Input selection for long-lead precipitation prediction using large-scale climate variables: A case study

Journal of Hydroinformatics

Volumn 17, Issue 1, 2015, Pages 114-129

  Ahmadi, Azadeh ^a   Han, Dawei ^b   Lafdani, Elham Kakaei ^c   Moridi, Ali ^d  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

^c TARBIAT MODARES UNIVERSITY   (Iran)

^d SHAHID BEHESHTI UNIVERSITY   (Iran)

Author keywords

Climatic prediction; Entropy theory; Gamma test; Precipitation prediction; Support vector machine

Indexed keywords

EID: 84924120665     PISSN: 14647141     EISSN: None     Source Type: Journal    
DOI: 10.2166/hydro.2014.138     Document Type: Article

References (56)

1. Ahmadi, A. & Han, D. 2013 Identification of dominant sources of sea level pressure for precipitation forecasting over Wales. J. Hydroinform. 15 (3), 1002-1021.
2. Ahmadi, A., Han, D., Karamouz, M. & Remesan, R. 2009 Input data selection for solar radiation estimation. Hydrol. Process. 23 (19), 2754-2764.
3. Alfonso, L., Lobbrecht, A. & Price, R 2010 Optimization of water level monitoring network in polder systems using information theory. Water Resour. Res. 46, W12553, 13.
4. Araghinejad, S. & Burn, D. H. 2005 Probabilistic forecasting of hydrological events using geostatistical analysis. Hydrol. Sci. J. 50 (5), 838-856.
5. Araghinejad, S., Burn, D. H. & Karamouz, M. 2006 Long-lead probabilistic forecasting of streamflow using ocean-atmospheric and hydrological predictors. Water Resour. Res. 42, W03431, 11.
6. Bray, M. & Han, D. 2004 Identification of support vector machines for runoff modeling. J. Hydroinform. 6 (4), 265-280.
7. Busuico, A., Giorgi, F., Bi, X. & Ionita, M. 2006 Comparison of regional climate model and statistical downscaling simulation of different winter precipitation change scenarios over Romania. Theor. Appl. Climatol. 86, 101-123.
8. Caselton, W. F. & Husain, T. 1980 Hydrologic networks: information transinformation. J. Water Res. Plan. Manage. 106, 503-529.
9. Cavazos, T. & Hewitson, B. C. 2005 Performance of NCEP-NCAR reanalysis variables in statistical downscaling of daily precipitation. Clim. Res. 28, 95-107.
10. Choy, K. Y. & Chan, C. W. 2003 Modelling of river discharges and rainfall using radial basis function networks based on support vector regression. Int. J. Syst. Sci. 34 (14-15), 763-773.
11. Chuzhanova, N. A., Jones, A. J. & Margetts, S. 1998 Feature selection for genetic sequence classification. Bioinformatics 14 (2), 139-143.
12. Conway, H, Gades, A. & Raymond, C. F. 1996 Albedo of dirty snow during conditions of melt. Water Resour. Res. 32 (6), 1713-1718.
13. Cover, T. M. & Thomas, J. A. 1991 Elements of information theory (D. L. Schilling, ed.) Wiley Series in Telecommunications, John Wiley & Sons, New York.
14. Crawford, T., Betts, N. L. & Favis-Mortlock, D. 2007 GCM grid-box choice and predictor selection associated with statistical downscaling of daily precipitation over Northern Ireland. Clim. Res. 34 (2), 145.
15. Dibike, Y B., Velickov, S., Solomatine, D. & Abbott, M. B. 2001 Model induction with support vector machines: introduction and applications. J. Comput. dvil Engng. 15 (3), 208-216.
16. Evans, D. 2002 Data Derived Estimates of Noise Using Near Neighbour Asymptotics. PhD Thesis, Department of Computer Science, University of Cardiff, UK.
17. Evans, D. & Jones, A. J. 2002 A proof of the gamma test. Proc. Roy. Soc. Lond. Series A 458 (2027), 2759-2799.
18. Ghosh, S. & Mujumdar, P. P. 2008 Statistical downscaling of GCM simulations to streamflow using relevance vector machine. Adv. Water Res. 31, 132-146.
19. Han, D., Chan, L. & Zhu, N. 2007 Flood forecasting using support vector machines. J. Hydroinform. 9 (4), 267-276.
20. Hanssen-Bauer, I., Forland, E. J., Haugen, J. E. & Tveito, O. E. 2003 Temperature and precipitation scenarios for Norway: Comparison of results from dynamical and empirical downscaling. dim. Res. 25, 15-27.
21. Harmancioglu, N. B. & Alpaslan, N. 1992 Water quality monitoring network design a problem of multi-objective decision making. Water Res. Bull. 28, 179-192.
22. Harmancioglu, N. B. & Singh, V. P. 1998 Entropy in environmental and water resources. In: Encyclopedia of Hydrology and Water Resources (R. W. Herschy & R. W. Fairbridge, eds). Kluwer Academic Publishers, Boston, MA, pp. 225-241.
23. Hashmi, M. Z., Shamseldin, A. Y. & Melville, B. W. 2009 Statistical downscaling of precipitation: State-of-the-art and application of Bayesian multi-model approach for uncertainty assessment. Hydrol. Earth Syst. Sci. Discuss. 6, 6535-6579.
24. Hashmi, M. Z., Shamseldin, A. Y. & Melville, B. W. 2011 Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch. Environ. Res. Risk A 25 (4), 475-484.
25. Haylock, M. R, Peterson, T. C, Alves, L. M., Ambrizzi, T., Anunciação, Y. M. T., Baez, J., Barros, V. R, Berlato, M. A., Bidegain, M., Coronel, G., Corradi, V., Garcia, V. J., Grimm, A. M., Karoly, D., Marengo, J. A., Marino, M. B., Moncunill, D. F., Nechet, D., Quintana, J., Rebello, E., Rusticucci, M., Santos, J. L., Trebejo, I. & Vincent, L. A. 2006 Trends in total and extreme south American rainfall in 1960-2000 and links with sea surface temperature. J. Climate 19, 1490-1512.
26. Hertig, E. & Jacobeit, J. 2008 Assessments of Mediterranean precipitation changes for the 21st century using statistical downscaling techniques. Int. J. Climatol. 28 (8), 1025-1045.
27. Husain, T. 1989 Hydrologic uncertainty measure and network design. Water Resour. Bull. 25, 527-534.
28. Jaafar, W. Z. W. & Han, D. 2011 Calibration catchment selection for flood regionalisation modeling. J. Am. Water Resour. Assoc. 48 (4), 698-706.
29. Johansson, B. & Chen, D. 2003 The influence of wind and topography on precipitation distribution in Sweden: Statistical analysis and modeling. Int. J. Climatol. 23, 1523-1535.
30. Karamouz, M., Zahraie, B., Fatahi, E., Mirzaie, E., Remezani, F. & Hashemi, R 2005 Predictors for long-lead precipitation forecasting in western Iran. The first Iran-Korea Joint Workshop on Climate Modelling, November 16-17, Mashahd, Iran.
31. Karamouz, M., Ahmadi, A. & Moridi, A. 2009 Probabilistic reservoir operation using Bayesian stochastic model and support vector machine. Adv. Water Res. 32, 1588-1600.
32. Končar, N. 1997 Optimisation Methodologies for Direct Inverse Neurocontrol. PhD Thesis, Department of Computing, Imperial College of Science, Technology and Medicine, University of London, London, UK.
33. Krstanovic, P. F. & Singh, V. P. 1992 Evaluation of rainfall networks using entropy: I. Theorical development. Water Resour. Manage. 6 (4), 279-293.
34. Liong, S. Y. & Sivapragasam, C. 2002 Flood stage forecasting with support vector machines. J. Am. Water Res. Assoc. 38, 173-186. doi: 10.1111/j.1752-1688.2002.tb01544.
35. Moghaddamnia, A., Ghafari, M., Piri, J. & Han, D. 2009 Evaporation estimation using support vector machines technique. Int. J. Math. 3 (3), 134-142.
36. Mogheir, Y & Singh, V. P. 2002 Application of information theory to groundwater quality monitoring networks. Water Resour. Manage. 16 (1), 37-49.
37. Moradkhani, H. & Meier, M. 2010 Long-lead water supply forecast using large-scale climate predictors and independent component analysis. J. Hydrol. Eng. 15 (10), 744-762.
38. Mpelasoka, F., Mullan, A. B. & Heerdegen, R. G 2001 New Zealand climate change information drived by multivariate statistical and artificial neural network approaches. Int. J. Climatol. 21, 1415-1433.
39. Najafi, M., Moradkhani, H. & Wherry, S. 2011 Statistical downscaling of precipitation using machine learning with optimal predictor selection. J. Hydrol. Eng. 16 (8), 650-664.
40. Nash, J. E. & Sutcliffe, J. V. 1970 River flow forecasting through conceptual models, Part 1 - A discussion of principles. J. Hydrol. 10 (3), 282-290.
41. Nourani, V. & Parhizkar, M. 2013 Conjunction of SOM-based feature extraction method and hybrid wavelet-ANN approach for rainfall-runoff modeling. J. Hydroinform. 15 (3), 829-848.
42. Nourani, V. & Sayyah Frad, M. 2012 Sensitivity analysis of the artificial neural network outputs in simulation of the evaporation process at different climatologic regimes. Adv. Eng. Softw. 47 (1), 127-146.
43. Piri, J., Amin, S., Moghaddamnia, A., Keshavarz, A., Han, D. & Remesan, R 2009 Daily pan evaporation modelling in a hot and dry climate. J. Hydrol. Eng. 14 (8), 803-811.
44. Remesan, R, Shamim, M. A. & Han, D. 2008 Model input data selection using gamma test for daily solar radiation estimation. Hydrol. Process. 22, 4301-4309.
45. Schmidli, J., and Goodess., C. M., Feri, C, Haylock, M. R, Hundecha, Y., Ribalaygua, J. & Schmith, T 2007 Statistical and dynamical downscaling of precipitation: an evaluation and comparison of scenarios for the European Alps. J. Geophys. Res. 112, D04105.
46. Schoof, J. T. & Pryor, S. C. 2001 Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networks. Int. J. Climatol. 21, 773-790.
47. Shannon, C. E. & Weaver, W. 1949 The Mathematical Theory of Communication. University of Illinois Press, Urbana, IL.
48. Singh, V. P. 1997 The use of entropy in hydrology and water resources. Hydrol. Process. 11, 587-626.
49. Sivapragasam, C. & Liong, S. Y 2005 Flow categorization model for improving forecasting. Nord. Hydrol. 36 (1), 37-48.
50. Stefansson, A., Koncar, N. & Jones, A. J. 1997 A note on the gamma test. Neural Comput. Appl. 5, 131-133.
51. Tripathi, S., Srinivas, V. V. & Nanjundiah, R. S. 2006 Downscaling of precipitation for climate change scenarios: A support vector machine approach. J. Hydrol. 330 (3-4), 621-640.
52. Vapnik, V. 1998 Statistical Learning Theory. Wiley, New York.
53. Vapnik, V. N. 1992 Principles of risk minimization for learning theory. In: Advances in Neural Information Processing Systems (J. Moody, S. Hanson & R. Lippmann, eds). Elsevier, New York, p. 4.
54. Vapnik, V. N. 2010 The Nature of Statistical Learning Theory, 2nd edn. Springer, New York.
55. Widmann, M., Bretherton, C. S. & Salathé, E. P. 2003 Statistical precipitation downscaling over the northwestern United States using numerically simulated precipitation as a predictor. J. Climate 16 (5), 799-816.
56. Yu, X. Y, Liong, S. Y & Babovic, V. 2004 EC-SVM approach for realtime hydrologic forecasting. J. Hydroinform. 6 (3), 209-223.