Cumulative effects of meteorological factors on low-flow change in the upper Yellow River

Abstract

Climate change significantly impacts water cycle processes and water resource management in the upper Yellow River (UYR), China. Understanding the influence of meteorological factors on low-flow changes is crucial, but the optimal number of antecedent days and the specific contributions of different factors remain unclear. In this study, we use a structural equation model and path analysis to dissect the direct and indirect effects of selected meteorological factors (daily precipitation, P; average temperature, AT; average wind velocity, AWV; average relative humidity, ARH; and total radiation, TR) on four low-flow indices in the UYR. We employ data from 1958 to 2017, collected from six meteorological stations and eight hydrological stations above Lanzhou hydrological station. Our findings reveal that: (1) meteorological factors have varying direct and indirect impacts on low-flow changes at corresponding and cumulative scales. For instance, at the corresponding scale, P, AT, AWV, ARH, and TR have direct impacts of 42%, 54%, 74%, 79%, and 59%, respectively. At the cumulative scale, these values change to 67%, 59%, 67%, 64%, and 60%, respectively. (2) Cumulative effects of meteorological factors enhance the significance and goodness of fit of the analysis model, decreasing residual path coefficients and elevating the contribution of independent variables to the model. (3) The dominant components of meteorological factors affecting low-flow changes differ between corresponding and cumulative scales, explaining the variations in direct and indirect impacts. These insights are valuable for sustainable water resource management in drought-prone regions with water scarcity.