Predicting the effects of land use changes on the monthly flow using hydrological model and Remote Sensing in the Kouzetopraghi watershed, Ardabil

This study has been carried out for the modeling of monthly runoff using Temez model and then the effects of the different land use change scenarios on runoff components have been assessed. The OLI-Landsat 8 satellite imageries were used using a support vector machine (SVM) classification method. The 10 management scenarios have been developed based on field characteristics, changes trend in the land use pattern, and the suitability criteria. The Temez monthly hydrological model was employed. A 10-year (2002 to 2012) daily precipitation, temperature and runoff data were aggregated to monthly time scales. The calibration and validation steps were performed based on observed data. For calibration of the model, the first 6 years data and for model validation 4 years data were used. The accuracy of the land use map was quite high. A Kappa coefficient of 0.95 and an overall accuracy of 0.975 was obtained. The accuracy of the modeled runoff was presented using R2 coefficient, which was 0.77 and 0.65, for calibration and validation stages, respectively. The results showed that land use reclamation scenarios of 3, 4 and 5 had a decreasing effect on the runoff by 3.4, 3.3, and 4.1 percent, respectively. Also, the land use scenarios of degradation condition, 9 and 10 scenarios, caused an increasing effect on the monthly runoff to 15.24 and 4.5 percent, respectively. The monthly hydrological Temez model showed relatively good performance in estimating monthly runoff values based on the data used.