Potential of Mie–Fluorescence–Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters

Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the fi...

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Bibliographic Details
Published in:Environmental science & technology 2023-09, Vol.57 (38), p.14226-14236
Main Authors: Zhao, Hongkai, Zhou, Yudi, Wu, Hongda, Kutser, Tiit, Han, Yicai, Ma, Ronghua, Yao, Ziwei, Zhao, Huade, Xu, Peituo, Jiang, Chengchong, Gu, Qiuling, Ma, Shizhe, Wu, Lingyun, Chen, Yang, Sheng, Haiyan, Wan, Xueping, Chen, Wentai, Chen, Xiaolong, Bai, Jian, Wu, Lan, Liu, Qun, Sun, Wenbo, Yang, Suhui, Hu, Miao, Liu, Chong, Liu, Dong
Format: Article
Language:English
Subjects:
Aquatic ecosystems
Biogeochemical Cycling
Chlorophyll
Ecological monitoring
Ecosystems
Fluorescence
Inland waters
Lidar
Parameterization
Phytoplankton
Plankton
Primary production
Remote sensing
Trophic levels
Trophic status
Vertical distribution
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Summary:Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the first Mie–fluorescence–Raman lidar (MFRL) measurements of continuous chlorophyll a (Chl-a) profiles as well as their parametrization in inland water. The lidar-measured Chl-a during several experiments showed good agreement with the in situ data. A case study verified that MFRL had the potential to profile the Chl-a concentration. The results revealed that the maintenance of subsurface chlorophyll maxima (SCM) was influenced by light and nutrient inputs. Furthermore, inspired by the observations from MFRL, an SCM model built upon surface Chl-a concentration and euphotic layer depth was proposed with root mean square relative difference of 16.5% compared to MFRL observations, providing the possibility to map 3D Chl-a distribution in aquatic ecosystems by integrated active–passive remote sensing technology. Profiling and modeling Chl-a concentration with MFRL are expected to be of paramount importance for monitoring inland water ecosystems and environments.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.3c04212