Modelling daily pan evaporation of Zayanderud dam station utilizing artificial intelligence and time series models

Document Type : Original Article

Authors

1 Associate Professor, Department of Water Engineering, Shahrekord University

2 Assistant Professor, Department of Geography and Urban Planning, Maragheh University

10.30488/ccr.2024.433405.1193

Abstract

The pan evaporation is used as a practical parameter in various fields, such as estimating water loss from lakes and dams, as well as estimating the Plant water requirement, especially in areas where there is no lysimeter information. Modeling this parameter can be useful in the estimation of missing data and long-term planning of water resources and agricultural development. In this research, by using an artificial intelligence model (GEP) and two time series models (Fourier and ARIMA), evaporation from the pan at Zayanderud dam station, was modeled in the period from 1344 to 1396 (53 years). The results showed that the GEP model has acceptable results only in Mehr, and for other months the results are not acceptable in terms of statistical indicators. The daily evaporation estimated error was found to be 0.38 mm in Mehr. This error was acceptable based on the coefficient of determination of 0.84, the Nash-Sutcliffe coefficient of 0.83 and the Willmott's index of agreement of 0.95. Unlike the gene expression programming model, the Fourier model provided acceptable results in all the studied months. The error values were obtained between 1.02 and 0.7 mm per day in all the studied months, which is equivalent to 5.2 to 8.8 percent. Comparing the results of the above two models with the ARIMA model showed that, the error values of the ARIMA model in all months are higher (9.4 to 19.6%) than the Fourier model, and Gene Expression Programming model. Therefore, the best model for estimating pan evaporation in October (Mehr) is the Gene Expression Programming model and in the rest of the months, the Fourier model. The evaluation of the model in estimating the extremes daily evaporation data also showed that the highest and lowest accuracy is in October (Mehr) and June (Khordad), respectively.

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