Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-99-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-99-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
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05 Jan 2017
Research article | Highlight paper |
| 05 Jan 2017
A comprehensive one-dimensional numerical model for solute transport in rivers
Maryam Barati Moghaddam
Department of Water Structures, Tarbiat Modares University, Tehran,
Iran
Mehdi Mazaheri
CORRESPONDING AUTHOR
Department of Water Structures, Tarbiat Modares University, Tehran,
Iran
Jamal MohammadVali Samani
Department of Water Structures, Tarbiat Modares University, Tehran,
Iran
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Cited
21 citations as recorded by crossref.
- Inverse modeling of contaminant transport for pollution source identification in surface and groundwaters: a review M. Barati Moghaddam et al. https://doi.org/10.1016/j.gsd.2021.100651
- An embedded VPMM-AD model for riverine transient flow and non-reactive contaminant transports R. Swain et al. https://doi.org/10.1016/j.jhydrol.2018.06.025
- Modelling of heavy metals transport along the Lom River in the mining site of Gankombol (Adamawa Cameroon) M. Ayiwouo et al. https://doi.org/10.1007/s13762-021-03889-9
- A general Lagrangian tracking methodology for riverine flow and transport J. Nelson et al. https://doi.org/10.1002/esp.5458
- Development of A 2D Numerical Model for Pollutant Transport using FTCS Scheme and Numerical Filter https://doi.org/10.7454/mst.v25i3.3966
- An Experimental Investigation of the Hydraulics and Pollutant Dispersion Characteristics of a Model Beaver Dam J. Hart et al. https://doi.org/10.3390/w12092320
- A Review on Storage Process Models for Improving Water Quality Modeling in Rivers A. Saadat et al. https://doi.org/10.3390/hydrology11110187
- A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels M. Najafzadeh et al. https://doi.org/10.1016/j.jhydrol.2021.126850
- Investigation of river water pollution using Muskingum method and particle swarm optimization (PSO) algorithm H. Norouzi & J. Bazargan https://doi.org/10.1007/s13201-024-02127-0
- Climate change projections and hydrological modelling to predict the streamflow in Berach-Banas catchment, Rajasthan K. Pareta & Y. Dashora https://doi.org/10.1007/s43832-025-00208-y
- Evaluation of the Accuracy of Methods for Estimating the Longitudinal Dispersion Coefficient in Natural Rivers Using a Field Study A. Bashiri et al. https://doi.org/10.1007/s41742-025-00793-9
- Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis S. Kwon et al. https://doi.org/10.3390/ijerph18031023
- Solving the Master Equation on river networks: A computer algebra approach S. De Bartolo et al. https://doi.org/10.1016/j.envsoft.2024.106288
- Modeling One-Dimensional Nonreactive Solute Transport in Open Channel Flows Under Uncertain Flow and Solute Loading Conditions T. Tu et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001957
- New coefficient for water quality modelling in meandering rivers: Fatigue Factor S. Hashemi Monfared et al. https://doi.org/10.1016/j.ecoinf.2023.101999
- Analytical solution of two-dimensional conservative solute transport in a heterogeneous porous medium for varying input point source R. Yadav & L. Kumar https://doi.org/10.1007/s12665-021-09584-9
- A comprehensive assessment and comparison of the impacts of storage parameters on solute transport in streams using a novel framework S. Khodambashi Emami & M. Mazaheri https://doi.org/10.1016/j.jhydrol.2024.130873
- Quantifying the Impact of Uncertainty within the Longitudinal Dispersion Coefficient on Concentration Dynamics and Regulatory Compliance in Rivers V. Camacho Suarez et al. https://doi.org/10.1029/2018WR023417
- Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streams B. Ghiasi et al. https://doi.org/10.1038/s41598-022-08417-4
- Application of the QUAL2K model for assessing water quality in the anthropogenically impacted Dil Stream, Turkey M. Yağcıoğlu & M. Öncel https://doi.org/10.1038/s41598-026-56761-6
- Experimental and numerical study of bed roughness effect on longitudinal dispersion M. Nasrabadi et al. https://doi.org/10.2166/ws.2021.274
21 citations as recorded by crossref.
- Inverse modeling of contaminant transport for pollution source identification in surface and groundwaters: a review M. Barati Moghaddam et al. https://doi.org/10.1016/j.gsd.2021.100651
- An embedded VPMM-AD model for riverine transient flow and non-reactive contaminant transports R. Swain et al. https://doi.org/10.1016/j.jhydrol.2018.06.025
- Modelling of heavy metals transport along the Lom River in the mining site of Gankombol (Adamawa Cameroon) M. Ayiwouo et al. https://doi.org/10.1007/s13762-021-03889-9
- A general Lagrangian tracking methodology for riverine flow and transport J. Nelson et al. https://doi.org/10.1002/esp.5458
- Development of A 2D Numerical Model for Pollutant Transport using FTCS Scheme and Numerical Filter https://doi.org/10.7454/mst.v25i3.3966
- An Experimental Investigation of the Hydraulics and Pollutant Dispersion Characteristics of a Model Beaver Dam J. Hart et al. https://doi.org/10.3390/w12092320
- A Review on Storage Process Models for Improving Water Quality Modeling in Rivers A. Saadat et al. https://doi.org/10.3390/hydrology11110187
- A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels M. Najafzadeh et al. https://doi.org/10.1016/j.jhydrol.2021.126850
- Investigation of river water pollution using Muskingum method and particle swarm optimization (PSO) algorithm H. Norouzi & J. Bazargan https://doi.org/10.1007/s13201-024-02127-0
- Climate change projections and hydrological modelling to predict the streamflow in Berach-Banas catchment, Rajasthan K. Pareta & Y. Dashora https://doi.org/10.1007/s43832-025-00208-y
- Evaluation of the Accuracy of Methods for Estimating the Longitudinal Dispersion Coefficient in Natural Rivers Using a Field Study A. Bashiri et al. https://doi.org/10.1007/s41742-025-00793-9
- Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis S. Kwon et al. https://doi.org/10.3390/ijerph18031023
- Solving the Master Equation on river networks: A computer algebra approach S. De Bartolo et al. https://doi.org/10.1016/j.envsoft.2024.106288
- Modeling One-Dimensional Nonreactive Solute Transport in Open Channel Flows Under Uncertain Flow and Solute Loading Conditions T. Tu et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001957
- New coefficient for water quality modelling in meandering rivers: Fatigue Factor S. Hashemi Monfared et al. https://doi.org/10.1016/j.ecoinf.2023.101999
- Analytical solution of two-dimensional conservative solute transport in a heterogeneous porous medium for varying input point source R. Yadav & L. Kumar https://doi.org/10.1007/s12665-021-09584-9
- A comprehensive assessment and comparison of the impacts of storage parameters on solute transport in streams using a novel framework S. Khodambashi Emami & M. Mazaheri https://doi.org/10.1016/j.jhydrol.2024.130873
- Quantifying the Impact of Uncertainty within the Longitudinal Dispersion Coefficient on Concentration Dynamics and Regulatory Compliance in Rivers V. Camacho Suarez et al. https://doi.org/10.1029/2018WR023417
- Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streams B. Ghiasi et al. https://doi.org/10.1038/s41598-022-08417-4
- Application of the QUAL2K model for assessing water quality in the anthropogenically impacted Dil Stream, Turkey M. Yağcıoğlu & M. Öncel https://doi.org/10.1038/s41598-026-56761-6
- Experimental and numerical study of bed roughness effect on longitudinal dispersion M. Nasrabadi et al. https://doi.org/10.2166/ws.2021.274
Saved (final revised paper)
Latest update: 28 Oct 2026
Short summary
In this study a comprehensive model was developed that combines numerical schemes with high-order accuracy for solution of the advection–dispersion equation considering transient storage zones term in rivers. In developing the subjected model (TOASTS), for achieving better accuracy and applicability, irregular-cross sections and unsteady flow regime were considered. For this purpose the QUICK scheme due to its high stability and low approximation error has been used for spatial discretization.
In this study a comprehensive model was developed that combines numerical schemes with...
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