The use of multimetric framework in calibrating the HBV model

Thesis Type: Doctorate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey

Approval Date: 2015




In this study, the HBV model is applied on the upper Euphrates basin in Turkey. Individual sensitivity of the parameters is analyzed by calibrating the model using the Multi-Objective Shuffled Complex Evolution (MOSCEM) algorithm. The calibration is performed against snow cover area (SCA) in addition to runoff data for the water years 2009, 2010, 2011 and 2012. Detailed validation studies are also performed for the snow products namely snow recognition (H10) and snow water equivalent (H13) over Turkey and Austria. In this study signature metrics, which are based on the flow duration curve (FDC) are used to see the performance of the model for low flows. The sensitivity analysis of the parameters around the calibrated optimum points showed that parameters of the soil moisture and evapotranspiration have a strong effect in the total volume error of the model. The parameters from the response and transformation routines have a significant influence on the peak flows. It is observed that the parameters of snow routine have strong effect in high flows and total volume. Besides the Shuffled Complex Evaluation Method in the calibration of the model, multi-metric evaluation framework, which represent the different phases of the hydrograph precisely, is used. A stepwise evaluation is done with commonly used statistical performance metrics (Nash-Sutcliffe, Percent Bias) and signature metrics, which are based on the flow duration curve. Validation of the model is performed for the water year 2013.