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Geocarto International Volume 37, 2022 - Issue 27
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Research Articles

Model identification and accuracy for estimation of suspended sediment load

Khabat Khosravia Department of Earth and Environment, Florida International University, Miami, USACorrespondence[email protected] [email protected]
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,
Ali Golkarianb Department of Watershed Management Engineering, Ferdowsi University of Mashhad, Mashhad, IranView further author information
,
Patricia M. Sacoc Civil, Surveying and Environmental Engineering and Centre for Water Security and Environmental Sustainability, The University of Newcastle, AustraliaView further author information
,
Martijn J. Booijd Water Engineering and Management, Faculty of Engineering Technology, University of Twente, the NetherlandsORCID Iconhttps://orcid.org/0000-0001-6208-9045View further author information
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Assefa M. Melessea Department of Earth and Environment, Florida International University, Miami, USAORCID Iconhttps://orcid.org/0000-0003-4724-9367View further author information
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Pages 18520-18545 | Received 08 May 2022, Accepted 28 Oct 2022, Published online: 20 Nov 2022

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Read on this site (1)

Gebre Gelete, Vahid Nourani, Huseyin Gokcekus & Tagesse Gichamo. (2023) Physical and artificial intelligence-based hybrid models for rainfall–runoff–sediment process modelling. Hydrological Sciences Journal 68:13, pages 1841-1863.
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Articles from other publishers (1)

Majid Niazkar & Mohammad Zakwan. (2023) Developing ensemble models for estimating sediment loads for different times scales. Environment, Development and Sustainability.
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