An artificial neural network-hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

Article


Bhattarai, Roshika, Bhattarai, Utsav, Pandey, Vishnu Prasad and Bhattarai, Pawan Kumar. 2022. "An artificial neural network-hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal." Journal of Flood Risk Management. 15 (4). https://doi.org/10.1111/jfr3.12852
Article Title

An artificial neural network-hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

ERA Journal ID41778
Article CategoryArticle
AuthorsBhattarai, Roshika, Bhattarai, Utsav, Pandey, Vishnu Prasad and Bhattarai, Pawan Kumar
Journal TitleJournal of Flood Risk Management
Journal Citation15 (4)
Article Numbere12852
Number of Pages19
Year2022
PublisherJohn Wiley & Sons
Place of PublicationUnited Kingdom
ISSN1753-318X
Digital Object Identifier (DOI)https://doi.org/10.1111/jfr3.12852
Web Address (URL)https://onlinelibrary.wiley.com/doi/10.1111/jfr3.12852
Abstract

Recurring floods have devastating consequences on the East Rapti Watershed (ERW), but effective mitigation/adaptation measures are lacking. This article aims at establishing a rainfall-runoff (RR) relationship; estimating depth and extent of inundation under climate change scenarios; assessing impacts on the socio-economy; and identifying and evaluating adaptation strategies in the ERW. Artificial Neural Network (ANN) was used to generate peak flows which were then entered into a hydraulic model to simulate inundation. Results were validated with field survey. The calibrated and validated RR and hydraulic models were fed with projected future climate (2021–2050) derived from multiple regional-climate-models to assess the changes in inundation. Results showed the peak discharge likely exceeds 10,500 m3/s at the ERW outlet in the extreme future flood scenario with corresponding inundation of 80 km2 and up to a depth of 11 m sweeping away over 1000 houses and 19 km2 of agricultural land in the critical areas. Constructing a 17 km long embankment in the critical areas along the right bank of the East Rapti River could reduce the flood spread by 35%, safeguarding 78% of the houses and saving 51% agricultural land compared with the scenarios without the embankment.

Keywordsadaptation strategies; HEC-RAS; flood modelling; East Rapti Watershed; climate change; ANN
ANZSRC Field of Research 2020410103. Human impacts of climate change and human adaptation
Byline AffiliationsTribhuvan University, Nepal
Water Modeling Solutions, Nepal
Institute for Life Sciences and the Environment
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