Updating real-time flood forecasting using a fuzzy rule-based model

Hydrological Sciences Journal

Volumn 50, Issue 2, 2005, Pages 265-278

  Yu, Pao Shan ^a   Chen, Shien Tsung ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Flood forecasting; Fuzzy rule based model; Grey model; Updating

Indexed keywords

FORECASTING; FUZZY CONTROL; MATHEMATICAL MODELS; RAIN;

ERROR PREDICTION MODEL; FLOOD FORECASTING MODEL; FORECAST HYDROGRAPHS; GREY RAINFALL MODEL;

FLOODS;

FLOOD FORECASTING; FORECASTING METHOD; FUZZY MATHEMATICS; RAINFALL-RUNOFF MODELING; REAL TIME;

EID: 17444408911     PISSN: 02626667     EISSN: None     Source Type: Journal    
DOI: 10.1623/hysj.50.2.265.60651     Document Type: Article

References (35)

1. Abebe, A. J., Solomatine, D. P. & Venneker, R. G. W. (2000) Application of adaptive fuzzy rule-based models for reconstruction of missing precipitation events. Hydrol. Sci. J. 45(3), 425-436.
2. Ahsan, M. & O'Connor K. M. (1994) A reappraisal of the Kalman filtering technique, as applied in river flow forecasting. J. Hydrol. 161, 197-226.
3. Babovic, V., Canizares, R., Jensen, H. R. & Klinting, A. (2001) Neural networks as routine for error updating of numerical models. J. Hydraul. Engng ASCE 127(3), 181-193.
4. Chen, S. T. (1998) Application of grey prediction model on runoff forecasting. MSc Thesis, National Cheng Kung University, Tainan, Taiwan (in Chinese).
5. Chen Shouyu & Fu Guangtao (2003) A DRASTIC-based fuzzy pattern recognition methodology for groundwater vulnerability evaluation. Hydrol. Sci. J. 48(2), 211-220.
6. Coppola, E. A., Duckstein, L. & Davis, D. (2002) Fuzzy rule-based methodology for estimating monthly groundwater recharge in a temperate watershed. J. Hydrol. Engng ASCE 7(4), 326-335.
7. Deka, P. & Chandramouli, V. (2003) A fuzzy neural network model for deriving the river stage-discharge relationship. Hydrol. Sci. J. 48(2), 197-209.
8. Deng, J. L. (1989) Introduction to grey system theory. The Journal of Grey System 1(1), 1-24.
9. Dubrovin, T., Jolma, A. & Turumen, E. (2002) Fuzzy model for real-time reservoir operation. Water Resour. Plan. Manage. ASCE 128(1), 66-73.
10. Hundecha, Y., Bardossy, A. & Theisen, H. W. (2001) Development of a fuzzy logic-based rainfall-runoff model. Hydrol. Sci. J. 46 (3), 363-376.
11. Khan, M. H. (1993) Muskingum flood routing model for multiple tributaries. Water Resour. Res. 29(4), 1057-1062.
12. Lee, R. H. & Wang, R. Y. (1998) Parameter estimation with colored noise effect for differential hydrological grey model. J. Hydrol. 208, 1-15.
13. Lees, M., Young, P., Ferguson, S., Beven, K. & Burns, J. (1994) An adaptive flood warning scheme for the River Nith at Dumfries. In: River Flood Hydraulics (ed. by W. R. White & J. Watts) (Proc. Second Int. Conf. on River Flood Hydraulics, March 1994, York, UK), 65-75. John Wiley & Sons Ltd, Chichester, West Sussex, UK.
14. Mukherjee, D. & Mansour, N. (1996) Estimation of flood forecasting errors and flow-duration joint probability of exceedance. J. Hydraul. Engng ASCE 122(3), 130-140.
15. O'Donnell, T. (1985) A direct three-parameter Muskingum procedure incorporating lateral inflow. Hydrol. Sci. J. 30(4), 479-496.
16. Panigrahi, D. P. & Mujumdar, P. P. (2000) Reservoir operation modelling with fuzzy logic. Water Resour. Manage. 14(2), 89-109.
17. Pongrácz, R., Bogardi, I. & Duckstein, L. (1999) Application of fuzzy rule-based modeling technique to regional drought. J. Hydrol. 224, 100-114.
18. Pongrácz, R., Bogardi, I. & Duckstein, L. (2003) Climatic forcing of droughts: a Central European example. Hydrol. Sci. J. 48(1), 39-50.
19. Reed, D. W. (1984) A review of British flood forecasting practice. Report no. 90, Institute of Hydrology, Wallingford, UK.
20. Refsgård, J. C. (1997) Validation and intercomparison of different updating procedures for real-time forecasting. Nordic Hydrol. 28(2), 65-84.
21. Ross, T. J. (1995) Fuzzy Logic with Engineering Application. McGraw-Hill, New York, USA.
22. Seibert, J. (2001) On the need for benchmarks in hydrological modeling. Hydrol. Processes 15, 1063-1064.
23. Shamseldin, A. Y. & O'Connor, K. M. (2001) A non-linear neural network technique for updating of river flow forecasts. Hydrol. Earth System Sci. 5(4), 577-597.
24. Vojinovic, Z., Kecman, V. & Sharman, B. (2002) A radial basis function neural network model as an error correction tool for ICS deterministic models. In: Hydroinformatics 2002 (Proc. Fifth Int. Conf. on Hydroinformatics) (Cardiff, UK), 659-665. IWA Publishing, London, UK.
25. WMO (World Meteorological Organization) (1992) Simulated real-time intercomparison of hydrological models. Operational Hydrology Report no. 38, WMO, Geneva, Switzerland.
26. Xia, J. (1989) Research and application of grey system theorem to hydrology. The Journal of Grey System 1(1), 43-52.
27. Xiong, L. H. & O'Connor, K. M. (2002) Comparison of four updating models for real-time river flow forecasting. Hydrol. Sci. J. 47(4), 621-639.
28. Yagi, S. & Shiba, S. (1999) Application of genetic algorithms and fuzzy control to a combined sewer pumping station. Water Sci. Technol. 39(9), 217-224.
29. Young, P. C. (2002) Advances in real-time flood forecasting. Phil. Trans. Roy. Soc. London 360, 1433-1450.
30. Yu, P. S. (1989) Real-time grid based distributed rainfall-runoff model for flood forecasting with weather radar. PhD Thesis, The University of Birmingham, Birmingham, UK.
31. Yu, P. S. & Tseng, T. Y. (1996) A model to forecast flow with uncertainty analysis. Hydrol. Sci. J. 41(3), 327-344.
32. Yu, P. S., Chen, C. J. & Chen, S. J. (2000) Application of grey and fuzzy methods for rainfall forecasting. J. hydrol. Engng ASCE 5(4), 339-345.
33. Yu, P. S., Chen, C. J., Chen, S. J. & Lin, S. C. (2001) Application of grey model toward runoff forecasting. J. Am. Water Resour. Assoc. 37(1), 151-166.
34. Yu, P. S., Chen, S. T. & Chang-Chien, F. L. (2003) A friendly window-based model for real-time flood forecasting. In: Proceedings of International Conference of GIS & RS in Hydrology, Water Resources and Environment (16-19 September 2003, Three Gorges, China) (CD-ROM).
35. Zadeh, L. A. (1965) Fuzzy sets. Information and Control 8, 338-353.