Calibration of recursive digital filters to separate the base flow, case study: Karkheh Basin

Understanding the base flow can be useful in river flow analysis, rainfall-runoff modeling, calibration of models, water resource management in low flow conditions and determination of the amount of water storage in watershed. In this research, 22 stations were selected with the appropriate data and common period of the years of 1982-2012. The trend of flow changes during the months of the year was determined for all hydrometric stations in the study area and the driest month was determined. Then, the calibration of six recursive digital algorithms was performed using the long-term data of the driest month of the year and after obtaining optimal parameters of the models, the base flow separation for the whole period was performed. The performance evaluation of the models was done using root mean square error. The results showed that the major part of the river flow in the study area was related to the base flow and the minimum, maximum and average annual base flow index for the whole period was equal to 0.48, 0.62 and 0.56, respectively, representing more than 50% of ground water contribution to stream flow of the studied watersheds. Results of the evaluation of the models using the root mean square error showed that the mean error in the research area for all the methods ranged from 0.025 to 0.044. The minimum was related to Lynie and Holick, and the maximum related to the One-parameter digital filter. Over all, conclusion of the results of the calibration process and investing the correlation between calculated and measured data showed that there was a correlation with a coefficient of explanation of more than 80%. Calibration method with dry season data in the absence of tracer-based methods is suggested as the most suitable method for calibrating digital separation filters in the study area.