Satellites unveil long-term phenological shifts and environmental drivers of algal blooms in plateau lakes of southwestern China

In recent years, the ecosystems of plateau lakes have encountered notable challenges characterized by a surge in the frequency of algal blooms (ABs), thereby presenting a substantial threat to both human well-being and ecosystem integrity. While the existing satellite-based monitoring of ABs, there still remains a scarcity of systematic analysis of AB phenology. This study focuses on five representative plateau lakes in Yunnan Province, China, namely Dianchi, Erhai, Xingyun, Qilu, and Chenghai, all of which have encountered occurrences of ABs. By integrating high-spatial-resolution Landsat and Sentinel-2 satellite data from 1987 to 2023, we derived the long-term sequences and phenological patterns of AB areas in these lakes using the Floating Algae Index (FAI) and the threshold segmentation method. The findings demonstrated a notable upward trend in the monthly average percentage of bloom areas across these studied lakes, except for Lake Dianchi. Particularly noteworthy were the substantial increases observed in Lake Xingyun (slope = 0.94, p < 0.01) and Qilu (slope = 0.46, p < 0.01). Additionally, the annual frequency of ABs across these lakes demonstrated an initial increase followed by a subsequent decline from 1987 to 2023, with the highest frequency observed during the summer and autumn months. Correlation analysis revealed that the magnitude of the four-year cycle monthly average percentage of bloom area was primarily linked to water quality parameters related to lake pollution (r = 0.35, p < 0.01) and eutrophication (r = 0.34, p < 0.01). Conversely, the frequency of AB on a four-year cycle correlated with meteorological factors, including mean spring air temperature (r = 0.35, p < 0.05) and winter wind speed (r = 0.31, p < 0.05). Furthermore, the termination time of ABs was influenced by mean winter precipitation (r = 0.3, p < 0.05) and four-year cycle surface water temperature (r = 0.36, p < 0.05). This study elucidated the persistent phenological patterns of ABs in plateau lakes and explored the underlying mechanisms driven by multiple environmental factors. These findings would enhance comprehension regarding the evolution and mitigation of ABs, thereby facilitating the prediction and control of ABs in the context of more complex climate changes and anthropogenic impacts.