Articles | Volume 22, issue 12 
            
                
                    
                    
                        
            
            
            https://doi.org/10.5194/nhess-22-3859-2022
                    © Author(s) 2022. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Special issue:
                        
                    https://doi.org/10.5194/nhess-22-3859-2022
                    © Author(s) 2022. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Comparison of machine learning techniques for reservoir outflow forecasting
                                            Centro de Investigación Mariña, Universidade de Vigo,
Environmental Physics Laboratory (CIM-EPhysLab),  Campus Auga, 32004 Ourense, Spain
                                        
                                    
                                            Water and Environmental Engineering Group, Department of Civil
Engineering,  Universidade da Coruña, 15071 A Coruña, Spain
                                        
                                    José González-Cao
                                            Centro de Investigación Mariña, Universidade de Vigo,
Environmental Physics Laboratory (CIM-EPhysLab),  Campus Auga, 32004 Ourense, Spain
                                        
                                    Diego Fernández-Nóvoa
                                            Centro de Investigación Mariña, Universidade de Vigo,
Environmental Physics Laboratory (CIM-EPhysLab),  Campus Auga, 32004 Ourense, Spain
                                        
                                    
                                            Instituto Dom Luiz (IDL), Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisbon, Portugal
                                        
                                    Gonzalo Astray Dopazo
                                            Departamento de Química Física, Facultade de Ciencias, Universidade de Vigo, 32004 Ourense, Spain
                                        
                                    Moncho Gómez-Gesteira
                                            Centro de Investigación Mariña, Universidade de Vigo,
Environmental Physics Laboratory (CIM-EPhysLab),  Campus Auga, 32004 Ourense, Spain
                                        
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 - Neural network approach for modeling future natural river flows: Assessing climate change impacts on the Tagus River D. Fernández-Nóvoa et al. 10.1016/j.ejrh.2025.102191
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 - Forecasting hydrologic controls on juvenile anadromous fish out-migration with process-based modeling and machine learning K. King et al. 10.1016/j.jenvman.2023.118420
 - Assessment of Different Machine Learning Methods for Reservoir Outflow Forecasting A. Soria-Lopez et al. 10.3390/w15193380
 - Machine Learning-Based Water Level Forecast in a Dam Reservoir: A Case Study of Karaçomak Dam in the Kızılırmak Basin, Türkiye S. Güneş Şen 10.3390/su17188378
 - Analysis of reservoir outflow using deep learning model S. Choudhary & S. Ghosh 10.1007/s40808-023-01803-5
 - Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling D. Fernández-Nóvoa et al. 10.3390/w16101408
 - Optimization of Offshore Saline Aquifer CO2 Storage in Smeaheia Using Surrogate Reservoir Models B. Amiri et al. 10.3390/a17100452
 - A knowledge-guided LSTM reservoir outflow model and its application to streamflow simulation in reservoir-regulated basins R. Chen et al. 10.1016/j.jhydrol.2025.133164
 - Reservoir outflow prediction using adaptive neuro-fuzzy interference system A. Tatavarthi et al. 10.1007/s13198-024-02602-6
 - Incorporating multi-timescale data into a single long short-term memory network to enhance reservoir-regulated streamflow simulation L. Lang et al. 10.1016/j.jhydrol.2025.132806
 - Modeling the total outflow of reservoirs using Wavelet-developed approaches: a case study of the Mahabad Dam reservoir, Iran A. Emadi et al. 10.2166/ws.2023.291
 - Intersection of Hydrologic Change and Hydropower in the United States: Needs for Future Research and Practice E. Hester et al. 10.1111/1752-1688.70020
 - Enhanced reservoir outflow prediction using STL-Informer model: a decomposition–prediction–reconstruction framework Z. Zhou et al. 10.2166/hydro.2025.088
 - From Indices to Algorithms: A Hybrid Framework of Water Quality Assessment Using WQI and Machine Learning Under WHO and FAO Standards S. Güneş Şen 10.3390/w17213050
 - A comprehensive analysis of reservoir capacity loss: A case study of the Akhangaran reservoir, Uzbekistan K. Khasanov 10.1016/j.watcyc.2024.11.003
 - A New Machine Learning Algorithm to Simulate the Outlet Flow in a Reservoir, Based on a Water Balance Model M. Cordero Mancilla et al. 10.3390/limnolrev25030029
 - An energy prediction approach using bi-directional long short-term memory for a hydropower plant in Laos S. Kaewarsa & V. Kongpaseuth 10.1007/s00202-023-02096-8
 
18 citations as recorded by crossref.
- Machine Learning for Flood Resiliency—Current Status and Unexplored Directions V. Uddameri & E. Hernandez 10.3390/environments12080259
 - Neural network approach for modeling future natural river flows: Assessing climate change impacts on the Tagus River D. Fernández-Nóvoa et al. 10.1016/j.ejrh.2025.102191
 - A Mamba-type of deep state space model for reservoir release simulation with a large-scale verification over 441 dams across CONUS J. Zhang et al. 10.1016/j.jhydrol.2025.134145
 - Forecasting hydrologic controls on juvenile anadromous fish out-migration with process-based modeling and machine learning K. King et al. 10.1016/j.jenvman.2023.118420
 - Assessment of Different Machine Learning Methods for Reservoir Outflow Forecasting A. Soria-Lopez et al. 10.3390/w15193380
 - Machine Learning-Based Water Level Forecast in a Dam Reservoir: A Case Study of Karaçomak Dam in the Kızılırmak Basin, Türkiye S. Güneş Şen 10.3390/su17188378
 - Analysis of reservoir outflow using deep learning model S. Choudhary & S. Ghosh 10.1007/s40808-023-01803-5
 - Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling D. Fernández-Nóvoa et al. 10.3390/w16101408
 - Optimization of Offshore Saline Aquifer CO2 Storage in Smeaheia Using Surrogate Reservoir Models B. Amiri et al. 10.3390/a17100452
 - A knowledge-guided LSTM reservoir outflow model and its application to streamflow simulation in reservoir-regulated basins R. Chen et al. 10.1016/j.jhydrol.2025.133164
 - Reservoir outflow prediction using adaptive neuro-fuzzy interference system A. Tatavarthi et al. 10.1007/s13198-024-02602-6
 - Incorporating multi-timescale data into a single long short-term memory network to enhance reservoir-regulated streamflow simulation L. Lang et al. 10.1016/j.jhydrol.2025.132806
 - Modeling the total outflow of reservoirs using Wavelet-developed approaches: a case study of the Mahabad Dam reservoir, Iran A. Emadi et al. 10.2166/ws.2023.291
 - Intersection of Hydrologic Change and Hydropower in the United States: Needs for Future Research and Practice E. Hester et al. 10.1111/1752-1688.70020
 - Enhanced reservoir outflow prediction using STL-Informer model: a decomposition–prediction–reconstruction framework Z. Zhou et al. 10.2166/hydro.2025.088
 - From Indices to Algorithms: A Hybrid Framework of Water Quality Assessment Using WQI and Machine Learning Under WHO and FAO Standards S. Güneş Şen 10.3390/w17213050
 - A comprehensive analysis of reservoir capacity loss: A case study of the Akhangaran reservoir, Uzbekistan K. Khasanov 10.1016/j.watcyc.2024.11.003
 - A New Machine Learning Algorithm to Simulate the Outlet Flow in a Reservoir, Based on a Water Balance Model M. Cordero Mancilla et al. 10.3390/limnolrev25030029
 
Latest update: 03 Nov 2025
Short summary
                    Extreme events have increased in the last few decades; having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. This study analyzes the efficiency of different machine learning techniques to predict reservoir outflow. The results obtained showed that the proposed models provided a good estimation of the outflow of the reservoirs, improving the results obtained with classical approaches.
                    Extreme events have increased in the last few decades; having a good estimation of the outflow...
                    
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