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Showing 2 results for Solgi

Dr Abazar Solgi, Dr Heidar Zarei, , ,
Volume 18, Issue 50 (3-2018)
Abstract

Estimating and predicting precipitation and achieving its runoff play an important role to correct management and exploitation of basins, management of dams and reservoirs, minimizing the flood damages and droughts, and water resource management, so they are considered by hydrologists. The appropriate performance of intelligent models leads researchers to use them for predicting hydrological phenomena more and more. Therefore, in this study, the Gene Expression Programming (GEP) and Support Vector Regression (SVR) models were used to model monthly precipitation of Nahavand City. In this study, precipitation, temperature, and relative humidity data were used in a 32-year period (from 1983 to 2014). The results showed that the same and good performance of both models (R2= 0.92), but according to different evaluation criteria, GEP model showed a little better performance (RMSE= 0.0478 and 0.0486), while the running GEP model is so easier than the SVM model. Totally, it can be said that GEP model had been suitable for modeling monthly precipitation of Varayeneh station in Nahavand City. Finally, the monthly precipitation was predicted the GEP which showed a decrease in precipitation in compared with previous months.
 


Mr Abazar Solgi, Dr Heidar Zarei, Dr Safar Marofi,
Volume 24, Issue 72 (3-2024)
Abstract

Different methods are used for baseflow separation, filtering method one of these methods. In this study, the filtering methods with different algorithms, inclusive One-Parameter, Two-Parameter, Three-Parameter, Lyne & Hollick, Chapman, Furey & Gupta, Eckhardt and Ewma used for daily baseflow separation of Kahman karst spring in Aleshter county. The statistical period used in this study was a period of 27 years. The Isotope content method used as the main method for baseflow separation. Samples analyzed at the Mesbah Energy Company laboratory. Each algorithm has different parameters. First the parameters of each algorithm optimized based on the isotopic content method in the water year of 2017-2018. Then the optimized parameters used for the period 27 years.  At the end, using the evaluation of different critical compared to the different algorithms. The results showed that the Eckhart algorithm performs better than other algorithms. This algorithm estimated baseflow and surface water indexes, respectively 81 and 19 percent.


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