Preprints
https://doi.org/10.5194/hess-2021-630
https://doi.org/10.5194/hess-2021-630
 
23 Feb 2022
23 Feb 2022
Status: a revised version of this preprint is currently under review for the journal HESS.

Long-term water clarity patterns of lakes across China using Landsat series imagery from 1985 to 2020

Xidong Chen1, Liangyun Liu2, Xiao Zhang2,3, Junsheng Li2,3, Shenglei Wang2, Yuan Gao4, and Jun Mi2,3 Xidong Chen et al.
  • 1North China University of Water Resources and Electric Power, Zhengzhou 450046, China
  • 2Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
  • 4Beijing Normal University, Beijing 100091, China

Abstract. Monitoring the water clarity of lakes is essential for the sustainable development of human society. However, existing water clarity assessments in China have mostly focused on lakes with areas > 1 km2, and the monitoring periods were mainly in the 21st century. In order to improve the understanding of spatiotemporal variations in lake clarity across China, based on the Google Earth Engine cloud platform, a 30 m long-term LAke Water Secchi Depth (SD) dataset (LAWSD30) of China (1985–2020) was first developed using Landsat series imagery and a robust water-color-parameter-based SD model. The LAWSD30 dataset exhibited a good performance compared with concurrent in situ SD datasets, with an R2 of 0.86 and a root-mean-square error of 0.225 m. Then, based on our LAWSD30 dataset, long-term spatiotemporal variations in SD for lakes > 0.01 km2 (N = 40,973) across China were evaluated. The results show that the SD of lakes with areas ≤ 1 km2 exhibited a significant downward trend in the period 1985–2020, but the decline rate began to slow down and stabilized after 2001. In addition, the SD of lakes with an area > 1 km2 showed a significant downward trend before 2001, and began to increase significantly afterwards. Moreover, in terms of the spatial patterns, the proportion of small lakes (area ≤ 1 km2) showing a decreasing SD trend was the largest in the Mongolian–Xinjiang Plateau Region (MXR) (about 30.0 %), and the smallest in the Eastern Plain Region (EPR) (2.6 %). In contrast, for lakes > 1 km2, this proportion was the highest in MXR (about 23.0 %), and the lowest in the Northeast Mountain Plain Region (NER) (16.1 %). The LAWSD30 dataset and the spatiotemporal patterns of lake water clarity in our research can provide effective guidance for the protection and management of lake environment in China.

Xidong Chen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-630', Anonymous Referee #1, 17 Mar 2022
    • AC1: 'Reply on RC1', Liangyun Liu, 19 Apr 2022
  • RC2: 'Comment on hess-2021-630', Anonymous Referee #2, 18 Mar 2022
    • AC2: 'Reply on RC2', Liangyun Liu, 19 Apr 2022

Xidong Chen et al.

Data sets

The 30 m long-term LAke Water Secchi Depth (SD) dataset (LAWSD30) of China (1985–2020) Xidong Chen; Liangyun Liu https://doi.org/10.5281/zenodo.5734071

Xidong Chen et al.

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Short summary
A 30 m LAke Water Secchi Depth (LAWSD30) dataset was first developed for 1985–2020, and a national-scale water clarity estimations of lakes in China over the past 35 years were analyzed. The lake clarity in China exhibited a significant downward trend before the 21st century, but improved after 2000. The developed LAWSD30 dataset and the evaluation results can provide effective guidance for the water preservation and restoration.