The use of geographic information systems (GIS) and remote sensing is common to facilitate the estimation of catchment's runoff in the last century. This action is performed by using the rainfallrunoff model, which includes climate and geomorphological changes. One way to estimate the runoff height is the Curve Number (CN) method that shows the hydrological behavior of catchment. In this research, the Arc-GIS software was used for mapping curve number by integrating vegetation maps, land use and soil hydrological group, and then the annual runoff height map of Hesarak catchment was prepared. In addition, by using empirical methods, annual runoff of the study area was compared with I. C. A. R, Justin, Angeli di Sousa, and SCS-CN methods. The comparison of estimated runoff values in different methods with observations of runoff showed that the result of SCS-CN method has more adaptation to the observed runoff and discharge. The advantage of this model is the use of different parameters such as annual precipitation, soil holding, and permeability of the curve number of the basin, which causes the measured runoff to be closer to the observed value.

RAINFALL-RUNOFF process is one of the most important and complex phenomena in the hydrological cycle and therefore different views have been presented for modeling the phenomenon. Obviously, the recognition of the behavior of the catchment can play an important role in selecting the appropriate model as well as saving time on the simulation. Previous studies have shown that the multi-linear models have an acceptable performance in the case of watersheds which usually have a regular rainfall pattern. In this study, the multilinear Wavelet-M5 model was introduced and the rainfallrunoff process in the Aji Chay catchment was investigated. At first, the main rainfall and runoff time series were decomposed to several sub-time series by the wavelet transform to overcome its non-stationarity. Then the obtained sub-time series were imposed as input data to M5 model tree to forecast the runoff values and also the results were compared to the other models (i. e. ANN, M5 and WANN) by the root mean squared error and determination coefficient criteria. The results showed that the performance of the proposed hybrid Wavelet-M5 model increased up to 69% compared to the sole M5 model tree for the Aji Chay catchment.

One of the most important objectives in hydrological studies is quantitative RAINFALL-RUNOFF process estimation at the basin. Several methods and models have been created in order to simulate the RAINFALL-RUNOFF process that each one has its’ own advantages and disadvantages. The aim of this study is to investigate the capability of the Geomorphologic Instantaneous Unit Hydrograph model in flood hydrograph development and comparing its’ performance with Snyder, SCS and Triangular models. In order to implement the mentioned methods, Rainfallrunoff data were collected for 14 events and direct hydrograph was obtained. According to the statistical indicators such as RMSE, MRE and Nash-Sutcliff Coefficient, comparison of the observed and estimated hydrographs depicted that the GIUH method was the most efficient in peak discharge estimation, and Triangular, SCS and Snyder models were the next, respectively. Also according to the results, Snyder, GIUH, Triangular and SCS methods have the most efficiency to predict the time to peak, respectively. In addition the results indicate a low estimation for GIUH and SCS methods in peak discharge prediction and over estimation for Snyder and low estimation for GIUH method in time to peak prediction.

In this study, rainfall and runoff data recorded of selected stations of Aras Boundary Basin were used to analyze rainfall and runoff fluctuations and they are projected for horizons, 2050. The Pettitt test was used to detect the breakpoint in rainfall and runoff time series. Trends in rainfall and runoff were also calculated using the original and modified Mann-Kendall test. The trend line slope was also obtained by Sen's estimator method. To project the future, general circulation models (GCMs) under two greenhouse gas emission scenarios i. e. RCP4. 5 (low emission) and RCP8. 5 (high emissions) were used. The Eureqa Formulize tool was used to simulate the rainfallrunoff process. Results showed that most of the abrupt changes have occurred in the second half of the 1990s. 83% of seasonal time series breakpoints were related to runoff. Also, 67% of the abrupt changes have occurred in the winter and spring seasons. The highest increase in annual rainfall (according to RCP4. 5 scenario) at Nir station is expected to be 9% and the highest decrease in annual rainfall (according to RCP8. 5 scenario) at Khoy station is predicted at 11%. It is also worth mentioning that in the seasonal time scale will have the highest rainfall reduction in summer. The Eureqa Formulize performed very well at all stations with NRMSE of less than 0. 5%. The results indicated that the lowest slope of the base period runoff trend line (in seasonal time scale) was-1. 3 million m 3 in summer at Badalan station. There will be no significant change in the annual flow in the future period.