滇池作为中国重要的淡水湖泊,其水质时空变化特征及富营养化状况备受关注。基于综合水质指数(WQI)及对数型幂函数普适指数公式,对滇池2021—2023年国控断面监测点水质及富营养状况进行评价与分析。结果表明:滇池水质评价等级分为一般、中等、良好3类,时间上夏季良好占比最少且WQI平均值最低,为水质最差季节,空间上草海水质优于外海。富营养等级分为中营养、轻度富营养、中度富营养3类,时间上春季滇池的富营养化问题最为严重,空间上草海的富营养化程度显著高于外海。造成这种时空差异性的原因是,水质方面主要受降雨、温度等因素的调控,富营养化程度则与光照强度、区域植物数量差异等因素相关。研究成果可为滇池水环境保护和可持续发展提供科学依据。

[Objective] Dianchi Lake, an important freshwater lake in Southwest China, has experienced increasing water quality degradation and eutrophication in recent years due to urbanization and agricultural activities. Most existing studies primarily focus on interannual variations, with limited understanding of seasonal variation and spatial heterogeneity. This study aims to: (1) reveal the spatiotemporal distribution patterns of water quality in Dianchi Lake using the Water Quality Index (WQI) method; (2) evaluate eutrophication dynamics using a logarithmic power-function universal index; and (3) identify key driving factors to provide scientific support for targeted remediation strategies. [Methods] Using daily water quality data from 2021 to 2023 at ten nationally controlled monitoring stations in Dianchi Lake, the WQI—incorporating six indicators (TP, TN, COD_Mn, NH₃-N, DO, and turbidity)—was employed to classify water quality levels. Eutrophication Index (EI) calculated using the logarithmic power function model including Chl-a, TN, TP, and COD_Mn, was applied to evaluate eutrophication levels. Spatial patterns were depicted using Kriging interpolation in ArcGIS, and correlation analysis was conducted to identify the major influencing factors. [Results] 1) Spatiotemporal characteristics of WQI: (a) regarding temporal variations, the mean WQI was 65.03 (ranging from 31.33 to 82.67), with “moderate” water quality prevailing. Water quality was poorest in summer (only 16% rated “good”), primarily due to high temperatures accelerating organic decomposition, leading to decreased DO (8.40 mg/L) and increased COD_Mn (6.29 mg/L). Water quality was best in winter. (b) In terms of spatial variations, the average WQI in Caohai (68.96) was significantly higher than that in the Waihai (64.01), attributed to nutrient absorption by wetland vegetation. Severe pollution accumulation was observed in the central Waihai (e.g., Guanyinshan monitoring station) due to limited water exchange. 2) Dynamics of EI: (a) for seasonal patterns, eutrophication was most severe in spring, with an average EI of 55.166, and 16.8% of the area reached a “moderate eutrophication” level, due to runoff inputs during the peak agricultural fertilization season. Summer exhibited the greatest variation in EI (38.102-87.603), accompanied by frequent algal blooms. (b) In light of spatial differentiation, EI values in Caohai were generally higher than those in Waihai,particularly at Duanqiao and the center of Caohai, where direct urban sewage discharge was significant. In northern Waihai, areas such as Luojiaying exhibited higher eutrophication levels due to intensive human activities. 3) Key driving factors: (a) WQI was strongly positively correlated with DO (+0.492), and negatively correlated with NH₃-N (-0.485) and COD_Mn (-0.358), indicating that organic pollution primarily drove water quality variation. (b) EI was mainly influenced by TP (with a weight of 0.230) and Chl-a (0.326), suggesting that phosphorus control and algae management were crucial for mitigating eutrophication. [Conclusions] Dianchi Lake exhibits pronounced seasonal and spatial heterogeneity in both water quality and eutrophication. In summer, nonpoint source pollution should be strictly controlled, while in spring, agricultural fertilization should be limited. The ecological restoration experiences in Caohai could be extended to Waihai, and enhanced water circulation is needed in the deep-water central zone. This study innovatively integrates the WQI and EI models, establishing a replicable methodological framework for dynamic assessment of eutrophic lakes, and emphasizes the need for long-term monitoring data to refine management strategies.