Multi-scale modeling of the response of runoff to climate change

Abstract

With global warming, climate change has tremendously changed the hydrological processes. To discover the non-linear trend of the natural runoff and its response 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 analysis and multiple linear regression analysis. The main findings of this study are: (1) The annual natural runoff, precipitation and temperature have the similar periods (27-year, 12-year), which indicates that the periodicity of the natural annual runoff has closely relationship with the regional climate change. (2) The annual runoff, precipitation and temperature exhibit five patterns non-linear variations 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 significant 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) Although the runoff and the climate change factors have non-linear trends at different time scales, the runoff has linear correlation with the temperature and the precipitation, especially at a large time scale.