New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models
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Accurate estimation of rainfall has an important role in the optimal water resources management, as well as hydrological and climatological studies. In the present study, two novel types of hybrid models, namely gene expression programming-autoregressive conditional heteroscedasticity (GEP-ARCH) and artificial neural networks-autoregressive conditional heteroscedasticity (ANN-ARCH) are introduced to estimate monthly rainfall time series. To fulfill this purpose, five stations with various climatic conditions were selected in Iran. The lagged monthly rainfall data was utilized to develop the different GEP and ANN scenarios. The performance of proposed hybrid models was compared to the GEP and ANN models using root mean square error (RMSE) and coefficient of determination (R2). The results show that the proposed GEP-ARCH and ANN-ARCH models give a much better performance than the GEP and ANN in all of the studied stations with various climates. Furthermore, the ANN-ARCH model generally presents better performance in comparison with the GEP-ARCH model.
KeywordsEstimation Rainfall GEP-ARCH ANN-ARCH
The authors of the paper would like to thank the anonymous reviewers for their constructive comments, as well as the Islamic Republic of Iran Meteorological Organization (IRIMO) to provide the monthly rainfall data for the present study.
- Behmanesh J, Mehdizadeh S (2017) Estimation of soil temperature using gene expression programming and artificial neural networks in a semiarid region. Environ Earth Sci. https://doi.org/10.1007/s12665-017-6395-1
- Chinchorkar SS, Patel GR, Sayyad FG (2012) Development of monsoon model for long range forecast rainfall explored for Anand (Gujarat-India). Int J Water Resour Environ Eng 4(11):322–326Google Scholar
- Delleur JW, Karamouz M (1982) Uncertainty in reservoir operation. Optimal Allocation of Water Resources (Proceedings of the Fxeter Symposium), IAHS Publication no. 135:7–16Google Scholar
- Ferreira C (2001) Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst 13(2):87–129Google Scholar
- Haykin S (1998) Neural networks-a comprehensive foundation, 2nd edn. Prentice-Hall, Upper Saddle River, pp 26–32Google Scholar
- Kashid SS, Maity R (2012) Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using genetic programming. J Hydrol 454–455:26–41Google Scholar
- Khalili K, Nazeri Tahroudi M, Mirabbasi R, Ahmadi F (2016) Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stoch Environ Res Risk Assess 30(4):1205–1221Google Scholar
- UNEP (1992) World atlas of desertification. The united nations environment programme (UNEP), LondonGoogle Scholar