Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31423
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS
Author(s): Wang, Shenglei
Li, Junsheng
Zhang, Bing
Lee, Zhongping
Spyrakos, Evangelos
Feng, Lian
Liu, Chong
Zhao, Hongli
Wu, Yanhong
Zhu, Liping
Jia, Liming
Wan, Wei
Zhang, Fangfang
Shen, Qian
Tyler, Andrew N
Zhang, Xianfeng
Contact Email: evangelos.spyrakos@stir.ac.uk
Keywords: Secchi disk depth
Lakes and reservoirs
MODIS
FUI
Hue angle
Water clarity changes
Issue Date: 15-Sep-2020
Date Deposited: 13-Jul-2020
Citation: Wang S, Li J, Zhang B, Lee Z, Spyrakos E, Feng L, Liu C, Zhao H, Wu Y, Zhu L, Jia L, Wan W, Zhang F, Shen Q, Tyler AN & Zhang X (2020) Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS. Remote Sensing of Environment, 247, Art. No.: 111949. https://doi.org/10.1016/j.rse.2020.111949
Abstract: Water clarity is a well-established first-order indicator of water quality and has been used globally by water regulators in their monitoring and management programs. Assessments of water clarity in lakes over large temporal and spatial scales, however, are rare, limiting our understanding of its variability and the driven forces. In this study, we developed and validated a robust Secchi disk depth (ZSD) algorithm for lakes across China based on two water color parameters, namely Forel-Ule Index (FUI) and hue angle α, retrieved from MODIS data. The MODIS ZSD model shows good results when compared with in-situ measurements from 17 lakes, with a 27.4% mean relative difference (MRD) in the validation dataset. Compared with other empirical ZSD models, our FUI and α-based model demonstrates improved performance and adaptability over a wide range of water clarity and trophic states. This algorithm was subsequently applied to MODIS measurements to provide a comprehensive assessment of water clarity in large lakes (N = 153) across China for the first time. The mean summer ZSD of the studied lakes between 2000 and 2017 demonstrated marked spatial and temporal variations. Spatially, the ZSD of large lakes presented a distinct spatial pattern of “high west and low east” over China. This spatial pattern was found to be associated with the significant differences in lake depth and altitude between west and east China while China's population, GDP, temperature, and precipitation distribution have also contributed to a certain extent. Temporally, the ZSD of most lakes increased during this period, with an overall mean rate of 3.3 cm/yr for all lakes. Here, 38.6% (N = 59) of the lakes experienced a significant increase in their ZSD value during the past 18 years while only 8.5% (N = 13) showed a significant decreasing trend. Significant increases in lake ZSD were observed in west China, which were found to correlate with the increase of air temperature and lake surface area. This is possibly a response of the lakes in west China to climate change. In the lake systems of east China, which are predominately used as a drinking water source, the increase in lake ZSD was found to be strongly correlated with changes in local GDP (gross domestic production), NDVI (normalized difference vegetation index) and lake surface area, suggesting a combined effect of the implemented management practices and climatic variability. The results of this study provide important information for water quality conservation and management in China, and also highlight the value of satellite remote sensing in monitoring water quality over lakes at a large scale and long-term.
DOI Link: 10.1016/j.rse.2020.111949
Rights: This article is available under the Creative Commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed. For commercial reuse, permission must be requested.
Licence URL(s): http://creativecommons.org/licenses/by-nc-nd/4.0/

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