Article
Engineering, Civil
Laxmipriya Mohanty, Prashant Istalkar, Basudev Biswal
Summary: Understanding and modeling the dynamics of suspended sediment concentration (C) in river channels is crucial. The sediment rating curve that relates C with river discharge (Q) is a widely used approach due to its simplicity and effectiveness. However, the relationship between C and Q is not unique and changes over time. This study analyzes recession periods and proposes a model that can predict future suspended sediment concentration based on past data. The results emphasize the importance of recognizing the dynamic nature of the C-Q relationship.
JOURNAL OF HYDROLOGY
(2023)
Article
Green & Sustainable Science & Technology
Tarate Suryakant Bajirao, Pravendra Kumar, Manish Kumar, Ahmed Elbeltagi, Alban Kuriqi
Summary: This study analyzed the validity of simple and wavelet-coupled Artificial Intelligence models for daily Suspended Sediment estimation in the Koyna River basin of India. The results showed that data pre-processing using wavelet transform significantly improves the model's predictive efficiency and reliability, with the Coiflet wavelet-coupled ANFIS model performing the best. Sensitivity analysis revealed the importance of the previous one-day SSC as the most crucial input variable for daily SSC estimation in the Koyna River basin.
Article
Environmental Sciences
Jenq-Tzong Shiau, Yu-Cheng Lien
Summary: This study proposes a parsimonious probabilistic model based on copulas to infill sediment data scarcity issues in river basins of Taiwan. By constructing a copula-based bivariate distribution model and using conditional distributions, the study provides probabilistic estimations of sediment loads. The outcomes of the proposed approach are compared with traditional sediment rating curve methods and evaluated based on performance metrics, showing different strengths in terms of accuracy and behavior preservation.
Article
Geochemistry & Geophysics
Temel Temiz, Osman Sonmez, Emrah Dogan, Adnan Oner, Mucahit Opan
Summary: This study analyzed the change of land use and lake area in a natural water source basin subjected to human pressure and found significant destruction of natural vegetation and a 2% reduction in the lake surface area. Sediment prediction models were developed using measurement data, and the artificial neural networks (ANN) model achieved the closest results.
Article
Environmental Sciences
Kezhen Wang, Scott Steinschneider
Summary: This study explores multi-scale variability in the relationship between turbidity and flow across 162 watersheds in the United States. The findings show significant differences in the T-n-Q relationship between different regions, and conducting a geographical feature analysis can help understand the reasons behind the numerical fluctuations.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Haniyeh Asadi, Mohammad T. Dastorani, Roy C. Sidle, Kaka Shahedi
Summary: This study optimized suspended sediment load (SSL) transport information using two main approaches, with findings showing that metaheuristic algorithms improved the performance of the sediment rating curve (SRC) model, particularly with the particle swarm optimization (PSO) model outperforming others. Additionally, the temporal separation of data was found to be directly related to model performance.
Article
Environmental Sciences
Khabat Khosravi, Ali Golkarian, Patricia M. Saco, Martijn J. Booij, Assefa M. Melesse
Summary: This study applied three widely used modeling approaches to predict suspended sediment load at the Talar watershed in Iran and evaluated their performance. The random forest model showed the best prediction power in the training phase, while the dagging-RF hybrid algorithm outperformed all other models in the validation phase.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Arvind Yadav, Premkumar Chithaluru, Aman Singh, Devendra Joshi, Dalia H. Elkamchouchi, Cristina Mazas Perez-Oleaga, Divya Anand
Summary: Estimation of suspended sediment yield (SSY) is essential for river basin management, and a developed artificial neural network (ANN) model showed superior accuracy and generalizability for SSY prediction in the Mahanadi River basin.
Article
Water Resources
Siyamak Doroudi, Ahmad Sharafati, Seyed Hossein Mohajeri
Summary: This study proposes a prediction model for suspended sediment load using support vector regression models, particle swarm optimization, and grey wolf optimization algorithms. The predictors used in the model are the Satellite Precipitation of Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Global Land Data Assimilation System (GLDAS) soil moisture products. The model is evaluated based on visual and quantitative indicators, with results showing that the support vector regression-particle swarm optimization model performs the best among the models tested in this study. The best indices obtained are: Pearson correlation coefficient of 0.997, relative root mean square error of 13.17, percentage bias of 4.05, and Nash-Sutcliffe efficiency of 0.995.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Water Resources
Chien Pham Van, Hien Le, Le Van Chin
Summary: This study introduces three methods, including the sediment rating curve, multiple regression, and long short-term memory model, for estimating daily suspended sediment concentration. The results show that these methods can effectively reproduce the observed values, with the LSTM model performing the best.
JOURNAL OF WATER AND CLIMATE CHANGE
(2023)
Article
Environmental Sciences
Anna Maria De Girolamo, Giovanni Francesco Ricci, Ossama M. M. Abdelwahab, Antonio Lo Porto, Fabio Milillo, Addolorata Maria Netti, Francesco Gentile
Summary: This study quantified suspended sediment loads in two mountainous river basins. The findings revealed that over 80% of the sediment load was transported during high-flow conditions, while less than 1% was transported during low-flow conditions.
Article
Engineering, Civil
Shicheng Li, Qiancheng Xie, James Yang
Summary: This study establishes a new hybrid model for improved forecast of suspended sediment concentration, utilizing wavelet transformation and multigene genetic programming. The model outperforms conventional methods, showing significant improvements in coefficient of determination and root mean squared error. The framework is robust for real-time and multistep SSC forecasts, providing valuable reference for time series modeling in various hydrological applications.
JOURNAL OF HYDROLOGY
(2022)
Article
Chemistry, Multidisciplinary
Muhammad Adnan Khan, Juergen Stamm, Sajjad Haider
Summary: The study compared different suspended sediment estimation methods in rivers and found that soft computing techniques (LLR, ANN, and WANN) outperformed the SRC method in predicting SSL, with WANN models being the most accurate.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Sciences
P. W. Downs, P. J. Soar
Summary: Understanding how river bedload responds to climate and land use changes and water resource management initiatives is critical in developing sustainable approaches to river management. The relative proportion of supply-related coarse bedload yield is strongly related to the wetness of the previous year. High-resolution, multiyear passive monitoring data can reveal unique controls on bedload dynamics specific to a site's hydrogeoclimatic context.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Nisreen G. Al-Ghorani, Marwan A. Hassan, Eddy J. Langendoen
Summary: This study utilized wavelet transforms to analyze the suspended sediment dynamics in Goodwin Creek watershed, revealing the varying impacts of land use and channel composition on sediment load and concentration. The results highlight the complex nature of sediment transport processes and the importance of considering multiple factors in watershed management strategies.
WATER RESOURCES RESEARCH
(2021)
Letter
Computer Science, Interdisciplinary Applications
Darren J. Beriro, Robert J. Abrahart, C. Paul Nathanail
COMPUTERS & GEOSCIENCES
(2013)
Editorial Material
Computer Science, Interdisciplinary Applications
Darren J. Beriro, Robert J. Abrahart, C. Paul Nathanail
COMPUTERS AND GEOTECHNICS
(2012)
Article
Computer Science, Interdisciplinary Applications
Darren J. Beriro, Robert J. Abrahart, C. Paul Nathanail, Jimmy Moreno, A. Salim Bawazir
ENVIRONMENTAL MODELLING & SOFTWARE
(2013)
Article
Water Resources
Nick J. Mount, Robert J. Abrahart, Christian W. Dawson, Ngahzaifa Ab Ghani
HYDROLOGICAL PROCESSES
(2012)
Article
Water Resources
Meng-Jung Tsai, Robert J. Abrahart, Nick J. Mount, Fi-John Chang
HYDROLOGICAL PROCESSES
(2014)
Editorial Material
Water Resources
Robert J. Abrahart, Nick J. Mount
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2011)
Article
Water Resources
Robert J. Abrahart, Nick J. Mount, Asaad Y. Shamseldin
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2012)
Article
Computer Science, Interdisciplinary Applications
E. Dominguez, C. W. Dawson, A. Ramirez, R. J. Abrahart
JOURNAL OF HYDROINFORMATICS
(2011)
Article
Computer Science, Interdisciplinary Applications
C. W. Dawson, N. J. Mount, R. J. Abrahart, J. Louis
JOURNAL OF HYDROINFORMATICS
(2014)
Editorial Material
Engineering, Civil
Robert J. Abrahart, Nick J. Mount, Asaad Y. Shamseldin
JOURNAL OF HYDROLOGY
(2012)
Article
Geography, Physical
Robert J. Abrahart, Francois Anctil, Paulin Coulibaly, Christian W. Dawson, Nick J. Mount, Linda M. See, Asaad Y. Shamseldin, Dimitri P. Solomatine, Elena Toth, Robert L. Wilby
PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT
(2012)
Letter
Engineering, Civil
Darren J. Beriro, Robert J. Abrahart, Nick J. Mount, C. Paul Nathanail
WATER RESOURCES MANAGEMENT
(2012)
Article
Geosciences, Multidisciplinary
N. J. Mount, C. W. Dawson, R. J. Abrahart
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2013)
Article
Geosciences, Multidisciplinary
C. W. Dawson, N. J. Mount, R. J. Abrahart, A. Y. Shamseldin
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2012)