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Structural equation modelling (SEM) results, showing the interactions between environmental factors (topography, land use types, and climate) and water quality parameters. The red and blue lines indicate positive and negative effects, respectively, while arrows between nodes indicate causal relationships. Thicker lines/arrows indicate stronger causal effects. Darker edges indicate a higher significance level ( p ≤ 0.05). H, TWI, DO, EC, PMI, and TN denote the mean elevation, topographic wetness index, dissolved oxygen, electrical conductivity, permanganate index, and total nitrogen, respectively. • Topography, land use types, and hydroclimatic parameters affect the water quality. • Hydroclimatic and biogeochemical processes shape the seasonality of water quality. • Elevation and TWI have a synergistic influence on land use and water quality in the SRYR. The source region of the Yellow River (SRYR) plays a critical role in runoff formation and ecological function in the Yellow River Basin. However, comprehensive research on water quality in this basin remains relatively scarce. Exploring water quality across different spatial regions of the basin is, in fact, important for ensuring sustainable development in the region. In this context, the present study aims to assess the spatiotemporal variations in water quality in the SRYR in September 2021 and June 2022 using the Wilcoxon test, Spearman correlation analysis, clustering, and principal component analysis (PCA). The clustering results classified the water quality in the SRYR into three regions. The spatial variability in the water quality across the relatively undisturbed upper and middle reaches of the region was primarily governed by topographic features and land use types. In contrast, anthropogenic disturbances from agricultural activities and urbanization in the lower basin promoted the formation of biogeochemical hotspots, marked by high topographic wetness index values as well as elevated concentrations of organic matter, and heavy metals. Cluster analysis coupled with PCA revealed the major factors driving water quality in the study area. On the other hand, the structural equation model results indicated that climatic variables, such as temperature, have moderate effects on water quality. Specifically, hydrological transport processes (e.g., discharge rate) increased the concentrations of total nitrogen, total phosphorus, turbidity and selenium, but decreased the concentrations of nutrients and organic substances through dilution effects at the basin scale. This study highlights the significance of reducing agricultural expansion and implementing sustained water quality and hydroclimatic monitoring policies to effectively protect and predict water quality, enabling the development of proactive strategies to mitigate the effects of increasingly extreme and variable climate regimes.
Long et al. (Sat,) studied this question.