

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Centre for Development of Advanced Computing, C-DAC Innovation Park, Panchawati Road, Panchawati, Pashan, Pune 411008, Maharashtra, India
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Department of Environmental Science, Savaitribai Phule Pune University (SPPU), Ganeshkhind Road, Ganeshkhind, Pune 411007, Maharashtra, India
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Sinchai Bhawan, Ganga Flood Control Commission, Department of Water Resources, RD & GR, Ministry of Jal Shakti, Govt. of India, Patna 800015, Bihar, India
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Hydrological Observation Circle, Central Water Commission (CWC), Mahanadi Bhawan, Department of Water Resources, RD & GR, Ministry of Jal Shakti, Govt. of India, Bhoi Nagar, Bhubaneshwar 751002, Odisha, India
*
Author to whom correspondence should be addressed.
Academic Editor: Pavol Miklánek
Water 2021, 13(24), 3484; https://doi.org/10.3390/w13243484
Received: 1 October 2021 / Revised: 19 November 2021 / Accepted: 26 November 2021 / Published: 7 December 2021
(This article belongs to the Special Issue Research of River Flooding)
The Indian subcontinent is annually affected by floods that cause profound irreversible damage to crops and livelihoods. With increased incidences of floods and their related catastrophes, the design, development, and deployment of an Early Warning System for Flood Prediction (EWS-FP) for the river basins of India is needed, along with timely dissemination of flood-related information for mitigation of disaster impacts. Accurately drafted and disseminated early warnings/advisories may significantly reduce economic losses incurred due to floods. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. HPC, remote sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. The model is open-source, supports geographic file formats, and is capable of simulating rainfall run-off, river routing, and tidal forcing, simultaneously. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta, 9225 sq km) with actual and predicted discharge, rainfall, and tide data. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. View Full-Text
Keywords: flood; prediction; large river basin; FOSS; HPC; ANUGA Hydro; Mahanadi River Basin flood; prediction; large river basin; FOSS; HPC; ANUGA Hydro; Mahanadi River Basin
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MDPI and ACS Style

Dutta, U.; Singh, Y.K.; Prabhu, T.S.M.; Yendargaye, G.; Kale, R.G.; Kumar, B.; Khare, M.; Yadav, R.; Khattar, R.; Samal, S.K. Flood Forecasting in Large River Basins Using FOSS Tool and HPC. Water 2021, 13, 3484. https://doi.org/10.3390/w13243484

AMA Style

Dutta U, Singh YK, Prabhu TSM, Yendargaye G, Kale RG, Kumar B, Khare M, Yadav R, Khattar R, Samal SK. Flood Forecasting in Large River Basins Using FOSS Tool and HPC. Water. 2021; 13(24):3484. https://doi.org/10.3390/w13243484

Chicago/Turabian Style

Dutta, Upasana, Yogesh K. Singh, T. S.M. Prabhu, Girishchandra Yendargaye, Rohini G. Kale, Binay Kumar, Manoj Khare, Rahul Yadav, Ritesh Khattar, and Sushant K. Samal. 2021. "Flood Forecasting in Large River Basins Using FOSS Tool and HPC" Water 13, no. 24: 3484. https://doi.org/10.3390/w13243484

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