The identification of key influencing factors and their critical values for the prevention and control of water bloom in lakes is of great significance. Taking Wuhan South Lake as the study area, based on hydrological, water quality and meteorological monitoring data, Pearson Correlation Analysis, Gray Correlation Analysis and Principal Component Analysis were used to screen and identify key environmental factors with high correlation with chlorophyll a concentration, and the critical values of key environmental impact factors were analyzed by the Receiver Operating Characteristic (ROC) curve method. The results show that the CODMn, total phosphorus, total nitrogen, water temperature and air temperature had strong correlations with chlorophyll a concentration and were the key factors for water bloom outbreak, with the critical values of 6.25 mg/L, 0.146 mg/L, 0.725 mg/L, 27.05 ℃ and 22.35 ℃, respectively. It was found that the accuracy of the ROC curve method for solving the critical values of CODMn, total phosphorus, total nitrogen and other environmental factors with small daily variation was better than that of environmental factors with large daily variation such as air temperature and water temperature, and the ROC curve method has a greater advantage in determining the critical values of nutrient concentrations for water blooms in lakes.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |