Articles | Volume 27, issue 19
https://doi.org/10.5194/hess-27-3581-2023
https://doi.org/10.5194/hess-27-3581-2023
Research article
 | 
09 Oct 2023
Research article |  | 09 Oct 2023

Remote quantification of the trophic status of Chinese lakes

Sijia Li, Shiqi Xu, Kaishan Song, Tiit Kutser, Zhidan Wen, Ge Liu, Yingxin Shang, Lili Lyu, Hui Tao, Xiang Wang, Lele Zhang, and Fangfang Chen

Related authors

Characterization of chromophoric dissolved organic matter in lakes on the Tibet Plateau, China, using spectroscopic analysis
Kaishan Song, Sijia Li, Zhidan Wen, Lili Lyu, and Yingxin Shang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-259,https://doi.org/10.5194/bg-2018-259, 2018
Revised manuscript not accepted
Short summary

Related subject area

Subject: Rivers and Lakes | Techniques and Approaches: Remote Sensing and GIS
Hydrological regime of Sahelian small waterbodies from combined Sentinel-2 MSI and Sentinel-3 Synthetic Aperture Radar Altimeter data
Mathilde de Fleury, Laurent Kergoat, and Manuela Grippa
Hydrol. Earth Syst. Sci., 27, 2189–2204, https://doi.org/10.5194/hess-27-2189-2023,https://doi.org/10.5194/hess-27-2189-2023, 2023
Short summary
Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning
Antoine Di Ciacca, Scott Wilson, Jasmine Kang, and Thomas Wöhling
Hydrol. Earth Syst. Sci., 27, 703–722, https://doi.org/10.5194/hess-27-703-2023,https://doi.org/10.5194/hess-27-703-2023, 2023
Short summary
Long-term water clarity patterns of lakes across China using Landsat series imagery from 1985 to 2020
Xidong Chen, Liangyun Liu, Xiao Zhang, Junsheng Li, Shenglei Wang, Yuan Gao, and Jun Mi
Hydrol. Earth Syst. Sci., 26, 3517–3536, https://doi.org/10.5194/hess-26-3517-2022,https://doi.org/10.5194/hess-26-3517-2022, 2022
Short summary
Changes in glacial lakes in the Poiqu River basin in the central Himalayas
Pengcheng Su, Jingjing Liu, Yong Li, Wei Liu, Yang Wang, Chun Ma, and Qimin Li
Hydrol. Earth Syst. Sci., 25, 5879–5903, https://doi.org/10.5194/hess-25-5879-2021,https://doi.org/10.5194/hess-25-5879-2021, 2021
Short summary
Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept
Concetta Di Mauro​​​​​​​, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 4081–4097, https://doi.org/10.5194/hess-25-4081-2021,https://doi.org/10.5194/hess-25-4081-2021, 2021
Short summary

Cited articles

APHA/AWWA/WAF: Standard Methods for the Examination of Water and Wastewater, American Public Health Association, Washington, DC, https://doi.org/10.1080/23267224.1919.10651076, 1998. 
Aizaki, M.: Applications of Carlson's trophic state index to Japanese lakes and relationships between the index and other parameters, Int. Ver. Theor. Angew., 21, 675–681, https://cir.nii.ac.jp/crid/1572543024605566976, 1981. 
Binding, C. E., Jerome, J. H., Bukata, R. P., and Booty, W. G.: Trends in water clarity of the lower Great Lakes from remotely sensed aquatic color, J. Great Lakes Res., 33, 828–841, https://doi.org/10.3394/0380-1330(2007)33, 2007. 
Cao, Z., Ma, R., Duan, H., Pahlevan, N., Melack, J., Shen, M., and Xue, K.: A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes, Remote Sens. Environ., 248, 111974, https://doi.org/10.1016/j.rse.2020.111974, 2020 
Carlson, R.: A trophic state index for lakes 1, Limnol. Oceanogr., 22, 361–369, https://doi.org/10.4319/lo.1977.22.2.0361, 1977. 
Download
Short summary
1. Blue/red and green/red Rrs(λ) are sensitive to lake TSI. 2. Machine learning algorithms reveal optimum performance of TSI retrieval. 3. An accurate TSI model was achieved by MSI imagery data and XGBoost. 4. Trophic status in five limnetic regions was qualified. 5. The 10m TSI products were first produced in 555 typical lakes in China.