Evaluating the performance of CRU and NCEP CFSR global reanalysis climate datasets, in hydrological simulation by SWAT model, Case Study: Maharlu basin

Hydrological modeling needs climate data with high spatially accuracy, especially in low-rainfall areas, which usually there is a no-good observational network throughout the country. Currently, the problems of lack in climate observational data can be solved somewhat with using gridded global databases. CRU and NCEP CFSR databases, including the most prestigious gridded databases, which in this study were evaluated by using SWAT model for Maharlu Lake basin. After statistical index comparisons in 33 years (1980 -2013), which Nash Sutcliffe efficiency showed the accuracy approximately 0.91 in monthly scale, modeling was conducted by SWAT for different three datasets. The modeling results showed that both of two databases beside the observation values could have high accuracy in rainfall runoff modeling which CRU database indicated better runoff simulation toward NCEP CFSR database. Coefficients of determination and Nash Sutcliffe efficiency in each calibration and validation periods represented average values above 0.7 for observed datasets, 0.65 for CRU and 0.6 for NCEP CFSR.