In this study, five hydrological models, including the soil and water assessment tool (SWAT), identification of unit hydrograph and component flows from rainfall, evapotranspiration, and streamflow (IHACRES), Hydrologiska Byråns Vattenbalansavdelning (HBV), Australian water balance model (AWBM), and Soil Moisture Accounting (SMA), were used to simulate the flow of the Hablehroud River, north-central Iran. All the models were validated based on the root mean square error (RMSE), coefficient of determination (R2), Nash-Sutcliffe model efficiency coefficient (NS), and Kling-Gupta efficiency (KGE). It was found that SWAT, IHACRES, and HBV had satisfactory results in the calibration phase. However, only the SWAT model had good performance in the validation phase and outperformed the other models. It was also observed that peak flows were generally underestimated by the models. The sensitivity analysis results of the model parameters were also evaluated. A hybrid model was developed using gene expression programming (GEP). According to the error measures, the ensemble model had the best performance in both calibration (NS = 0.79) and validation (NS = 0.56). The GEP combination method can combine model outputs from less accurate individual models and produce a superior river flow estimate.

The observed radar reflectivity (Z) converts to rainfall intensity (R) by a transfer function. In the first stage, for calibration of collected data (with time step 15 minutes) by weather radar and determination of the best relation between Z and R, it applied a genetic algorithm (GA) to minimize the amount of root mean square error (RMSE). Although Z = 166R2 (the transfer function in the Khuzestan province of Iran) is an appropriate equation, the GA method distinguished that Z = 110R1.8 (from February to May) and Z = 126R2 (for other months) are the optimum transfer functions for the Abolabbas watershed in Iran. The mean of RMSE of optimum transfer equations is 0.59 mm/hr in the calibration stage and 0.85 mm/hr in the verification stage. In the second stage, the Hydrologic Modeling System (HEC-HMS model) used four types of precipitation data (extracted rainfall data from radar and the optimum transfer equations, Z = 166R2, Z = 200R1.6 and extracted rainfall data from rainfall gauging stations). The calibrated rainfall data by the optimum transfer equations can produce flood hydrographs in which their accuracy is similar to the accuracy of generated flood hydrographs by collected rainfall data of rainfall gauging stations. The mean of RMSE is 0.65 cubic metres per second and the mean or R2 is 0.89 for optimum transfer equations.