Understanding the change in streamflow of an inland river as a response to regional climate change in Northwest China

The hydro-climatic process in arid areas is an important academic issue, which has been paid more and more attentions since the 1990s. But to date, it has not received satisfactory answers. From a perspective of multi-time scales, this paper studied the relationship between the stream flow of an inland river and its related climatic factors in the arid area of northwest China by an integrated approach combining wavelet decomposition (WD), multiple linear regression (MLR), and back propagation artificial neural network (BPANN), and investigated the Yarkand River in the southern Xinjiang as a case study. The results show that the annual runoff (AR) was mainly affected by the annual average temperature (AAT) and annual precipitation (AP), which revealed different variation patterns at five time scales. At the 16- year and 32- year scale, AR basically presented a monotonically increasing trend with the similar trend of AAT and AP. But at 2-year, 4-year, 8-year and 16-year scale, AR presented nonlinear variation with fluctuations of AAT and AP.