Wavelet-based hydrological time series forecasting

Journal of Hydrologic Engineering

Volumn 21, Issue 5, 2016, Pages

  Sang, Yan Fang ^a   Singh, Vijay P ^b   Sun, Fubao ^a   Chen, Yaning ^c   Liu, Yong ^d   Yang, Moyuan ^a  

^a INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

^b TEXAS A AND M UNIVERSITY   (United States)

^c XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY   (China)

^d NANJING HYDRAULIC RESEARCH INSTITUTE   (China)

Author keywords

Artificial intelligence modeling; Hydrological forecasting; Hydrological time series analysis; Statistical significance; Temporal scale; Wavelet analysis

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORECASTING; UNCERTAINTY ANALYSIS; WAVELET ANALYSIS;

DATA PREPROCESSING; DISCRETE WAVELETS; HYDROLOGICAL FORECASTING; HYDROLOGICAL TIME SERIES ANALYSIS; HYDROLOGICAL TIME-SERIES; STATISTICAL SIGNIFICANCE; TEMPORAL SCALE; UNCERTAINTY EVALUATION;

TIME SERIES ANALYSIS;

ARTIFICIAL INTELLIGENCE; DATA PROCESSING; HYDROLOGICAL MODELING; TIME SERIES ANALYSIS; WAVELET ANALYSIS;

EID: 84964575877     PISSN: 10840699     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)HE.1943-5584.0001347     Document Type: Article

References (27)

1. Adamowski, J., and Sun, K. (2010). "Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds". J. Hydrol., 390(1-2), 85-91
2. Belayneh, A., Adamowski, J., Khalil, B., and Ozga-Zielinski, B. (2014). "Long-term SPI drought forecasting in the Awash River basin in Ethiopia using wavelet neural network and wavelet support vector regression models". J. Hydrol., 508, 418-429
3. de Artigas, M. Z., Elias, A. G., and de Campra, P. F. (2006). "Discrete wavelet analysis to assess long term trends in geomagnetic activity". Phys. Chem. Earth., 31(1-3), 77-80
4. Donoho, D. H. (1995). "De-noising by soft-thresholding". IEEE T. Inform. Theory, 41(3), 613-627
5. Kisi, O. (2009). "Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting". Hydrol. Process., 23(25), 3583-3597
6. Krzysztofowicz, R. (2001). "The case for probabilistic forecasting in hydrology". J. Hydrol., 249(1-4), 2-9
7. Labat, D. (2008). "Wavelet analysis of the annual discharge records of the world's largest rivers". Adv. Water Resour., 31(1), 109-117
8. Maheswaran, R., and Khosa, R. (2012). "Comparative study of different wavelets for hydrologic forecasting". Comput. Geosci., 46, 284-295
9. Nalley, D., Adamowski, J., and Khalil, B. (2012). "Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954-2008)". J. Hydrol., 475, 204-228
10. Nourani, V., Baghanam, A. H., Adamowski, J., and Kisi, O. (2014). "Applications of hybrid wavelet-artificial intelligence models in hydrology: A review". J. Hydrol., 514, 358-377
11. Nourani, V., Kisi, O., and Komasi, M. (2011). "Two hybrid artificial intelligence approaches for modelling rainfall-runoff process". J. Hydrol., 402(1-2), 41-59
12. Percival, D. B., and Walden, A. T. (2000). Wavelet methods for time series analysis, Cambridge University Press, Cambridge, U.K
13. Rathinasamy, M., Adamowski, J., and Khosa, R. (2013). "Multiscale stream flow forecasting using a new Bayesian model average based ensemble multi-wavelet Volterra nonlinear method". J. Hydrol., 507, 186-200
14. Sang, Y. F. (2012). "A practical guide to discrete wavelet decomposition of hydrologic time series". Water Resour. Manage., 26(11), 3345-3365
15. Sang, Y. F. (2013). "Improved wavelet modeling framework for hydrologic time series forecasting". Water Resour. Manage., 27(8), 2807-2821
16. Sang, Y. F., Singh, V. P., Wen, J., and Liu, C. M. (2015). "Gradation of complexity and predictability of hydrological processes". J. Geophys. Res. Atmos., 120(11), 5334-5343
17. Sang, Y. F., Wang, D., Wu, J. C., Zhu, Q. P., and Wang, L. (2013). "Improved continuous wavelet analysis on the variation of hydrologic time series' dominant period". Hydrol. Sci. J., 58(1), 118-132
18. Schaefli, B., Maraun, D., and Holschneider, M. (2007). "What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology". Adv. Water Resour., 30(12), 2511-2525
19. Shoaib, M., Shamseldin, A. Y., and Melville, B. W. (2014). "Comparative study of different wavelet based neural network models for rainfall-runoff modeling". J. Hydrol., 515, 47-58
20. Singh, R. M. (2011). "Wavelet-ANN model for flood events". Adv. Intel. Software Comput., 131, 165-175
21. Singh, V. P. (1998). Entropy-based parameter estimation in hydrology, Kluwer Academic Publishers, Boston, London
22. Tiwari, M., and Adamowski, J. (2013). "Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models". Water Resour. Res., 49(10), 6486-6507
23. Tiwari, M. K., and Chatterjee, C. (2010). "Development of an accurate and reliable hourly flood forecasting model using wavelet-bootstrap-ANN (WBANN) hybrid approach". J. Hydrol., 394(3-4), 458-470
24. Torrence, C., and Compo, G. P. (1998). "A practical guide to wavelet analysis". B. Am. Meteorol. Soc., 79(1), 61-78
25. Walker, J. S. (1999). A primer on wavelets and their scientific applications, Chapman and Hall, CRC, New York
26. Wang, W. S., and Ding, J. (2003). "Wavelet network model and its application to the predication of hydrology". Nature Sci., 1(1), 67-71
27. Yevjevich, V. (1972). Stochastic process in hydrology, Water Resources Publications, Littleton, CO