Investigation on impact of stream flow data temporal resolution on base flow separation in Karkhe Basin

Estimation of Base Flow Index (BFI), has always been one of the most important issues in hydrology. Base flow separation process, often is done using daily stream flow data. Lack of full coverage of daily data for the whole country, may lead to some errors for estimating the base flow and its index. In this research, base flow index in some catchments of Karkhe basin based on daily and monthly stream flow data and using six algorithms were extracted. Three based on recursive digital filter (One-parameter, two parameter and Lynie & Hollick algorithms), and the others on simple smoothing including, Local minimum, Fixed interval and sliding interval methods. Results were analyzed using different statistical methods such as standard deviation, mean absolute error, relative error and other descriptive methods. The results showed that minimum relative error of monthly data compared to daily data was related to two parameter algorithm with 2.45% and the maximum was related to Lynie & Hollick algorithm with 84.19 percent .In overall conclusion, two parameter algorithms because of low relative error, minimum Mean Absolute and Root Mean Square Error was recognized as a suitable method for the extraction of base flow using monthly data in the absence of appropriate data daily.