Impact assessment of climate change and human activities on streamflow signatures in the Yellow River Basin using the Budyko hypothesis and derived differential equation

Abstract

Streamflow has been complexly altered by climate change and human activities in major rivers worldwide. The traditional Darwinian approach for impact assessment of climate change and human activities mainly focuses on variations in annual streamflow, but ignores other critical streamflow characteristics (e.g., high- and low-flow signatures). In our study, seven streamflow metrics were adopted to characterize the main streamflow signatures including average, low and high flows, and the Budyko-based method was extended based on the derived differential equation of streamflow signature change to separate individual impacts of climate change and human activities. The Yellow River Basin, China was selected as the study area because of its high intensity of human activities, and daily runoff observation series from 1960 to 2015 at four stations from the source region to the downstream region were used for the assessment. The assessment results were also compared with those estimated by the hydrological modeling method for validation. The results show that all streamflow signatures at the four stations have evidently declined after the 1980s, particularly for high-flow magnitudes. Both climate change and human activities decrease most of streamflow signatures, and human activities play major roles, which are gradually enhanced from the source region to the downstream region. The contributions of human activities are from −66.85% to −56.68% in the Tangnaihai controlled catchment, from −96.93% to −54.59% in the Qingtongxia controlled catchment, from −83.61% to −57.49% in the Longmen controlled catchment, and from −91.02% to −57.29% in the Lijin controlled catchment. The most impacted signature is the average flow in the non-flood season, followed by the annual maximum flow. The estimated contributions of climate change and human activities match well with those estimated by the hydrological modeling method, particularly for the high- and average-flow signatures with contribution deviations less than 10%. However, the estimated contributions to the low-flow signatures are quite different likely due to large uncertainty of low flow estimation. This study is expected to provide insights into the streamflow variations basin wide and provide scientific foundations for ecological protection and high-quality development of the Yellow River Basin, China.