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Water surface profile in converging compound channel using gene expression programming
Author(s) -
Bandita Naik,
Vijay Kumar Kaushik,
Munendra Kumar
Publication year - 2022
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2022.172
Subject(s) - overbank , gene expression programming , floodplain , channel (broadcasting) , surface water , surface (topology) , hydrology (agriculture) , flow (mathematics) , convergence (economics) , mean squared error , water flow , mathematics , environmental science , statistics , geometry , algorithm , soil science , computer science , geology , geotechnical engineering , environmental engineering , artificial intelligence , geomorphology , ecology , telecommunications , biology , facies , structural basin , economic growth , economics
Assessment of water surface profile in compound channels is essential for flood defence systems. Agriculture and development activities in floodplains affect the floodplain shape over the length, leading in a converging compound channel. Few laboratory investigations proved overbank flow in converging floodplains. Therefore, innovative and precise approaches are still in great demand. In this paper, new approach has been proposed to forecast the water surface profile of various compound channels with converging floodplains using gene expression programming (GEP). The models are constructed utilising pertinent experimental data from past studies. A new equation is devised to compute water surface profile in such channels using non-dimensional geometric and flow parameters such as converging angle, width ratio, relative distance, relative depth, aspect ratio and bed slope. The findings demonstrate that the GEP-derived water surface profile is in good correlation with the experimental data and data from other studies (R2 = 0.99 and RMSE = 0.028 for the training data and R2 = 0.99 and RMSE = 0.027 for the testing data). According to the results of statistically based investigations, the GEP model created for the study of compound channel flow is reliable and can be used in this domain.

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