Articles | Volume 13, issue 9
https://doi.org/10.5194/hess-13-1555-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-13-1555-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Classification of hydro-meteorological conditions and multiple artificial neural networks for streamflow forecasting
E. Toth
University of Bologna, Faculty of Engineering, viale Risorgimento 2, 40136 Bologna, Italy
Viewed
Total article views: 3,238 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 23 Feb 2009)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,453 | 1,578 | 207 | 3,238 | 132 | 106 |
- HTML: 1,453
- PDF: 1,578
- XML: 207
- Total: 3,238
- BibTeX: 132
- EndNote: 106
Total article views: 2,575 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 03 Sep 2009)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,205 | 1,183 | 187 | 2,575 | 120 | 97 |
- HTML: 1,205
- PDF: 1,183
- XML: 187
- Total: 2,575
- BibTeX: 120
- EndNote: 97
Total article views: 663 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013, article published on 23 Feb 2009)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
248 | 395 | 20 | 663 | 12 | 9 |
- HTML: 248
- PDF: 395
- XML: 20
- Total: 663
- BibTeX: 12
- EndNote: 9
Cited
51 citations as recorded by crossref.
- Multi-objective groundwater management strategy under uncertainties for sustainable control of saltwater intrusion: Solution for an island country in the South Pacific A. Lal & B. Datta 10.1016/j.jenvman.2018.12.054
- Regional monthly runoff forecast in southern Canada using ANN, K-means, and L-moments techniques C. Escalante-Sandoval & L. Amores-Rovelo 10.1080/07011784.2017.1290552
- Univariate streamflow forecasting using commonly used data-driven models: literature review and case study Z. Zhang et al. 10.1080/02626667.2018.1469756
- Investigation of quantitative and qualitative changes in groundwater of Ardebil plain using ensemble artificial intelligence-based modeling A. Sarreshtedar et al. 10.2166/ws.2022.273
- Improving Daily Streamflow Forecasting Using Deep Belief Net-Work Based on Flow Regime Recognition J. Shen et al. 10.3390/w14142241
- Diagnostic evaluation of conceptual rainfall–runoff models using temporal clustering N. de Vos et al. 10.1002/hyp.7698
- A self-organizing radial basis network for estimating riverine fish diversity F. Chang et al. 10.1016/j.jhydrol.2012.10.038
- A classification-based deep belief networks model framework for daily streamflow forecasting H. Chu et al. 10.1016/j.jhydrol.2021.125967
- A progressive segmented optimization algorithm for calibrating time-variant parameters of the snowmelt runoff model (SRM) S. Xie et al. 10.1016/j.jhydrol.2018.09.030
- Tools for enhancing the application of self-organizing maps in water resources research and engineering S. Clark et al. 10.1016/j.advwatres.2020.103676
- Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China L. Liu et al. 10.1016/j.jhydrol.2017.08.032
- Exploration on hydrological model calibration by considering the hydro-meteorological variability B. Zhao et al. 10.2166/nh.2019.047
- Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting R. Abrahart et al. 10.1177/0309133312444943
- Catchment classification based on characterisation of streamflow and precipitation time series E. Toth 10.5194/hess-17-1149-2013
- A comparative study of artificial intelligence and conventional techniques for rainfall-runoff modeling V. SINGH et al. 10.15740/HAS/IJAE/10.2/441-449
- Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks Y. Chiang et al. 10.5194/hess-15-185-2011
- Evaluation of Machine Learning Techniques for Inflow Prediction in Lake Como, Italy M. Pini et al. 10.1016/j.procs.2020.09.087
- How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance B. Guse et al. 10.1002/hyp.9777
- Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control F. Chang et al. 10.1016/j.jhydrol.2014.06.013
- Scenario-Based Real-Time Flood Prediction with Logistic Regression J. Lee & B. Kim 10.3390/w13091191
- A dimension range representation (DRR) measure for self-organizing maps S. Clark et al. 10.1016/j.patcog.2015.11.002
- Combination of geostatistics and self-organizing maps for the spatial analysis of groundwater level variations in complex hydrogeological systems E. Varouchakis et al. 10.1007/s00477-023-02436-x
- The flood prediction model using Artificial Neural Network (ANN) and weather Application Programming Interface (API) as an alternative effort to flood mitigation in the Jenelata Sub-watershed O. Gessang & U. Lasminto 10.1088/1757-899X/930/1/012080
- Regional Flood Frequency Analysis Using an Artificial Neural Network Model S. Kordrostami et al. 10.3390/geosciences10040127
- Neural network modeling of hydrological systems: A review of implementation techniques O. Oyebode & D. Stretch 10.1111/nrm.12189
- Improving short-term streamflow forecasting by flow mode clustering S. Liu et al. 10.1007/s00477-022-02367-z
- Prediction of Daily Streamflow Data Using Ensemble Learning Models L. Latifoğlu & Ü. Canpolat 10.56038/ejrnd.v2i4.218
- Data-driven catchment classification: application to the pub problem M. Di Prinzio et al. 10.5194/hess-15-1921-2011
- Identification of the controlling factors for hydrological responses by artificial neural networks R. Hao et al. 10.1002/hyp.14420
- Vector machine techniques for modeling of seismic liquefaction data P. Samui 10.1016/j.asej.2013.12.004
- Prediction of monthly regional groundwater levels through hybrid soft-computing techniques F. Chang et al. 10.1016/j.jhydrol.2016.08.006
- Machine Learning Models Coupled with Variational Mode Decomposition: A New Approach for Modeling Daily Rainfall-Runoff Y. Seo et al. 10.3390/atmos9070251
- Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites 10.5194/hess-14-1309-2010
- Neural network river forecasting through baseflow separation and binary-coded swarm optimization R. Taormina et al. 10.1016/j.jhydrol.2015.08.008
- Using self-organizing maps and wavelet transforms for space–time pre-processing of satellite precipitation and runoff data in neural network based rainfall–runoff modeling V. Nourani et al. 10.1016/j.jhydrol.2012.10.054
- Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan N. Mount et al. 10.1080/02626667.2016.1159683
- Hybrid of SOM-Clustering Method and Wavelet-ANFIS Approach to Model and Infill Missing Groundwater Level Data V. Nourani et al. 10.1061/(ASCE)HE.1943-5584.0001398
- AI techniques for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands W. Tsai et al. 10.1016/j.jhydrol.2015.10.024
- Reservoir operation optimization for balancing hydropower generation and biodiversity conservation in a downstream wetland C. Xu et al. 10.1016/j.jclepro.2019.118885
- Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering H. Zhang et al. 10.1016/j.advwatres.2011.06.005
- Improving real time flood forecasting using fuzzy inference system A. Lohani et al. 10.1016/j.jhydrol.2013.11.021
- Clustering flood events from water quality time series using Latent Dirichlet Allocation model A. Aubert et al. 10.1002/2013WR014086
- Establishing uncertainty ranges of hydrologic indices across climate and physiographic regions of the Congo River Basin P. Kabuya et al. 10.1016/j.ejrh.2020.100710
- Catchment classification by runoff behaviour with self-organizing maps (SOM) R. Ley et al. 10.5194/hess-15-2947-2011
- Identification of spatial and temporal contributions of rainfalls to flash floods using neural network modelling: case study on the Lez basin (southern France) T. Darras et al. 10.5194/hess-19-4397-2015
- An expert-knowledge-based algorithm for time-varying multi-objective coastal groundwater optimization Q. Sun et al. 10.1016/j.jhydrol.2022.128396
- Wavelet-entropy data pre-processing approach for ANN-based groundwater level modeling V. Nourani et al. 10.1016/j.jhydrol.2015.02.048
- Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests N. Kayastha et al. 10.5194/hess-17-4441-2013
- Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles A. Wunsch et al. 10.1007/s11269-021-03006-y
- Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin G. Corzo et al. 10.5194/hess-13-1619-2009
- Homogeneous region determination using linear and nonlinear techniques J. Swain et al. 10.1080/02723646.2016.1211460
47 citations as recorded by crossref.
- Multi-objective groundwater management strategy under uncertainties for sustainable control of saltwater intrusion: Solution for an island country in the South Pacific A. Lal & B. Datta 10.1016/j.jenvman.2018.12.054
- Regional monthly runoff forecast in southern Canada using ANN, K-means, and L-moments techniques C. Escalante-Sandoval & L. Amores-Rovelo 10.1080/07011784.2017.1290552
- Univariate streamflow forecasting using commonly used data-driven models: literature review and case study Z. Zhang et al. 10.1080/02626667.2018.1469756
- Investigation of quantitative and qualitative changes in groundwater of Ardebil plain using ensemble artificial intelligence-based modeling A. Sarreshtedar et al. 10.2166/ws.2022.273
- Improving Daily Streamflow Forecasting Using Deep Belief Net-Work Based on Flow Regime Recognition J. Shen et al. 10.3390/w14142241
- Diagnostic evaluation of conceptual rainfall–runoff models using temporal clustering N. de Vos et al. 10.1002/hyp.7698
- A self-organizing radial basis network for estimating riverine fish diversity F. Chang et al. 10.1016/j.jhydrol.2012.10.038
- A classification-based deep belief networks model framework for daily streamflow forecasting H. Chu et al. 10.1016/j.jhydrol.2021.125967
- A progressive segmented optimization algorithm for calibrating time-variant parameters of the snowmelt runoff model (SRM) S. Xie et al. 10.1016/j.jhydrol.2018.09.030
- Tools for enhancing the application of self-organizing maps in water resources research and engineering S. Clark et al. 10.1016/j.advwatres.2020.103676
- Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China L. Liu et al. 10.1016/j.jhydrol.2017.08.032
- Exploration on hydrological model calibration by considering the hydro-meteorological variability B. Zhao et al. 10.2166/nh.2019.047
- Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting R. Abrahart et al. 10.1177/0309133312444943
- Catchment classification based on characterisation of streamflow and precipitation time series E. Toth 10.5194/hess-17-1149-2013
- A comparative study of artificial intelligence and conventional techniques for rainfall-runoff modeling V. SINGH et al. 10.15740/HAS/IJAE/10.2/441-449
- Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks Y. Chiang et al. 10.5194/hess-15-185-2011
- Evaluation of Machine Learning Techniques for Inflow Prediction in Lake Como, Italy M. Pini et al. 10.1016/j.procs.2020.09.087
- How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance B. Guse et al. 10.1002/hyp.9777
- Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control F. Chang et al. 10.1016/j.jhydrol.2014.06.013
- Scenario-Based Real-Time Flood Prediction with Logistic Regression J. Lee & B. Kim 10.3390/w13091191
- A dimension range representation (DRR) measure for self-organizing maps S. Clark et al. 10.1016/j.patcog.2015.11.002
- Combination of geostatistics and self-organizing maps for the spatial analysis of groundwater level variations in complex hydrogeological systems E. Varouchakis et al. 10.1007/s00477-023-02436-x
- The flood prediction model using Artificial Neural Network (ANN) and weather Application Programming Interface (API) as an alternative effort to flood mitigation in the Jenelata Sub-watershed O. Gessang & U. Lasminto 10.1088/1757-899X/930/1/012080
- Regional Flood Frequency Analysis Using an Artificial Neural Network Model S. Kordrostami et al. 10.3390/geosciences10040127
- Neural network modeling of hydrological systems: A review of implementation techniques O. Oyebode & D. Stretch 10.1111/nrm.12189
- Improving short-term streamflow forecasting by flow mode clustering S. Liu et al. 10.1007/s00477-022-02367-z
- Prediction of Daily Streamflow Data Using Ensemble Learning Models L. Latifoğlu & Ü. Canpolat 10.56038/ejrnd.v2i4.218
- Data-driven catchment classification: application to the pub problem M. Di Prinzio et al. 10.5194/hess-15-1921-2011
- Identification of the controlling factors for hydrological responses by artificial neural networks R. Hao et al. 10.1002/hyp.14420
- Vector machine techniques for modeling of seismic liquefaction data P. Samui 10.1016/j.asej.2013.12.004
- Prediction of monthly regional groundwater levels through hybrid soft-computing techniques F. Chang et al. 10.1016/j.jhydrol.2016.08.006
- Machine Learning Models Coupled with Variational Mode Decomposition: A New Approach for Modeling Daily Rainfall-Runoff Y. Seo et al. 10.3390/atmos9070251
- Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites 10.5194/hess-14-1309-2010
- Neural network river forecasting through baseflow separation and binary-coded swarm optimization R. Taormina et al. 10.1016/j.jhydrol.2015.08.008
- Using self-organizing maps and wavelet transforms for space–time pre-processing of satellite precipitation and runoff data in neural network based rainfall–runoff modeling V. Nourani et al. 10.1016/j.jhydrol.2012.10.054
- Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan N. Mount et al. 10.1080/02626667.2016.1159683
- Hybrid of SOM-Clustering Method and Wavelet-ANFIS Approach to Model and Infill Missing Groundwater Level Data V. Nourani et al. 10.1061/(ASCE)HE.1943-5584.0001398
- AI techniques for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands W. Tsai et al. 10.1016/j.jhydrol.2015.10.024
- Reservoir operation optimization for balancing hydropower generation and biodiversity conservation in a downstream wetland C. Xu et al. 10.1016/j.jclepro.2019.118885
- Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering H. Zhang et al. 10.1016/j.advwatres.2011.06.005
- Improving real time flood forecasting using fuzzy inference system A. Lohani et al. 10.1016/j.jhydrol.2013.11.021
- Clustering flood events from water quality time series using Latent Dirichlet Allocation model A. Aubert et al. 10.1002/2013WR014086
- Establishing uncertainty ranges of hydrologic indices across climate and physiographic regions of the Congo River Basin P. Kabuya et al. 10.1016/j.ejrh.2020.100710
- Catchment classification by runoff behaviour with self-organizing maps (SOM) R. Ley et al. 10.5194/hess-15-2947-2011
- Identification of spatial and temporal contributions of rainfalls to flash floods using neural network modelling: case study on the Lez basin (southern France) T. Darras et al. 10.5194/hess-19-4397-2015
- An expert-knowledge-based algorithm for time-varying multi-objective coastal groundwater optimization Q. Sun et al. 10.1016/j.jhydrol.2022.128396
- Wavelet-entropy data pre-processing approach for ANN-based groundwater level modeling V. Nourani et al. 10.1016/j.jhydrol.2015.02.048
4 citations as recorded by crossref.
- Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests N. Kayastha et al. 10.5194/hess-17-4441-2013
- Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles A. Wunsch et al. 10.1007/s11269-021-03006-y
- Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin G. Corzo et al. 10.5194/hess-13-1619-2009
- Homogeneous region determination using linear and nonlinear techniques J. Swain et al. 10.1080/02723646.2016.1211460
Saved (preprint)
Latest update: 17 Sep 2024