Artificial Neural Network Models of Daily Pan Evaporation
Publication: Journal of Hydrologic Engineering
Volume 11, Issue 1
Abstract
Artificial neural network (ANN) models are proposed as an alternative approach of evaporation estimation for Lake Eğirdir. This study has three objectives: (1) to develop ANN models to estimate daily pan evaporation from measured meteorological data; (2) to compare the ANN models to the Penman model; and (3) to evaluate the potential of ANN models. Meteorological data from Lake Eğirdir consisting of 490 daily records from 2001 to 2002 are used to develop the model for daily pan evaporation estimation. The measured meteorological variables include daily observations of air and water temperature, sunshine hours, solar radiation, air pressure, relative humidity, and wind speed. The results of the Penman method and ANN models are compared to pan evaporation values. The comparison shows that there is better agreement between the ANN estimations and measurements of daily pan evaporation than for other model.
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References
Abtew, W. (2001). “Evaporation estimation for Lake Okeechobee in South Florida.” J. Irrig. Drain. Eng., 127(3), 140–147.
Anders, U., and Korn, O. (1999). “Model selection in neural networks.” Neural Networks, 12, 309–323.
Andersen, M. E., and Jobson, H. E. (1982). “Comparison of techniques for estimating annual lake evaporation using climatological data.” Water Resour. Res., 18(3), 630–636.
Choudhury, B. J. (1999). “Evaluation of an empirical equation for annual evaporation using field observations and results from a biophysical model.” J. Hydrol., 216, 99–110.
de Bruin, H. A. R. (1978). “A simple model for shallow lake evaporation.” J. Appl. Meteorol., 17, 1132–1134.
Demuth, H., and Beale, M. (2001). Neural network toolbox user’ guide—version 4.
Dorvlo, A. S. S., Jervase, J. A., and Al-Lawati, A. (2002). “Solar radiation estimation using artificial neural networks.” Appl. Energy, 71, 307–319.
Imrie, C. E., Durucan, S., and Korre, A. (2000). “River flow prediction using artificial neural networks: Generalization beyond the calibration range.” J. Hydrol., 233, 138–153.
Lin, C. T., and Lee, C. S. G. (1995). Neural fuzzy systems, Prentice Hall, Englewood Cliffs, N.J.
Linsley, R. K., Kohler, M. A., and Paulhus, J. L. H. (1982). Hydrology for engineers, McGraw-Hill, London.
Luk, K. C., Ball, J. E., and Sharma, A. (2000). “A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting.” J. Hydrol., 227, 56–65.
McKenzie, R. S., and Craig, A. R. (2001). “Evaluation of river losses from the Orange River using hydraulic modeling.” J. Hydrol., 241, 62–69.
Morton, F. I. (1979). “Climatological estimates of lake evaporation.” Water Resour. Res., 15, 64–76.
Stewart, R. B., and Rouse, W. R. (1976). “A simple method for determining the evaporation from shallow lakes and ponds.” Water Resour. Res., 12, 623–627.
Sudheer, K. P., Gosain, A. K., Mohana Rangan, D., and Saheb, S. M. (2002). “Modelling evaporation using an artificial neural network algorithm.” Hydrolog. Process., 16, 3189–3202.
Tokar, A. S., and Johnson, P. A. (1999). “Rainfall-runoff modeling using artificial neural networks.” J. Hydraul. Eng., 4(3), 232–239.
Vallet-Coulomb, C., Legesse, D., Gasse, F., Travi, Y., and Chernet, T. (2001). “Lake evaporation estimates in tropical Africa (Lake Ziway, Ethiopia).” J. Hydrol., 245, 1–18.
Warnaka, K., and Pochop, L. (1988). “Analyses of equation for free water evaporation estimates.” Water Resour. Res., 24(7), 979–984.
Wilson, E. M. (1990). Engineering hydrology, Macmillan, London.
Xu, C. Y., and Singh, V. P. (1998). “Dependence of evaporation on meteorological variables at different time-scales and intercomparison of estimation methods.” Hydrolog. Process., 12, 429–442.
Zealand, C. M., Burn, D. H., and Simonovic, S. P. (1999). “Short term streamflow forecasting using artificial neural networks.” J. Hydrol., 214, 32–48.
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Information
Published In
Journal of Hydrologic Engineering
Volume 11 • Issue 1 • January 2006
Pages: 65 - 70
Copyright
© 2006 ASCE.
History
Received: May 14, 2003
Accepted: Mar 1, 2005
Published online: Jan 1, 2006
Published in print: Jan 2006
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