Impacts of Land Use Patterns and Associated Thresholds on Seasonal Water Quality Dynamics in a Typical Watershed of Qinling Mountains, China

Land use and landscape patterns strongly influence water quality and are critical for ecological conservation within watersheds, as well as for effective water resource management. This study analyzed water quality data collected from 11 monitoring sites in the Minjiahe Watershed of Qinling Mountains, China. Redundancy analysis was used to analyze the impact mechanism of multi-scale landscape patterns and land use on seasonal water quality changes, while non-parametric change point analysis was used to quantify the key landscape thresholds that lead to sudden changes in water quality. The results indicated that the concentrations of ammonia nitrogen, available phosphorus, and total nitrogen in the river water were significantly higher during the rainy season than during the dry season (p < 0.05), representing increases of 18.93%, 30.33%, and 37.52%, respectively. The dissolved oxygen levels were 27.76% higher in the dry season than in the rainy season (p < 0.05). Landscape metrics at different spatial scales can strongly explain the spatiotemporal changes in water quality, with an explanatory rate exceeding 76%. The interspersion and juxtaposition index of forestland (IJIfor), largest patch index of forestland (LPIfor), landscape shape index of residential land (LSIres), and percentage of landscape of farmland (PLANDfar) are the main factors affecting seasonal changes in water quality. Small and discontinuous grasslands did not significantly affect water quality. To effectively mitigate the impact of landscape patterns on water quality, the following thresholds are suggested as effective management targets: at the sub-watershed scale, IJIfor < 80% and LPIfor > 94%; at the 150 m buffer scale, LSIres < 8 and PLANDfar < 8%. These determined thresholds can be used as indicators for landscape planning to reduce the risk of water quality degradation. The research results provide valuable insights for sustainable land use and multi-scale landscape planning, thereby informing strategies to enhance water quality.