Abrahart, Robert J.

Practical Hydroinformatics

Abrahart, Robert J. - Practical Hydroinformatics, ebook


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ISBN: 9783540798811
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Table of contents

Part I.Hydroinformatics: Integrating Data and Models
1. Some Future Prospects in Hydroinformatics
2. Data-Driven Modelling: Concepts, Approaches and Experiences
Part II.Artificial Neural Network Models
3. Neural Network Hydroinformatics: Maintaining Scientific Rigour
4. Neural Network Solutions to Flood Estimation at Ungauged Sites
5. Rainfall-Runoff Modelling: Integrating Available Data and Modern Techniques
6. Dynamic Neural Networks for Nonstationary Hydrological Time Series Modeling
7. Visualisation of Hidden Neuron Behaviour in a Neural Network Rainfall-Runoff Model
8. Correction of Timing Errors of Artificial Neural Network Rainfall-Runoff Models
9. Data-Driven Streamflow Simulation: The Influence of Exogenous Variables and Temporal Resolution
10. Groundwater Table Estimation Using MODFLOW and Artificial Neural Networks
11. Neural Network Estimation of Suspended Sediment: Potential Pitfalls and Future Directions
Part III.Models Based on Fuzzy Logic
12. Fuzzy Logic-Based Approaches in Water Resource System Modelling
13. Fuzzy Rule-Based Flood Forecasting
14. Development of Rainfall–Runoff Models Using Mamdani-Type Fuzzy Inference Systems
15. Using an Adaptive Neuro-fuzzy Inference System in the Development of a Real-Time Expert System for Flood Forecasting
16. Building Decision Support Systems based on Fuzzy Inference
Part IV.Global and Evolutionary Optimization
17. Global and Evolutionary Optimization for Water Management Problems
18. Conditional Estimation of Distributed Hydraulic Conductivity in Groundwater Inverse Modeling: Indicator-Generalized Parameterization and Natural Neighbors
19. Fitting Hydrological Models on Multiple Responses Using the Multiobjective Evolutionary Annealing-Simplex Approach
20. Evolutionary-based Meta-modelling: The Relevance of Using Approximate Models in Hydroinformatics
21. Hydrologic Model Calibration Using Evolutionary Optimisation
22. Randomised Search Optimisation Algorithms and Their Application in the Rehabilitation of Urban Drainage Systems
23. Neural Network Hydrological Modelling: An Evolutionary Approach
Part V.Emerging Technologies
24. Combining Machine Learning and Domain Knowledge in Modular Modelling
25. Precipitation Interception Modelling Using Machine Learning Methods – The Dragonja River Basin Case Study
26. Real-Time Flood Stage Forecasting Using Support Vector Regression
27. Learning Bayesian Networks from Deterministic Rainfall–Runoff Models and Monte Carlo Simulation
28. Toward Bridging the Gap Between Data-Driven and Mechanistic Models: Cluster-Based Neural Networks for Hydrologic Processes
29. Applications of Soft Computing to Environmental Hydroinformatics with Emphasis on Ecohydraulics Modelling
30. Data-Driven Models for Projecting Ocean Temperature Profile from Sea Surface Temperature
Part VI.Model Integration
31. Uncertainty Propagation in Ensemble Rainfall Prediction Systems used for Operational Real-Time Flood Forecasting
32. OpenMI – Real Progress Towards Integrated Modelling
33. Hydroinformatics – The Challenge for Curriculum and Research, and the “Social Calibration” of Models
34. A New Systems Approach to Flood Management in the Yangtze River, China
35. Open Model Integration in Flood Forecasting


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Keywords: SCIENCE / Earth Sciences / General SCI019000

Publication year
Natural Sciences

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