Hydrological Modeling to Unravel the Spatiotemporal Heterogeneity and Attribution of Baseflow in the Yangtze River Source Area, China

Revealing the spatiotemporal variation in baseflow and its underlying mechanisms is critical for preserving the health and ecological functions of alpine rivers, but this has rarely been conducted in the source region of the Yangtze River (SRYR). Our study employed the Soil and Water Assessment Tool (SWAT) model coupled with two-parameter digital filtering and geostatistical approaches to obtain a visual representation of the spatiotemporal heterogeneity characteristics of the baseflow and baseflow index (BFI) in the SRYR. The SWAT model and multiple linear regression model (MLR) were used to quantitatively estimate the contribution of climate change and human activities to baseflow and BFI changes. The results underscore the robust applicability of the SWAT model within the SRYR. Temporally, the precipitation, temperature, and baseflow exhibited significant upward trends, and the baseflow and BFI showed contrasting intra-annual distribution patterns, which were unimodal and bimodal distribution, respectively. Spatially, the baseflow increased from northwest to southeast, and from the watershed perspective, the Tongtian River exhibited higher baseflow values compared to other regions of the SRYR. The baseflow and BFI values of the Dangqu River were greater than those of other tributaries. More than 50% of the entire basin had an annual BFI value greater than 0.7, which indicates that baseflow was the major contributor to runoff generation. Moreover, the contributions of climate change and human activities to baseflow variability were 122% and −22%, and to BFI variability, 60% and 40%. Specifically, precipitation contributed 116% and 60% to the baseflow and BFI variations, while the temperature exhibited contributions of 6% and 8%, respectively. Overall, it was concluded that the spatiotemporal distributions of baseflow and the BFI are controlled by various factors, and climate change is the main factor of baseflow variation. Our study offers valuable insights for the management and quantitative assessment of groundwater resources within the SRYR amidst climate change.