M. Teimouri, M.r. Ghanbarpour, M. Bashirgonbad, M. Zolfaghari, S. Kazemikia,
Volume 15, Issue 57 (10-2011)
Abstract
Baseflow separation has long been an important topic in hydrology and has a crucial role in water resources management in arid and semi arid regions like Iran. In this paper, a comparison among commonly used automated techniques for hydrograph separation including theoretical method of local minimum and digital filter of one parameter with different filtering parameters of 0.9 to 0.975 and two parameter methods was done to estimate baseflow using baseflow index. For this purpose, daily flow data in some stream gauging stations in west Azarbaijan province were used. For comparison, in addition to baseflow index the graphical method based on the observed daily flow data and correlation coefficient among them was utilized. The main aim of this research is distinguishing the most suitable method in hydrograph separation and estimating the baseflow. Results showed that in different methods baseflow largely contributes to streamflow and also has high fluctuations. However, the results of the digital filter with two parameters appear to be hydrologically more plausible than those of the other methods, but the results of digital filter with proper parameter - in this region one parameter method with filter of 0.925- has proper estimation accuracy. Also, the baseflow index based on method of two parameter digital filtering varies from 0.54 to 0.78 in this study area.
N. Dehghani , M. Vafakhah, A. R. Bahremand,
Volume 19, Issue 73 (11-2015)
Abstract
Rainfall-runoff modeling and prediction of river discharge is one important parameter in flood control and management, hydraulic structure design, and drought management. The goal of this study is simulating the daily discharge in Kasilian watershed by using WetSpa model and adaptive neuro-fuzzy inference system (ANFIS). The WetSpa model is a distributed hydrological and physically based model, which is able to predict flood on the watershed scale with various time intervals. The ANFIS is a black box model which has attracted the attention of many researchers. The digital maps of topography, land use, and soil type are 3 base maps used in the model for the prediction of daily discharge while intelligent models use available hydrometric and meteorological stations' data. The results of WetSpa model showed that this model can simulate the river base flow with Nash- Sutcliff criteria of 64 percent in the validation period, but shows less accuracy with flooding discharges. The reason for this result can be the small and short Travel time noted. This model can simulate the water balance in Kasilian watershed as well. The sensitivity analysis showed that groundwater flow recession and rainfall degree-day parameters have the highest and lowest effect on the results, respectively. Also, ANFIS with the inputs of rainfall 1-day lag and evaporation 1-day lag, with Nash-Sutcliff criteria of 80, was superior to WetSpa model with Nash-Sutcliff criteria of 24 percent in the validation period.
