MULTI-SCALE MODELING OF THE RESPONSE OF RUNOFF TO CLIMATE CHANGE by

With global warming, climate change has tremendously changed the hydrologi-cal processes. To discover the non-linear trend of the natural runoff and its re-sponse to precipitation and temperature in the Yellow River Basin, the non-linear relationships among the runoff, precipitation and temperature are analyzed by the wavelet decomposition and reconstruction methods, partial correlation anal-ysis and multiple linear regression analysis. The main findings of this study are: (1) The annual natural runoff, precipitation and temperature have the similar pe-riods (27-year, 12-year), which indicates that the periodicity of the natural annu-al runoff has closely relationship with the regional climate change. (2) The annu-al runoff, precipitation and temperature exhibit five patterns non-linear varia-tions at five time scales (1, 2, 4, 8, 16 years), that is to say, their non-linear trends are scale-dependent with time. (3) The annual natural runoff has a signifi-cant positive correlation with the precipitation and has a negative correlation with temperature. In addition, the runoff variation is more sensitive to change in precipitation than the change in temperature at all the five time scales. (4) Alt-hough the runoff and the climate change factors have non-linear trends at differ-ent time scales, the runoff has linear correlation with the temperature and the precipitation, especially at a large time scale