Zohreh Sheikh KhozaniMir Jafar Sadegh SafariAli Danandeh MehrWan Hanna Melini Wan Mohtar2025-10-062020002216940022-169410.1016/j.jhydrol.2020.124753https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079870720&doi=10.1016%2Fj.jhydrol.2020.124753&partnerID=40&md5=71fe816784263b0d6637450d52f8bd1ahttps://gcris.yasar.edu.tr/handle/123456789/9218Assimilating unique features of genetic programming (GP) and gene expression programming (GEP) this study introduces a hybrid algorithm which results in promising incipient non-cohesive sediment motion models. The new models use the dimensionless input parameters including relative particle size relative deposited bed thickness channel friction factor and channel bed slope to estimate particle Froude number in rectangular channels. The models’ accuracy is tested using different error measures and cross-validated through comparison with that of five empirical models available in the relevant literature. The results showed enhanced accuracy of the proposed models in comparison to the existing ones with concordance correlation coefficient of 0.92 and 0.94 for parsimonious and quasi-parsimonious ensemble GP models respectively. Such superiority is attributed to the integrated use of flow fluid sediment and channel characteristics in the modeling of incipient motion. Although the new algorithm is hybrid the proposed models are explicit and precise and thus motivating to be used in practice. © 2020 Elsevier B.V. All rights reserved.EnglishEmpirical Equations, Genetic Programming, Incipient Sediment Motion, Rectangular Channels, Sediment Bed Thickness, Gene Expression, Genetic Algorithms, Particle Size, Sediments, Channel Characteristics, Cohesive Sediments, Correlation Coefficient, Empirical Equations, Gene Expression Programming, Hybrid Algorithms, Rectangular Channel, Sediment Motion, Genetic ProgrammingGene expression, Genetic algorithms, Particle size, Sediments, Channel characteristics, Cohesive sediments, Correlation coefficient, Empirical equations, Gene expression programming, Hybrid algorithms, Rectangular channel, Sediment motion, Genetic programmingArticle