The application of chaos theory and genetic programming has been gained a special attention in hydrology by abilities of these two models. In this study, a daily streamflow series with 30 years records of Lighvan River has been studied using these models. First in chaos theory, possibility of the existence of deterministic chaos in the daily streamflow series has been investigated by employing the correlation dimension method and after determination of the necessary parameters for reconstruction of phase space; daily streamflow is predicted by the use of local prediction method. To reconstruct the data pertaining to phase space, the time delay and embedding dimension are needed. For this purpose, autocorrelation function and algorithm of false nearest neighbors have been used and the amount of the obtained correlation dimension expresses chaotic behavior in the time series under investigation. Finally, local prediction method was used for prediction of the daily discharge and the results illustrate acceptable accuracy of this theory. The genetic programming has been used for daily discharge modeling and the best input pattern consists of antecedent discharge with four time lags has also been selected. The obtained correlation coefficient being equal to 0.926 from local prediction method and 0.931 from genetic programming indicate good accuracy and similar results obtained from both methods for streamflow prediction. Thus, according to the obtained results, both methods can be used for streamflow prediction and modeling.
Moradizadeh Kermani, F., Ghorbani, M. A., Dinpashoh, Y., & Farsadizadeh, D. (2013). Predicting Model of River Streamflow Based on Chaotic Phase Space Reconstruction. Water and Soil Science, 22(4), 1-16.
MLA
Farnoosh Moradizadeh Kermani; Mohammad ali Ghorbani; Yaghob Dinpashoh; Davood Farsadizadeh. "Predicting Model of River Streamflow Based on Chaotic Phase Space Reconstruction". Water and Soil Science, 22, 4, 2013, 1-16.
HARVARD
Moradizadeh Kermani, F., Ghorbani, M. A., Dinpashoh, Y., Farsadizadeh, D. (2013). 'Predicting Model of River Streamflow Based on Chaotic Phase Space Reconstruction', Water and Soil Science, 22(4), pp. 1-16.
VANCOUVER
Moradizadeh Kermani, F., Ghorbani, M. A., Dinpashoh, Y., Farsadizadeh, D. Predicting Model of River Streamflow Based on Chaotic Phase Space Reconstruction. Water and Soil Science, 2013; 22(4): 1-16.
)