Abstract
Accurate monitoring and estimation of evaporation of a region is significant for proper planning and management of water resources management. Hence, the prediction of future alteration in evaporation is so critical in the development of irrigation systems, therefore; the current study aims to develop a hybrid artificial neural network that is coupled with COOT algorithm (ANN–COOT) to prediction the monthly evaporation in three stations in Iran. Utilizing different input combinations of monthly temperature (Tmin and Tmax), sunshine hours (SSH), wind speed (WS) and relative humidity (RH) datasets, the performance of the proposed ANN–COOT hybrid model results was compared with standalone ANN model. Statistical performances were calculated and comparison plots were made in the training and testing phases to find the most accurate model for evaporation prediction. Compared with the results of different input combinations, the hybrid ANN–COOT4 model at all three stations were found superior with input combinations of Tmin, Tmax, SSH, RH, WS. The testing results revealed that the lowest root mean square error (RMSE) (18.43 mm, 19.36 mm and 8.19 mm) and highest coefficient of correlation (R) (0.99, 0.97 and 0.99) and the highest Nash–Sutcliffe efficiency coefficient (NS) (0.98, 0.93 and 0.99) attained by the ANN–COOT4 hybrid model (relative to other ANN and ANN–COOT models) tested for three selected stations in Shiraz, Kish and Gorgan sites. In respect to the predictive efficiency, the developed ANN–COOT hybrid model, improved the modeling performance at extreme points, which outperforms conventional ANN model, indicating its capability in the prediction of monthly evaporation.
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Data Availability
The datasets used during the current study are available from the first author on reasonable request.
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The authors are thankful to the National Meteorological Organization for providing necessary data that are used for carrying out this research work.
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Alempour Rajabi, F., Ahmadi, E., Ragab Ibrahim, O. et al. Modeling Monthly Evaporation in Different Climates Using ANN–COOT Hybrid Algorithm. Iran J Sci Technol Trans Civ Eng (2024). https://doi.org/10.1007/s40996-023-01338-w
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DOI: https://doi.org/10.1007/s40996-023-01338-w