Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Rabin Chakrabortty, Subodh Chandra Pal (), Saeid Janizadeh, M. Santosh, Paramita Roy, Indrajit Chowdhuri and Asish Saha
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Rabin Chakrabortty: The University of Burdwan
Subodh Chandra Pal: The University of Burdwan
Saeid Janizadeh: Tarbiat Modares University
M. Santosh: China University of Geosciences Beijing
Paramita Roy: The University of Burdwan
Indrajit Chowdhuri: The University of Burdwan
Asish Saha: The University of Burdwan

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 12, No 19, 4274 pages

Abstract: Abstract Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

Keywords: Analytical neural network; Deep learning neural network; Deep boost; General circulation model (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11269-021-02944-x

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