Abstract: Hydroclimatic processes are usually influenced by a variety of deterministic and stochastic factors,and often present obvious short/long-range dependence characteristics.Fractionally autoregressive integrated moving average (FARIMA) models are widely used to comprehensively describe the short/long-range dependence of hydroclimatic processes.However,how to accurately determine the fractional order d,autoregressive order p,as well as moving average order q in the FARIMA model remains a challenging issue.The correlation coefficient information criterion (RIC) is based on the correlation coefficient between short/long-range dependence component and the original time series,and it calculates the mean square error to reflect the goodness of fit,and then constructs a penalty parameter to evaluate the model’s uncertainty and complexity.Thus,the RIC may be suitable for determining the key orders in the FARIMA model.In this article,the significance of the short/long-range dependence characteristics of hydrological time series is graded based on the correlation coefficient,and the applicability of the RIC to determine the FARIMA model’s key orders is explored.The results of Monte Carlo experiments show that all residual series,generated by RIC-based model,can pass the independence test.While not all residual series,generated by the models based on AIC and BIC,can pass the independence test.Moreover,compared with the AIC cand BIC,the RIC is more accurate in determining the FARIMA model’s key orders,thus more accurate short/long dependent components could be determined by the latter.The above mentioned three criteria are employed to analyze the temperature series of the Tibetan Plateau and its surrounding areas,and the results also verify that the RIC has higher accuracy and reliability than the AIC and BIC.