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Water clarity annual dynamics (1984-2018) dataset across China derived from Landsat images in Google Earth Engine.

Authors :
Tao, Hui
Song, Kaishan
Liu, Ge
Wang, Qiang
Wen, Zhidan
Jacinthe, Pierre-Andre
Xu, Xiaofeng
Du, Jia
Shang, Yingxin
Li, Sijia
Wang, Zongming
Lyu, Lili
Hou, Junbin
Wang, Xiang
Liu, Dong
Shi, Kun
Zhang, Baohua
Duan, Hongtao
Source :
Earth System Science Data Discussions; 7/22/2021, p1-21, 21p
Publication Year :
2021

Abstract

Water clarity provides a sensitive tool to examine spatial pattern and historical trend in lakes trophic status. Yet, this metric has insufficiently been explored despite the availability of remotely-sensed data. We used three Secchi disk depth (SDD) datasets for model calibration and validation from different field campaigns mainly conducted during 2004-2018. The red/blue band ratio algorithm was applied to map SDD for lakes (> 1 ha) based on the first SDD dataset, where R<superscript>2</superscript> = 0.79, RMSE = 100.3 cm, rRMSE = 61.9 %, MAE = 57.7 cm. The other two datasets were used to validate the SDD estimation model, which were indicated the model had a stable performance of temporal transferability. The annual mean SDD of lakes were retrieved across China using Landsat top of air reflectance products in GEE from 1984 to 2018. The spatiotemporal dynamics of SDD were analysed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found that the lakes with SDDs < 2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total area of lakes with SDD between 0-0.5 m and > 4 m were the largest, accounting for 48.28 % of the total lakes. During 1984-2018, lakes in the Tibetan-Qinghai Plateau lake region (TQR) had the clearest water with an average value of 3.32 ± 0.38 m, while that in the Northeastern lake region (NLR) exhibited the lowest SDD (mean: 0.60 ± 0.09 m). Among the 10,814 lakes with SDD results more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia-Xinjiang lake region (MXR), more than half of the total lakes in every other lake region exhibited significant increasing trends. In the Eastern lake region (ELR), NLR and Yungui Plateau lake region (YGR), almost more than 50 % of the lakes that displayed an increase or decrease in SDD were mainly distributed in an area of 0.01-1 km<superscript>2</superscript>, whereas that in the TQR and MXR were primarily concentrated in large lakes (> 10 km<superscript>2</superscript>). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset can now be accessed through the website of the National Tibetan Plateau Data Center (http://data.tpdc.ac.cn): DOI: 10.11888/Hydro.tpdc.271571. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18663591
Database :
Complementary Index
Journal :
Earth System Science Data Discussions
Publication Type :
Academic Journal
Accession number :
151515015
Full Text :
https://doi.org/10.5194/essd-2021-227