作者：Cui,C.,Pan,T.,Brookes,J.,Zhang,Q.,Qin,B.,Zhang,Y. & Zhu,G.

Elevated water temperatures accelerate nutrient cycling and metabolism in aquatic ecosystems. Eutrophic waters, such as Lake Taihu, historically has been suffered from cyanobacterial (Microcystis spp.) blooms, exhibiting heightened sensitivity to climate change. Nevertheless, the quantitative responses of this highly productive lake to future warming remains poorly predicted. This study employes a three-dimensional hydrodynamic model coupling a lake thermal model and cyanobacterial biomass model to project future water temperatures and associated phytoplankton biomass in Lake Taihu under multiple Shared Socioeconomic Pathways (SSPs), comparing scenarios for 2100 against current conditions (2015-2022 multi-year average). Results indicate that annual mean Lake Water Column Temperature (LWCT) will rise by 1.12 degrees C,2.15 degrees C,4.18 degrees C,and 4.97 degrees C under respective SSP scenarios,which is much higher than the global average increase of inland waters. The most pronounced warming occurs during autumn,while winter thermal stratification stability is projected to decline (vertical temperature deviation approach zero). Algal bloom intensity (by chlorophyll-a concentration) is projected to increase by 12.0%, 22.2%, 46.2% and 62.5%, indicating that climate warming may trigger extensive and severe blooms in highly productive waters. Sensitivity analyses reveal that a 40% nutrient reduction effectively controls cyanobacterial concentrations during 2060-2090 in all but the warmest scenario. These findings demonstrate that targeted nutrient mitigation can counteract the amplifying effects of climate warming on cyanobacterial blooms in eutrophic waters.

（来源：Journal of Hydrology 2025   DOI: 10.1016/j.jhydrol.2025.133716）