How to Select a Reference Basin in the Ungauged Regions
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Volume 18, Issue 8
Abstract
Long-term hydrologic prediction in ungauged basins is one of critical issues in the field of hydrologic calculations. Hydrologic analogy is an important method for long-term hydrologic prediction and hydrologic calculation in ungauged basins. The key point of hydrologic analogy is how to select a reference basin. This paper systematically discusses four popular methods to select a reference basin in China, which include grey analysis, fuzzy analysis, projection pursuit (PP), and set pair analysis. Through a case study in a small basin in Hebei Province, North China, the four methods are applied to select a reference basin. The advantages and disadvantages of these methods are explored. The results indicate that all four methods could be used in selecting a reference basin. It will depend on the familiarity and the experiences of the users with a specific method.
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Acknowledgments
The work was partly supported by the National Key Basic Research Program of China (No:2013CB036401), the National Science Foundation Committee of China (No.51179110), Ministry of Technology and Science of China (No:2011IM011000), and the Special Scientific Research Project of China Commonweal Trade (Meteorology) (No:GYHY201006053). The authors also thank the anonymous reviewers for their valuable comments.
References
Chen, S. (1993). “Fuzzy model and method for selection analogy basins.” Adv. Water Sci., 4(4), 288–293 (in Chinese).
Chen, S. (1994). System fuzzy decision theory and application, Technology Press, Dalian Univ., Dalian, China (in Chinese).
Chen, S. (2005). Fuzzy sets theory in water resources and flood control system, Technology Press, Dalian Univ., Dalian, China (in Chinese).
Deng, H., Li, C., and Zhang, S. (2006). “Selection method for analogy watersheds based on SPA.” Yellow River, 28(7), 3–4.
Deng, J. (1985). Grey control system, Technology Press, Huazhong Univ., Wuhan, China.
Ding, J., and Deng, Y. (1988). Stochastic hydrology, Chengdu Science and Technology University Press, Chengdu, China.
French, M. N., Krajewski, W. F., and Cuykendall, R. R. (1992). “Rainfall forecasting in space and time using a neural network.” J. Hydrol. (Amst), C-23(9), 881–890.
Friedman, J. H., and Tukey, J. W. (1974). “A projection-pursuit algorithm for exploratory data analysis.” IEEE Trans. Comput., C-23(9), 881–890.
Gill, M. K., Kaheil, Y. H., Khalil, A., McKee, M., and Bastidas, L. (2006). “Multiobjective particle swarm optimization for parameter estimation in hydrology.” Water Resour. Res., 42(7), 7417–7425.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley Longman, Boston.
Griffis, V. W., and Stedinger, J. R. (2009). “Log-Pearson Type 3 distribution and its application in flood frequency analysis. III: Sample skew and weighted skew estimators.” J. Hydrol. Eng., 14(2), 121–130.
Guo, S. (2005). Progress and evaluation of the design flood, China Water Conservancy and Hydropower Press, Beijing (in Chinese).
Huang, W. R., and Murray, C. (2008). “Multiple-station neural network for modeling tidal currents across Shinnecock Inlet, USA.” Hydrol. Processes, 22(8), 1136–1149.
Huber, P. J. (1993). “Projection-pursuit and robustness.” New directions in statistical data analysis and robustness, S. Morgenthaler, E. Ronchetti and W. A. Stahel, eds., Birkäuser, Basel, Switzerland, 139–146.
Ip, W. C., Hu, B. Q., Wong, H., and Xia, J. (2009). “Applications of grey relational method to river environment quality evaluation in China.” J. Hydrol., 379(3–4), 284–290.
Jin, J., Yang, X., and Ding, J. (2001). “An improved simple genetic algorithm—accelerating genetic algorithm.” Syst. Eng. Theory Pract., 21(4), 8–13.
Kang, M. G., Park, S. W., and Cai, X. (2009). “Integration of hydrologic gray model with global search method for real-time flood forecasting.” J. Hydrol. Eng., 14(10), 1136–1145.
Kar, A. K., Goel, N. K., Lohani, A. K., and Roy, G. P. (2012). “Application of clustering techniques using prioritized variables in regional flood frequency analysis—Case study of Mahanadi Basin.” J. Hydrol. Eng., 17(1), 213–223.
Karunasinghe, D. S. K., and Liong, S. Y. (2006). “Chaotic time series prediction with a global model: Artificial neural network.” J. Hydrol., 323(1–4), 92–105.
Levy, J. K., and Hall, J. (2005). “Advances in flood risk management under uncertainty.” Stoch. Environ. Res. Risk Assess, 19(6), 375–377.
Li, P., Chen, B., and Husain, T. (2011). “IFRAM: Integrated rule-based fuzzy adaptive resonance theory mapping system for watershed modeling.” J. Hydrol. Eng., 16(1), 21–32.
Liu, D.-F., Xie, B.-T., and Li, H.-J. (2011). “Design flood volume of the Three Gorges Dam Project.” J. Hydrol. Eng., 16(1), 71–80.
Liu, Q. Q., Singh, V. P., and Xiang, H. (2005). “Plot erosion model using gray relational analysis method.” J. Hydrol. Eng., 10(4), 288–294.
Nayak, P. C., Sudheer, K. P., and Ramasastri, K. S. (2005). “Fuzzy computing based rainfall–runoff model for real time flood forecasting.” Hydrol. Processes, 19(4), 955–968.
Partal, T., and Kisi, O. (2007). “Wavelet and neuro-fuzzy conjunction model for precipitation forecasting.” J. Hydrol., 342(1–2), 199–212.
Schulz, K., and Huwe, B. (1997). “Water flow modeling in the unsaturated zone with imprecise parameters using a fuzzy approach.” J. Hydrol., 201(1–4), 211–229.
Shamir, E., Lee, B., Bae, D., and Georgakakos, K. (2010). “Flood forecasting in regulated basins using the ensemble extended Kalman filter with the storage function method.” J. Hydrol. Eng., 15(12), 1030–1044.
Tesong, H., Lam, K. C., and Ng, S. T. (2001). “River flow time series prediction with a range dependent neural network.” Hydrol. Sci. J., 46(5), 729–745.
Tong, H. (1990). Non-linear time series: A dynamical system approach, Oxford University Press, Oxford.
Vrugt, A., Gupta, H. V., Bastidas, L. A., Bouten, W., and Sorooshian, S. (2003). “Effective and efficient algorithm for multiobjective optimization of hydrologic models.” Water Resour. Res., 39(8), 1214–1224.
Wang, W., Jin, J., and Li, Y. (2009). “Prediction of inflow at Three Gorges Dam in Yangtze River with wavelet network model.” Water Resour. Manage., 23(13), 2791–2803.
Wang, W., Li, Y., Jin, J., and Ding, J. (2010). Set pair analysis in hydrology and water resources, Science Press, Beijing, (in Chinese).
Wang, W., Xiang, H., and Li, Y. (2008). “A new approach to annual runoff classification based on set pair analysis.” J. Sichuan Univ., 40(5), 1–6 (in Chinese).
Wang, Y. (1992). Engineering hydrology, Hydraulic and Electric Press, Beijing (in Chinese).
Xia, J. (1999). Regional water environment and ecological environment quality evaluation, Hydraulic and Electric Press, Wuhan Univ., Wuhan, China.
Xiao, Y., and Mei, H. M. (1998). “Gray correlative analysis applied to selection analogy Watersheds.” J. Wuhan Univ. Hydraul. Electric Eng., 31, 10–11.
Zadeh, L. A. (1965). “Fuzzy sets.” Inf. Control, 8(3), 338–353.
Zhang, X., Ding, J., and Wang, S. (2001). “Projection pursuit method for assessing analogy basins.” Adv. Water Sci., 12(3), 356–360.
Zhao, K. (2000). Set pair analysis and its preliminary applications, Science and Technology Press of Zhejiang, Hangzhou, China.
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Published In
Journal of Hydrologic Engineering
Volume 18 • Issue 8 • August 2013
Pages: 941 - 947
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Jun 15, 2011
Accepted: Jul 2, 2012
Published online: Aug 6, 2012
Discussion open until: Jan 6, 2013
Published in print: Aug 1, 2013
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