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PRACTICAL HYDROINFORMATICS Water Science and Technology Library PRACTICAL HYDROINFORMATICS Water Science and Technology Library VOLUME 68 Editor-in-Chief V.P. Singh, Texas A&M University, College Station, U.S.A. Editorial Advisory Board M. Anderson, Bristol, U.K. L. Bengtsson, Lund, Sweden J. F. Cruise, Huntsville, U.S.A. U. C. Kothyari, Roorkee, India S. E. Serrano, Philadelphia, U.S.A. D. Stephenson, Johannesburg, South Africa W. G. Strupczewski, Warsaw, Poland For other titles published in this series, go to www.springer.com/series/6689 Robert J. Abrahart · Linda M. See · Dimitri P. Solomatine (Eds.) Practical Hydroinformatics Computational Intelligence and Technological Developments in Water Applications 123 Editors Robert J. Abrahart Linda M. See University Nottingham University of Leeds Dept. Geography School of Geography University Park Fac. Earth and Environment Nottingham Woodhouse Lane Leeds United Kingdom NT7 2QW United Kingdom LS2 9JT [email protected] [email protected] Dimitri P. Solomatine UNESCO - IHE Institute for Water Education 2601 DA Delft The Netherlands and Water Resources Section Delft University of Technology The Netherlands [email protected] ISBN: 978-3-540-79880-4 e-ISBN: 978-3-540-79881-1 Library of Congress Control Number: 2008928293 c 2008 Springer-Verlag Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Boekhorst Design b.v. Printed on acid-free paper 987654321 springer.com Contents Part I Hydroinformatics: Integrating Data and Models 1 Some Future Prospects in Hydroinformatics ..................... 3 M.B. Abbott 2 Data-Driven Modelling: Concepts, Approaches and Experiences .... 17 D. Solomatine, L.M. See and R.J. Abrahart Part II Artificial Neural Network Models 3 Neural Network Hydroinformatics: Maintaining Scientific Rigour .. 33 R.J. Abrahart, L.M. See and C.W. Dawson 4 Neural Network Solutions to Flood Estimation at Ungauged Sites ... 49 C.W. Dawson 5 Rainfall-Runoff Modelling: Integrating Available Data and Modern Techniques ................................................. 59 S. Srinivasulu and A. Jain 6 Dynamic Neural Networks for Nonstationary Hydrological Time Series Modeling ............................................. 71 P. Coulibaly and C.K. Baldwin 7 Visualisation of Hidden Neuron Behaviour in a Neural Network Rainfall-Runoff Model ....................................... 87 L.M. See, A. Jain, C.W. Dawson and R.J. Abrahart 8 Correction of Timing Errors of Artificial Neural Network Rainfall-Runoff Models ...................................... 101 N.J. de Vos and T.H.M. Rientjes v vi Contents 9 Data-Driven Streamflow Simulation: The Influence of Exogenous Variables and Temporal Resolution ............................ 113 E. Toth 10 Groundwater Table Estimation Using MODFLOW and Artificial Neural Networks ............................................ 127 K. Mohammadi 11 Neural Network Estimation of Suspended Sediment: Potential Pitfalls and Future Directions ................................. 139 R.J. Abrahart, L.M. See, A.J. Heppenstall and S.M. White Part III Models Based on Fuzzy Logic 12 Fuzzy Logic-Based Approaches in Water Resource System Modelling .................................................. 165 P.P. Mujumdar and S. Ghosh 13 Fuzzy Rule-Based Flood Forecasting ........................... 177 A. Bardossy 14 Development of Rainfall–Runoff Models Using Mamdani-Type Fuzzy Inference Systems ..................................... 189 A.P. Jacquin and A.Y. Shamseldin 15 Using an Adaptive Neuro-fuzzy Inference System in the Development of a Real-Time Expert System for Flood Forecasting .. 201 I.D. Cluckie, A. Moghaddamnia and D. Han 16 Building Decision Support Systems based on Fuzzy Inference ...... 215 C.K. Makropoulos, D. Butler and C. Maksimovic Part IV Global and Evolutionary Optimization 17 Global and Evolutionary Optimization for Water Management Problems .................................................. 231 D. Savic 18 Conditional Estimation of Distributed Hydraulic Conductivity in Groundwater Inverse Modeling: Indicator-Generalized Parameterization and Natural Neighbors ....................... 245 F.T-C. Tsai and X. Li 19 Fitting Hydrological Models on Multiple Responses Using the Multiobjective Evolutionary Annealing-Simplex Approach......... 259 A. Efstratiadis and D. Koutsoyiannis Contents vii 20 Evolutionary-based Meta-modelling: The Relevance of Using Approximate Models in Hydroinformatics ....................... 275 S.-T. Khu, D. Savic and Z. Kapelan 21 Hydrologic Model Calibration Using Evolutionary Optimisation .... 291 A. Jain and S. Srinivasulu 22 Randomised Search Optimisation Algorithms and Their Application in the Rehabilitation of Urban Drainage Systems ...... 303 D.P. Solomatine and Z. Vojinovic 23 Neural Network Hydrological Modelling: An Evolutionary Approach .................................................. 319 A.J. Heppenstall, L.M. See, R.J. Abrahart, and C.W. Dawson Part V Emerging Technologies 24 Combining Machine Learning and Domain Knowledge in Modular Modelling .................................................. 333 D.P. Solomatine 25 Precipitation Interception Modelling Using Machine Learning Methods – The Dragonja River Basin Case Study ................ 347 L. Stravs, M. Brilly and M. Sraj 26 Real-Time Flood Stage Forecasting Using Support Vector Regression ................................................. 359 P.-S. Yu, S.-T. Chen and I-F. Chang 27 Learning Bayesian Networks from Deterministic Rainfall–Runoff Models and Monte Carlo Simulation ........................... 375 L. Garrote, M. Molina and L. Mediero 28 Toward Bridging the Gap Between Data-Driven and Mechanistic Models: Cluster-Based Neural Networks for Hydrologic Processes .. 389 A. Elshorbagy and K. Parasuraman 29 Applications of Soft Computing to Environmental Hydroinformatics with Emphasis on Ecohydraulics Modelling ..................... 405 Q. Chen and A. Mynett 30 Data-Driven Models for Projecting Ocean Temperature Profile from Sea Surface Temperature ................................ 421 C.D. Doan, S.Y. Liong and E.S. Chan viii Contents Part VI Model Integration 31 Uncertainty Propagation in Ensemble Rainfall Prediction Systems used for Operational Real-Time Flood Forecasting ............... 437 I.D. Cluckie and Y. Xuan 32 OpenMI – Real Progress Towards Integrated Modelling ........... 449 D. Fortune, P. Gijsbers, J. Gregersen and R. Moore 33 Hydroinformatics – The Challenge for Curriculum and Research, and the “Social Calibration” of Models ......................... 465 J.P. O’Kane 34 A New Systems Approach to Flood Management in the Yangtze River, China ................................................ 479 H. Betts, S. Markar and S. Clark 35 Open Model Integration in Flood Forecasting .................... 495 M. Werner List of Contributors M.B. Abbott Knowledge Engineering BVBA, Avenue Francois Folie 28, Box 28, 1180 Brussels, Belgium, and European Institute for Industrial Leadership, Chateauˆ Latour de Freins, 1180, Brussels, Belgium, www.eiil.net, e-mail: [email protected] R.J. Abrahart School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD, UK A. Bardossy Institut fur¨ Wasserbau, Universitat¨ Stuttgart Pfaffenwaldring 61, D-70569 Stuttgart, Germany, e-mail: [email protected] H. Betts SAGRIC International Pty Ltd., 16 Carlisle Court, Hallett Cove, S.A. 5158 Australia M. Brilly Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova 2, SI-1000 Ljubljana, Slovenia, e-mail: [email protected] I-F. Chang Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Taiwan Q. Chen RCEES Chinese Academy of Sciences, Shuangqinglu 18, Haidian District, Beijing 100085; WL | Delft Hydraulics, Rotterdamsweg 185, 2600 MH Delft, The Netherlands S.-T. Chen Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Taiwan ix x List of Contributors C.D. Doan Tropical Marine Science Institute, National University of Singapore, 12 Kent Ridge Road, Singapore 119223 S. Clark Water Technology Pty Ltd, Unit 15 Business Park Drive, Notting Hill, VIC, 3168 Australia I.D. Cluckie Water and Environmental Management Research Centre (WEMRC), Department of Civil Engineering, University of Bristol, Bristol, BS8 1UP, UK, e-mail: [email protected] P. Coulibaly Department of Civil Engineering/School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, L8S 4L7 Canada, e-mail: [email protected] C.K. Baldwin Utah Water Research Laboratory, Utah State University, Logan, Utah 84322-8200 USA D. Butler Centre for Water Systems, School of Engineering, University of Exeter, UK C.W. Dawson Department of Computer Science, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK, e-mail:
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