Chen Jiangzhaoxia, Gao Xiaojie, Xu Xiaoke, Zhu Chongjing, She Xiaojun, Kong Debing, Xue Kun, Li Yao
Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, PR China.
Harvard Forest, Harvard University, Petersham 01366, USA.
Harmful Algae. 2025 Sep;148:102917. doi: 10.1016/j.hal.2025.102917. Epub 2025 Jul 5.
Monitoring algal bloom phenology is crucial for managing water quality in eutrophic lakes, particularly under changing climate and environmental conditions. However, the lack of reliable long-term data has limited our understanding of bloom dynamics in inland lakes. Here, we analyzed the spatiotemporal characteristics of algal bloom phenology in Lake Taihu using daily MODIS data from 2000 to 2023. The floating algae index (FAI) and Bayesian land surface phenology (BLSP) model were applied to quantify bloom patterns and explore their climatic and environmental drivers. Over the past 24 years, algal bloom coverage in Lake Taihu averaged 19.88 %, with severe events occurring in 2007 and 2017, reaching frequencies of 9.54 % and 10.60 % and coverages of 42.92 % and 41.10 %, respectively. Bloom durations ranged from 60 to 90 days, typically starting between March and June and ending between July and December. Notably, since 2015, blooms have shown a tendency to start earlier, persist longer, and end later. Bloom phenology was primarily driven by water quality, with wind speed and cumulative evaporation also playing significant roles. These findings provide new insights into the driving mechanisms behind algal bloom phenology and serve as a scientific basis for developing effective lake ecological management strategies and water quality improvement initiatives.
监测藻华物候对于富营养化湖泊的水质管理至关重要，尤其是在气候变化和环境条件不断变化的情况下。然而，缺乏可靠的长期数据限制了我们对内陆湖泊藻华动态的理解。在此，我们利用2000年至2023年的每日MODIS数据，分析了太湖藻华物候的时空特征。应用浮游藻类指数（FAI）和贝叶斯地表物候（BLSP）模型来量化藻华模式，并探索其气候和环境驱动因素。在过去24年中，太湖的藻华覆盖面积平均为19.88%，2007年和2017年发生了严重事件，频率分别达到9.54%和10.60%，覆盖面积分别为42.92%和41.10%。藻华持续时间为60至90天，通常在3月至6月开始，7月至12月结束。值得注意的是，自2015年以来，藻华呈现出开始更早、持续时间更长、结束更晚的趋势。藻华物候主要受水质驱动，风速和累积蒸发量也发挥着重要作用。这些发现为藻华物候背后的驱动机制提供了新的见解，并为制定有效的湖泊生态管理策略和水质改善举措提供了科学依据。
