A new multi-scalar framework for quantifying the impacts of climate change and human activities on streamflow variation

Abstract

Abstract Most previous studies on attributing climate change and human activities to streamflow variation focused only on an annual scale, while few attempts were devoted to shorter time scales, such as seasonal or monthly scales. In this study, a multi-scalar framework for attribution analysis was constructed by integrating hydrological modeling into the Budyko-based decomposition method. Then, the multi-scalar framework was employed in the source region of the Yellow River (SRYR) as a case study. Moreover, the quantification results are compared with the simulation of a monthly water balance model (i.e., abcd model). The main results and findings indicate: (1) The mutation point of the annual streamflow is 1991 in the SRYR, and the monthly ABCD hydrological model achieves good performance in streamflow simulation for the prechange period and postchange period; (2) The contribution of climate change to streamflow variation is 65.99%, 37.50%, and 70.86% for annual, dry season, and wet season, respectively, indicating that climate change is the dominant factor controlling streamflow variation for the annual and wet season, while human activities play a major role in streamflow variation for dry season; (3) The contributions of climate change and human activities show obvious dynamic and seasonal characteristics, which are strongly affected by the transition between dry and wet seasons. Generally, the findings of this study provide valuable references for local reasonable water resource planning and management to make timely and appropriate use of the water supply.