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Advanced Hydroinformatics : Machine Learning and Optimization for Water Resources
Advanced Hydroinformatics : Machine Learning and Optimization for Water Resources
Autore Corzo Perez Gerald A
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : American Geophysical Union, , 2023
Descrizione fisica 1 online resource (478 pages)
Altri autori (Persone) SolomatineDimitri P
Collana Special Publications
ISBN 1-119-63926-3
1-119-63932-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Preface -- Chapter 1 Hydroinformatics and Applications of Artificial Intelligence and Machine Learning in Water‐Related Problems -- 1.1 Introduction -- 1.2 Key Principles of ML/Hydroinformatics -- 1.2.1 AI and ML Definitions -- 1.2.2 Machine Learning (ML) -- 1.2.3 Natural Language Processing (NLP) -- 1.2.4 Pattern (Image) Recognition -- 1.3 Model Building and Input Variable Selection in Machine Learning for Water‐related Problems -- 1.3.1 Data Partitioning -- 1.3.2 Input Variable Selection (IVS) (Feature Engineering) -- 1.3.3 Optimization -- 1.3.4 Model Evaluation (Testing) -- 1.3.5 Uncertainties in the Process of Building a Model -- 1.4 Advanced Techniques in Machine Learning for Water Resources Applications -- 1.4.1 Artificial Neural Networks (ANNs) -- 1.4.2 Regression and Model Trees -- 1.4.3 Bagging and Boosting Techniques for Building Committee Models -- 1.4.4 Deep Learning -- 1.4.5 Recurrent Neural Networks (RNNs) and LSTM -- 1.5 Future Directions and Challenges -- References -- Part I Modeling Hydrological Systems -- Chapter 2 Improving Model Identifiability by Driving Calibration With Stochastic Inputs -- 2.1 Introduction -- 2.2 Methodology -- 2.3 Insights to the Stochastic Simulation Procedure -- 2.4 Proof of Concept -- 2.4.1 Data and Model Description -- 2.4.2 Results -- 2.4.3 Parameter Uncertainty Analysis -- 2.5 Concluding Remarks -- Acknowledgments -- References -- Chapter 3 A Two‐Stage Surrogate‐Based Parameter Calibration Framework for a Complex Distributed Hydrological Model -- 3.1 Introduction -- 3.2 Method -- 3.2.1 Hydrologic Model and Its Calibration -- 3.2.2 Algorithm of Response Surface Surrogates -- 3.2.3 Surrogate Model for Model Calibration -- 3.3 Study Area and Data -- 3.4 Experimental Setup -- 3.5 Results.
3.5.1 Benchmark Test of the Surrogate Model -- 3.5.2 Pareto Solutions of the Surrogate Model in Two Study Areas -- 3.5.3 Evaluation of the Surrogate Model in Two Study Areas -- 3.5.4 Efficiency of the Surrogate Model in Two Study Areas -- 3.6 Discussion -- 3.7 Conclusions -- Acknowledgments -- References -- Chapter 4 Fuzzy Committees of Conceptual Distributed Model -- 4.1 Introduction -- 4.2 Case Study -- 4.3 Methodology -- 4.3.1 Model Structure Description -- 4.3.2 Model Calibration and Building Specialized Local Models -- 4.3.3 Combining Specialized Models -- 4.3.4 Model Setup -- 4.3.5 Evaluation Criteria -- 4.4 Results and Discussion -- Acknowledgments -- References -- Chapter 5 Regression‐Based Machine Learning Approaches for Daily Streamflow Modeling -- 5.1 Introduction -- 5.2 Materials and Methods -- 5.2.1 ML Models -- 5.2.2 Study Region and Data -- 5.3 Results -- 5.4 Conclusion and Future Works -- Acknowledgments -- References -- Chapter 6 Use of Near‐Real‐Time Satellite Precipitation Data and Machine Learning to Improve Extreme Runoff Modeling -- 6.1 Introduction -- 6.2 Study Area and Data Set -- 6.2.1 Study Area -- 6.2.2 Data Set -- 6.3 Methodology -- 6.3.1 Determination of Nearly Independent Peak Hydrological Events -- 6.3.2 Object‐Based Connected Component Analysis -- 6.3.3 Classification of Precipitation Events Associated With Extreme Hydrologic Events -- 6.3.4 Event‐Based Runoff Modeling -- 6.4 Results -- 6.4.1 Determination of Nearly Independent Peak Hydrological Events -- 6.4.2 Object‐Based Connected Component Analysis -- 6.4.3 Classification of Precipitation Events Associated With Extreme Hydrologic Events -- 6.4.4 Event‐Based Runoff Modeling -- 6.5 Discussion -- 6.6 Conclusions -- References -- Part II Forecasting Water Resources.
Chapter 7 Forecasting Water Levels Using Machine (Deep) Learning to Complement Numerical Modeling in the Southern Everglades, USA -- 7.1 Introduction -- 7.2 Methods -- 7.3 Workflow -- 7.3.1 Data Acquisition and Processing -- 7.4 Experimental Setup -- 7.4.1 Selecting Model Inputs and Data Preparation -- 7.5 Comparison of Measured Rainfall and NWP Rainfall Forecasts -- 7.5.1 Model Development -- 7.6 Results and Discussion -- 7.6.1 Performance of All Data‐Driven Models -- 7.6.2 Short‐Term Forecasts -- 7.6.3 Medium‐Range Forecasts -- 7.6.4 Comparison of the ML Model With the Numerical Model -- 7.7 Conclusions and Future Directions -- Disclaimer -- Appendix -- References -- Chapter 8 Application of a Multilayer Perceptron Artificial Neural Network (MLP‐ANN) in Hydrological Forecasting in El Salvador -- 8.1 Introduction -- 8.2 Data‐Driven Modeling Technique -- 8.2.1 Artificial Neural Network (ANN) Architecture -- 8.2.2 Data Partitioning -- 8.2.3 Choice of Model Input Variable -- 8.3 Characterization of The Grande De San Miguel Catchment -- 8.4 Methodology -- 8.4.1 Data Exploration -- 8.4.2 Input Variable Selection -- 8.4.3 Data Partitioning and Model Developing -- 8.5 Experimental Setups -- 8.5.1 Data Analysis for Input Variable Selection -- 8.5.2 Data Partitioning -- 8.6 Results and Discussion -- 8.7 Operational MLP‐ANN Forecast Model -- 8.8 Conclusions and Recommendations -- Acknowledgments -- References -- Chapter 9 Noise Filter With Wavelet Analysis in Artificial Neural Networks (NOWANN) for Flow Time Series Prediction -- 9.1 Introduction -- 9.2 Materials -- 9.2.1 Wavelet Transform -- 9.2.2 The Continuous Wavelet Transform (CWT) -- 9.2.3 The discrete wavelet transform (DWT) -- 9.2.4 The A‐trous Wavelet Transform -- 9.2.5 Artificial Neural Networks.
9.2.6 Other Data‐Driven Models: Least Median Square, Linear Regressions, Pace Regression, and Model Tree -- 9.3 Methodology -- 9.3.1 Sequence of Experiments -- 9.3.2 Input Variable Selection (IVS) -- 9.3.3 K‐Fold Cross‐Validation -- 9.3.4 Wavelet Decompositions as an Input Preprocessor of an Artificial Neural Network -- 9.3.5 Levels of Decompositions and ANN Structure as Decision Variables in an Optimization Routine -- 9.3.6 Wavelet Decompositions as an Input Preprocessor of Other Data‐Driven Models -- 9.3.7 The Noise Filtering Process in Wavelets Analysis -- 9.3.8 Error Metrics -- 9.4 Case Study -- 9.5 Results and Discussions -- 9.5.1 ANN Stand‐Alone Model -- 9.5.2 Wavelet ANN Model -- 9.5.3 De‐Noised Wavelet ANN Model -- 9.5.4 Other Data‐Driven Models: Least Median Square, Model Tree (M5P), Pace Regression, and Linear Regressions -- 9.6 Conclusions -- References -- Part III Knowledge Discovery and Optimization -- Chapter 10 Application of Natural Language Processing to Identify Extreme Hydrometeorological Events in Digital News Media: Case of the Magdalena River Basin, Colombia -- 10.1 Introduction -- 10.2 Case Study -- 10.3 Methodology -- 10.3.1 Step 1 (Digital Citizens' Search for Information Sources) -- 10.3.2 Step 2 (Water Bodies and Keywords) -- 10.3.3 Step 3 (Digital Citizens' Media Search) -- 10.3.4 Step 4 (Data Extraction and Preprocessing) -- 10.3.5 Step 5 (Text Vectorization-Tokenization) -- 10.3.6 Step 6 (NLP Analysis) -- 10.3.7 Step 7 (Sentiment Analysis) -- 10.3.8 Step 8 (Validation) -- 10.3.9 Step 9 (Geovisualization) -- 10.4 Results -- 10.4.1 Step 1 -- 10.4.2 Step 2 -- 10.4.3 Step 3 -- 10.4.4 Step 4 -- 10.4.5 Step 5 (Tokenization) -- 10.4.6 Step 6 (NLP Analysis) -- 10.4.7 Step 7 (Sentiment Analysis) -- 10.4.8 Step 8 (Validation) -- 10.4.9 Step 9 (Geovisualization) -- 10.5 Conclusions -- References.
Chapter 11 Three‐Dimensional Clustering in the Characterization of Spatiotemporal Drought Dynamics: Cluster Size Filter and Drought Indicator Threshold Optimization -- 11.1 Introduction -- 11.2 Methods and Data -- 11.2.1 Drought Calculation -- 11.2.2 Drought Characterization -- 11.2.3 Data -- 11.3 Results and Discussion -- 11.3.1 Drought Calculation -- 11.3.2 Drought Characterization -- 11.3.3 Comparison with the Reported Droughts -- 11.4 Summary and Conclusions -- Acknowledgments -- References -- Chapter 12 Deep Learning of Extreme Rainfall Patterns Using Enhanced Spatial Random Sampling With Pattern Recognition -- 12.1 Introduction -- 12.2 Toolbox -- 12.2.1 Spatial Random Sampling Toolbox for Grid‐Based Data Analysis (SRS‐GDA) -- 12.2.2 Pattern Recognition and Feature Extraction of Rainfall Data -- 12.3 Identify the Specific Patterns of Rainfall in Great Britain -- 12.4 Generating the Training Sets for Deep Learning Studies -- 12.5 Conclusion -- References -- Chapter 13 Teleconnection Patterns of River Water Quality Dynamics Based on Complex Network Analysis -- 13.1 Introduction -- 13.2 Study Areas and Methods -- 13.2.1 Study Areas and Monitoring Campaign -- 13.2.2 Monitoring Campaign and Data Processing -- 13.3 Theory of Complex Network -- 13.3.1 Concept of Network -- 13.3.2 Indexes of Complex Network -- 13.3.3 CNs‐Based Teleconnection Analysis -- 13.4 Results and Discussion -- 13.4.1 Teleconnection Pattern on Huaihe River Basin -- 13.4.2 Teleconnection Analysis on China's Major Rivers -- 13.5 Comparison of Teleconnection Features Between Scales and Parameters -- 13.6 Study Limitations and Future Works -- 13.7 Conclusion -- Acknowledgments -- References -- Chapter 14 Probabilistic Analysis of Flood Storage Areas Management in the Huai River Basin, China, With Robust Optimization and Similarity‐Based Selection for Real‐Time Operation.
14.1 Introduction.
Record Nr. UNINA-9910841647303321
Corzo Perez Gerald A  
Newark : , : American Geophysical Union, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alaskan Geological and Geophysical Transect
Alaskan Geological and Geophysical Transect
Autore Nokleberg Warren J.
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1989
Descrizione fisica 1 online resource (131 pages) : illustrations
Disciplina 557.98
Collana Field trip guidebook (International Geological Congress (28th : 1989 : Washington, D.C.)), T104
Soggetto topico Geology - Alaska
Geophysics - Alaska
ISBN 1-118-66736-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996214939503316
Nokleberg Warren J.  
[Place of publication not identified], : American Geophysical Union, 1989
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Alaskan Geological and Geophysical Transect
Alaskan Geological and Geophysical Transect
Autore Nokleberg Warren J.
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1989
Descrizione fisica 1 online resource (131 pages) : illustrations
Disciplina 557.98
Collana Field trip guidebook (International Geological Congress (28th : 1989 : Washington, D.C.)), T104
Soggetto topico Geology - Alaska
Geophysics - Alaska
ISBN 1-118-66736-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910830888103321
Nokleberg Warren J.  
[Place of publication not identified], : American Geophysical Union, 1989
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alaskan Geological and Geophysical Transect
Alaskan Geological and Geophysical Transect
Autore Nokleberg Warren J.
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1989
Descrizione fisica 1 online resource (131 pages) : illustrations
Disciplina 557.98
Collana Field trip guidebook (International Geological Congress (28th : 1989 : Washington, D.C.)), T104
Soggetto topico Geology - Alaska
Geophysics - Alaska
ISBN 1-118-66736-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910841039403321
Nokleberg Warren J.  
[Place of publication not identified], : American Geophysical Union, 1989
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alaskan Geological and Geophysical Transect
Alaskan Geological and Geophysical Transect
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1989
ISBN 1-118-66736-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910130755203321
[Place of publication not identified], : American Geophysical Union, 1989
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alpine-Mediterranean Geodynamics / Edited by H. Berckhemer, K. Hsu
Alpine-Mediterranean Geodynamics / Edited by H. Berckhemer, K. Hsu
Pubbl/distr/stampa Washington ; Boulder : American Geophysical Union : Geological Society of America, 1982
Descrizione fisica 216 p. ; 27 cm
Disciplina 550
Collana Geodynamics Series
Soggetto non controllato Geofisica
Terra
ISBN 0-87590-503-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-990001441440403321
Washington ; Boulder : American Geophysical Union : Geological Society of America, 1982
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alpine-Mediterranean Geodynamics
Alpine-Mediterranean Geodynamics
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1982
Disciplina 551/.09182/2
ISBN 1-118-67024-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910130940803321
[Place of publication not identified], : American Geophysical Union, 1982
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alpine-Mediterranean Geodynamics
Alpine-Mediterranean Geodynamics
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1982
Descrizione fisica 1 online resource (369 pages)
Disciplina 551/.09182/2
Soggetto topico Geodynamics
ISBN 1-118-67024-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996214930503316
[Place of publication not identified], : American Geophysical Union, 1982
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Alpine-Mediterranean Geodynamics
Alpine-Mediterranean Geodynamics
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1982
Descrizione fisica 1 online resource (369 pages)
Disciplina 551/.09182/2
Soggetto topico Geodynamics
ISBN 1-118-67024-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910830062903321
[Place of publication not identified], : American Geophysical Union, 1982
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alpine-Mediterranean Geodynamics
Alpine-Mediterranean Geodynamics
Pubbl/distr/stampa [Place of publication not identified], : American Geophysical Union, 1982
Descrizione fisica 1 online resource (369 pages)
Disciplina 551/.09182/2
Soggetto topico Geodynamics
ISBN 1-118-67024-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910840570603321
[Place of publication not identified], : American Geophysical Union, 1982
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui

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