基于多源数据的巢湖蓝藻水华时空分布及驱动因素分析

富营养化和有害藻类水华暴发是全世界淡水湖泊共同面临的生态环境问题之一.巢湖作为典型的内陆淡水湖泊,其富营养化水平和蓝藻水华暴发面积常年居高不下,且在各湖区表现为一定的时空分布差异.为认识和了解不同阶段巢湖蓝藻水华发生和发展基本规律,利用巢湖水上综合观测平台和卫星遥感等多源数据,获得2015~2020年水体中藻密度和水华面积的时空分布信息,并采用基于增强回归树的机器学习算法,定量评估不同阶段各环境因子对蓝藻水华影响的重要程度及相互作用关系.结果表明：①巢湖蓝藻水华表现出较大的季节变化特征,蓝藻细胞在春季开始复苏,主要在巢湖西半湖和沿岸地区形成轻度水华,水体藻密度在夏、秋季达到最大,该季节发生中等程度以上的水华频率较高.②非暴发期间,巢湖藻密度变化受物理和化学因素影响较大,二者对解释藻密度方差变化的贡献率可达80.3%,水体中高浓度溶解氧、弱碱性pH值（7.2~7.6）和适宜水温（3℃）是藻类细胞生长繁殖的有利环境条件,巢湖蓝藻水华首次暴发一般在气温稳定通过7℃初日11 d前后出现.③暴发期内,巢湖蓝藻水华发生主要受藻类生物量和气象条件的综合影响,气温、藻密度、日照时数和风速的累计贡献率为95%,各因子均存在一个有利于蓝藻水华发生的最适区间.多因子交互作用分析结果显示,在水体藻密度大、气温适宜和微风的综合作用下,巢湖蓝藻水华发生概率较高.上述研究成果分析和揭示了不同阶段巢湖蓝藻水华的时空分布特征及其主导影响因子,可为巢湖蓝藻水华防控和预测、预警提供科学依据.

Analysis of the Spatiotemporal Distribution of Algal Blooms and Its Driving Factors in Chaohu Lake Based on Multi-source Datasets

Eutrophication and harmful algae blooms are one of the common ecological and environmental problems faced by freshwater lakes all over the world. As a typical inland freshwater lake, Chaohu Lake exhibits a high level of eutrophication and algae blooms year-round and shows a spatiotemporal difference in different regions of the lake. In order to understand the basic regularity of the development and outbreak of algal blooms in Chaohu Lake, the data from the comprehensive water observation platform and remote sensing were integrated to obtain the spatiotemporal distribution of algal blooms from 2015 to 2020. Then, an evaluation model based on Boosted Regression Trees (BRT) was constructed to quantitatively assess the importance and interactions of various environmental factors on algal blooms at different stages. The results indicated that:① The occurrence of algal blooms in Chaohu Lake exhibited significant seasonal variations, with the cyanobacteria beginning to recover in spring and bring about a light degree of algal blooms in the western and coastal areas of Chaohu Lake. The density of cyanobacteria reached its maximum in summer and autumn, accompanied by moderate and severe degrees of algal bloom outbreaks. ② During the non-outbreak period, the variation in the cyanobacteria density was greatly affected by physical and chemical factors, which explained 80.3% of the variance in the change in cyanobacteria density. The high concentrations of dissolved oxygen content in the water column and the weak alkalinity (7.2-7.6) and appropriate water temperature (about 3℃) provided a favorable environmental condition for the breeding and growth of cyanobacteria. In addition, the onset of algal blooms was closely related to the air temperature steadily passing through the threshold. According to the statistics, the date of first outbreak of algal blooms in Chaohu Lake was 11 days or so after the air temperature steadily remained above 7℃. ③ During the outbreak period, the occurrence of algal blooms was influenced by the combination of cyanobacterial biomass and meteorological conditions such as temperature, wind speed, and sunshine duration. The cumulative contribution ratio of the four factors was as high as 95%, and each factor had an optimal interval conductive to the outbreak of algal blooms. Furthermore, the results of multi-factor interaction analysis indicated a larger probability of the outbreak of algal blooms in Chaohu Lake under the combined effect of high cyanobacteria density, suitable temperature, and the breeze. This study analyzed and revealed the spatiotemporal characteristics and the dominant influencing factors of algal blooms in Chaohu Lake at different stages, which could provide the scientific basis for the prediction, early warning, and disposal of algal blooms under the context of climate change.