Taking the Yarkand River as an example, this paper conducted an integrative approach combining the Durbin-Watson statistic test (DWST), multiple linear regression (MLR), wavelet analysis (WA), coefficient of determination (CD), and Akaike information criterion (AIC) to analyze the climatic-hydrological process of inland river, Northwest China from a multitime scale perspective. The main findings are as follows. (1) The hydrologic and climatic variables, that is, annual runoff (AR), annual average temperature, (AAT) and annual precipitation (AP), are stochastic and, no significant autocorrelation. (2) The variation patterns of runoff, temperature, and precipitation were scale dependent in time. AR, AAT, and AP basically present linear trends at 16-year and 32-year scales, but they show nonlinear fluctuations at 2-year and 4-year scales. (3) The relationship between AR with AAT and AP was simulated by the multiple linear regression equation (MLRE) based on wavelet analysis at each time scale. But the simulated effect at a larger time scale is better than that at a smaller time scale.