A coupled modeling approach to predict water quality in Lake Taihu, China: linkage to climate change projections
Climate change is expected to impact water quality and ecosystem health in water bodies. In this study, a modeling framework was developed to assess the response of environmental variables to climate change scenarios in Lake Taihu, China. A coupled hydrodynamic-water quality-sediment flux model was employed to simulate water quality processes under future climate scenarios projected from a general circulation model (GCM) forced by the Representative Concentration Pathway 8.5 (RCP 8.5). The results showed that the climate change impacted physico-chemical parameters and biological interactions in Lake Taihu. The annual average water temperature increased by 0.96, 2.09, and 3.2 °C by the 2020s, 2050s, and 2080s, respectively. Daily temperature stratification tended to occur earlier and the period of stratification increased, especially in summer during calm wind conditions. The sediment flux increased and dissolved oxygen (DO) concentration decreased with climate change. Additionally, climate change increased the onset time, duration, and areas of algal blooms. The results showed that the blooms activation time advanced approximately six days per decade. The onset time of algal blooms of 2080s was in February and March and the elevated concentration of chlorophyll a lasted until late autumn in the west lake region. The chlorophyll a concentration in summer did not increase substantially (about 10–15 μg/L). Overall, water management strategies and ecological restoration plans in Lake Taihu, mainly based on nutrient load reduction and hydrodynamic modification, should incorporate anticipated effects of climate change.
A coupled modeling approach to predict water quality in Lake Taihu, China: linkage to climate change projections.
Journal of Freshwater Ecology, 30(1),