title: [Estimation and forecast of chlorophyll a concentration in Taihu Lake based on ensemble square root filters].
abstract: Chlorophyll a concentration is one of the important parameters for the characterization of water quality, which reflects the degree of eutrophication and algae content in the water body. It is also an important factor in determining water spectral reflectance. Chlorophyll a concentration is an important water quality parameter in water quality remote sensing. Remote sensing quantitative retrieval of chlorophyll a concentration can provide new ideas and methods for the monitoring and evaluation of lake water quality. In this work, we developed a data assimilation scheme based on ensemble square root filters and three-dimensional numerical modeling for wind-driven circulation and pollutant transport to assimilate the concentration of chlorophyll a. We also conducted some assimilation experiments using buoy observation data on May 20, 2010. We estimated the concentration of chlorophyll a in Taihu Lake, and then used this result to forecast the concentration of chlorophyll a. During the assimilation stage, the root mean square error reduced from 1.58, 1.025, and 2.76 to 0.465, 0.276, and 1.01, respectively, and the average relative error reduced from 0.2 to 0.05, 0.046, and 0.069, respectively. During the prediction stage, the root mean square error reduced from 1.486, 1.143, and 2.38 to 0.017, 0.147, and 0.23, respectively, and the average relative error reduced from 0.2 to 0.002, 0.025, and 0.019, respectively. The final results indicate that the method of data assimilation can significantly improve the accuracy in the estimation and prediction of chlorophyll a concentration in Taihu Lake.
authors.affiliation: Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210046, China. liyuannjnu@163.com
authors.forename: Yuan
authors.initials: Y
authors.lastname: Li
authors.forename: Yun-Mei
authors.initials: YM
authors.lastname: Li
authors.forename: Qiao
authors.initials: Q
authors.lastname: Wang
authors.forename: Zhuo
authors.initials: Z
authors.lastname: Zhang
authors.forename: Fei
authors.initials: F
authors.lastname: Guo
authors.forename: Heng
authors.initials: H
authors.lastname: Lü
authors.forename: Kun
authors.initials: K
authors.lastname: Bi
authors.forename: Chang-Chun
authors.initials: CC
authors.lastname: Huang
authors.forename: Yu-Long
authors.initials: YL
authors.lastname: Guo
mesh_terms: D002681:China; D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D004784:Environmental Monitoring / Q000379:methods / Q000706:statistics & numerical data*; D005068:Eutrophication; D005544:Forecasting; D060106:Lakes / Q000737:chemistry*; D008962:Models, Theoretical; D014876:Water Pollution / Q000032:analysis*; D060753:Water Quality
chemical_list: D002734:Chlorophyll; D000077194:Chlorophyll A