湖泊科学2026,Vol.38Issue(1):65-77,中插11-中插13,16.DOI:10.18307/2026.0110
大型浅水湖泊叶绿素a浓度对高温热浪响应的模拟研究
Simulation study on the response of chlorophyll-a concentration to extreme heatwaves in a large shallow lake
摘要
Abstract
The world is getting hotter and hotter,causing more and more heatwaves.It is very important to study how these factors affect the environment,for example the nutrients in lakes,the concentration of chlorophyll-a(Chl.a)in water,and the growth of phytoplankton.This will help us to understand how lakes respond to and recover from heatwaves,and it will provide scientific sup-port for the management and regulation of lakes under climate change.This study used the GOTM-WET model to see what effect the 2022 summer heatwave had on the amount of Chl.a in northern Lake Taihu.It looked at how different levels of heatwave inten-sity affected Chl.a and what might be causing this.The results showed that the 2022 summer heatwave greatly reduced the concen-tration of Chl.a in water,and the effect of this was stronger with the higher heatwave intensity.Further analysis showed that the maximum water temperature during the 2022 heatwave exceeded 37 ℃,which could have been too hot for most algae to grow.The heatwave also made the water more mixed up,with less nitrogen and phosphorus in the surface layer and more in the bottom layer.This meant there was less nutrition available for surface algae growth,which also meant there was less Chl.a.This study looked at how water temperature and nutrients can affect the growth of algae in lakes when it is very hot.It helps us to understand more about how heatwaves affect the natural processes in lakes.关键词
太湖/夏季热浪/叶绿素a/总氮/总磷/GOTM-WET模型/梅梁湾Key words
Lake Taihu/summer heatwave/chlorophyll-a/total nitrogen/total phosphorus/GOTM-WET model/Meiliang Bay引用本文复制引用
Yue Lintan,Qin Boqiang,Yang Yifan,Zhuang Xinfeng,Chen Weiyu,Kong Xiangzhen,Deng Jianming,Zhao Zhonghua,Lu Yingcheng,Zhu Guangwei..大型浅水湖泊叶绿素a浓度对高温热浪响应的模拟研究[J].湖泊科学,2026,38(1):65-77,中插11-中插13,16.基金项目
国家重点研发计划项目(2022YFC3202004)、湖泊与流域水安全全国重点实验室重点项目(NKL2023-KP01)和国家自然科学基金项目(42371016,42220104010)联合资助. (2022YFC3202004)