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The Scientific World Journal
Volume 2014, Article ID 347625, 13 pages
http://dx.doi.org/10.1155/2014/347625
Research Article

Prediction of the Reference Evapotranspiration Using a Chaotic Approach

1State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
2College of Water Resources and Hydrology, Hohai University, Nanjing 210098, China
3College of Resources & Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
4Key Laboratory of Efficient Irrigation-Drainage and Agricultural Soil-Water Environment in Southern China of Ministry of Education, College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
5College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

Received 11 April 2014; Revised 14 June 2014; Accepted 30 June 2014; Published 16 July 2014

Academic Editor: Dimitrios A. Karras

Copyright © 2014 Wei-guang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Evapotranspiration is one of the most important hydrological variables in the context of water resources management. An attempt was made to understand and predict the dynamics of reference evapotranspiration from a nonlinear dynamical perspective in this study. The reference evapotranspiration data was calculated using the FAO Penman-Monteith equation with the observed daily meteorological data for the period 1966–2005 at four meteorological stations (i.e., Baotou, Zhangbei, Kaifeng, and Shaoguan) representing a wide range of climatic conditions of China. The correlation dimension method was employed to investigate the chaotic behavior of the reference evapotranspiration series. The existence of chaos in the reference evapotranspiration series at the four different locations was proved by the finite and low correlation dimension. A local approximation approach was employed to forecast the daily reference evapotranspiration series. Low root mean square error (RSME) and mean absolute error (MAE) (for all locations lower than 0.31 and 0.24, resp.), high correlation coefficient (CC), and modified coefficient of efficiency (for all locations larger than 0.97 and 0.8, resp.) indicate that the predicted reference evapotranspiration agrees well with the observed one. The encouraging results indicate the suitableness of chaotic approach for understanding and predicting the dynamics of the reference evapotranspiration.