Algal blooms in Lake Taihu: Earlier onset and extended duration

Abstract

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.