Abstract

This paper simulates the thermal stratification of the Karkhe Reservoir, Iran, with the CE-QUAL-W2 model for the period 1981–1995. The simulation of reservoir water quality requires meteorological, hydrological, chemical, and discharge time series to accurately predict the temperature of water releases from the reservoir. Outlet water temperature of the Karkhe Reservoir is calculated using the CE-QUAL-W2 model and the simulated outlet water temperature is thereafter modeled with the library for support vector machines (LIBSVM) data-mining model. Simulation results show thermal stratification in the Karkhe Reservoir occurs once a year. In addition, the data-mining model is a good surrogate model for the CE-QUAL-W2 model for estimating water temperature at different outlet levels in the reservoir. The root-mean square, mean absolute error and Nash-Sutcliffe criteria are used to assess the performance of the data-mining method. The LIBSVM model was found to be a suitable surrogate model for the main simulation model, and can be linked to optimization models with which to calculate reservoir operational rules for thermal control.

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