Development of a Hybrid Index for Drought Prediction: Case Study
Publication: Journal of Hydrologic Engineering
Volume 14, Issue 6
Abstract
Drought is a natural phenomenon that occurs in many places on the planet and may cause considerable damage. Selection of an integrated index for quantifying drought severity is a challenge for decision makers in developing water resources and operation management policies. In this study, the standardized precipitation index, water surface supply index, and Palmer drought severity index have been combined to develop an integrated index, called the hybrid drought index (HDI), using associated damage of drought events. Application of the HDI in drought severity prediction has been examined using two different types of artificial neural networks, namely, a probabilistic neural network and a multilayer perceptron network. These models have been selected due to their special characteristics that are suitable for prediction schemes. The proposed algorithm for developing HDI and drought prediction has been applied to the “Gavkhooni/Zayandeh-rud” basin in the central part of Iran. The results show the merits of each model in prediction of drought severity and model adaptation. The results also show the significant value of the proposed algorithm in formulation of a combined index for drought prediction.
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Acknowledgments
This paper was partially funded by the Office of Research at the University of Tehran.
References
Alley, W. M. (1984). “The Palmer drought severity index: Limitations and assumptions.” J. Clim. Appl. Meteorol., 23, 1100–1109.
Berthold, M., and Diamond, J. (1998). “Constructive training of probabilistic neural networks.” Neurocomputing, 19, 167–183.
Chang, G. (1990). “Effects of droughts on the streamflow characteristics.” J. Irrig. Drain. Eng., 116(3), 332–341.
Chen, S., Cowan, C. F. N., and Grant, P. M. (1991). “Orthogonal least squares learning algorithm for radial basis function networks.” IEEE Trans. Neural Netw., 2(2), 302–309.
Clausen, B., and Pearson, C. P. (1995). “Regional frequency analysis of annual maximum streamflow drought.” J. Hydrol., 173, 111–130.
Cohen, S., and Intrator, N. (2002). “A hybrid projection-based and radial basis function architecture: Initial values and global optimisation.” Pattern Anal. Appl., 5(2), 113–120.
Dracup, J. A., Lee, K. S., and Paulson, E. G. (1980). “On the definition of droughts.” Water Resour. Res., 16(2), 297–302.
Eltahir, E. A. B. (1992). “Drought frequency analysis of annual rainfall series in central and western Sudan.” J. Hydrol. Sci., 37(3), 185–199.
Frick, D. M., Bode, D., and Salas, J. D. (1990). “Effects of drought on urban water supplies. I: Drought analysis.” J. Hydraul. Eng., 116(6), 733–753.
Garen, D. (1993). “Revised surface water supply index for western United States.” J. Water Resour. Plann. Manage., 119(4), 437–454.
Hornik, K., Stimchcombe, M., and White, H. (1989). “Multilayer feedforward network are universal approximators.” Neural Networks, 2, 359–366.
Karamouz, M., Rasavi, S., and Araghinejad, Sh. (2004a). “Application of artificial neural networks in flood estimation.” Proc., 4th Int. Conf. on Decision Making in Urban & Civil Engineering, Porto, Portugal.
Karamouz, M., Torabi, S., and Araghinejad, Sh. (2004b). “Analysis of hydrologic and agricultural droughts in central part of Iran.” J. Hydrol. Eng., 9(5), 402–414.
Karamouz, M., Torabi, S., and Araghinejad, Sh. (2007). “Case study of monthly regional rainfall evaluation by spatiotemporal geostatistical method.” J. Hydrol. Eng., 12(1), 97–108.
McKee, T. B., Doesken, N. J., and Kleist, J. (1993). “The relationship of drought frequency and duration to time scales.” Preprints, Proc., 8th Conf. on Applied Climatology, American Meteorological Society, Anaheim, Calif., 179–184.
Miravet, C., and Rodriguez, F. B. (2003). “A hybrid MLP-PNN architecture for fast image superresolution.” Lect. Notes Comput. Sci., 2714, 178–179.
Palmer, W. C. (1965). “Meteorological drought.” U.S. Weather Bureau, Research Paper No. 45, Washington, D.C.
Pinkayan, S. (1966). “Conditional probabilities of occurrence of wet and dry years over a large continental area.” Hydrology Paper 12, Colorado State Univ., Fort Collins, Colo.
Rouhani, S., and Cargile, A. K. (1989). “A geostatistical tool for drought management.” J. Hydrol., 108, 257–266.
Santos, M. A. B., Correia, F. N., and DaCunha, L. V. (1983). “Drought characterization and drought impacts in Portugal.” Memoria 591, Laboratorio Nacional de Engenharia Civil, Lisbon, Portugal.
Sen, Z. (1980). “Regional drought and flood frequency analysis: Theoretical consideration.” J. Hydrol., 46, 265–279.
Shafer, B. A., and Dezman, L. E. (1982). “Development of a surface water supply index (SWSI) to assess the severity of drought conditions in snow pack runoff area.” Proc., Western Snow Conf., Colorado State University, Fort Collins, Colo., 164–175.
Shin, H. S., and Salas, J. D. (2000). “Regional drought analysis based on neural networks,” J. Hydrol. Eng., 5(2), 145–155.
Specht, D. F. (1990). “Probabilistic neural networks.” Neural Networks, 1(3), 109–118.
Specht, D. F., and Romsdahl, H. (1994). “Experience with adaptive probabilistic neural network and adaptive general regression neural network.” Proc., IEEE World Congress on Computational Intelligence, Orlando, Fla., 2, 1203–1208.
Tase, N. (1976). “Area-deficit-intensity characteristics of drought.” Ph.D. dissertation, Colorado State Univ., Fort Collins, Colo.
Wang, D. C., and Salas, J. D. (1989). “Stochastic modeling and generation of droughts,” Proc., ASCE National Conf. on Hydraulic Engineering, New Orleans, August 14–18, 1989, ASCE, New York, 50–57.
Zelenhasic, E., and Salvai, A. (1987). “A method of streamflow drought analysis.” Water Resour. Res., 23(1), 156–168.
Information & Authors
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Published In
Journal of Hydrologic Engineering
Volume 14 • Issue 6 • June 2009
Pages: 617 - 627
Copyright
© 2009 ASCE.
History
Received: Aug 29, 2007
Accepted: Sep 5, 2008
Published online: Feb 18, 2009
Published in print: Jun 2009
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