Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31423
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dc.contributor.authorWang, Shengleien_UK
dc.contributor.authorLi, Junshengen_UK
dc.contributor.authorZhang, Bingen_UK
dc.contributor.authorLee, Zhongpingen_UK
dc.contributor.authorSpyrakos, Evangelosen_UK
dc.contributor.authorFeng, Lianen_UK
dc.contributor.authorLiu, Chongen_UK
dc.contributor.authorZhao, Honglien_UK
dc.contributor.authorWu, Yanhongen_UK
dc.contributor.authorZhu, Lipingen_UK
dc.contributor.authorJia, Limingen_UK
dc.contributor.authorWan, Weien_UK
dc.contributor.authorZhang, Fangfangen_UK
dc.contributor.authorShen, Qianen_UK
dc.contributor.authorTyler, Andrew Nen_UK
dc.contributor.authorZhang, Xianfengen_UK
dc.date.accessioned2020-07-14T00:09:48Z-
dc.date.available2020-07-14T00:09:48Z-
dc.date.issued2020-09-15en_UK
dc.identifier.other111949en_UK
dc.identifier.urihttp://hdl.handle.net/1893/31423-
dc.description.abstractWater 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.en_UK
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.relationWang 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.2020.111949en_UK
dc.rightsThis 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.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectSecchi disk depthen_UK
dc.subjectLakes and reservoirsen_UK
dc.subjectMODISen_UK
dc.subjectFUIen_UK
dc.subjectHue angleen_UK
dc.subjectWater clarity changesen_UK
dc.titleChanges of water clarity in large lakes and reservoirs across China observed from long-term MODISen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1016/j.rse.2020.111949en_UK
dc.citation.jtitleRemote Sensing of Environmenten_UK
dc.citation.issn1879-0704en_UK
dc.citation.issn0034-4257en_UK
dc.citation.volume247en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderChinese Arbitration Associationen_UK
dc.author.emailevangelos.spyrakos@stir.ac.uken_UK
dc.citation.date27/06/2020en_UK
dc.contributor.affiliationPeking Universityen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationUniversity of Massachusetts at Bostonen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationSouthern University of Science and Technologyen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationChina Institute of Water Resources and Hydropower Researchen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationPeking Universityen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationChinese Academy of Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationPeking Universityen_UK
dc.identifier.isiWOS:000549189200047en_UK
dc.identifier.scopusid2-s2.0-85086897159en_UK
dc.identifier.wtid1644146en_UK
dc.contributor.orcid0000-0003-0604-5827en_UK
dc.date.accepted2020-06-08en_UK
dcterms.dateAccepted2020-06-08en_UK
dc.date.filedepositdate2020-07-13en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorWang, Shenglei|en_UK
local.rioxx.authorLi, Junsheng|en_UK
local.rioxx.authorZhang, Bing|en_UK
local.rioxx.authorLee, Zhongping|en_UK
local.rioxx.authorSpyrakos, Evangelos|en_UK
local.rioxx.authorFeng, Lian|en_UK
local.rioxx.authorLiu, Chong|en_UK
local.rioxx.authorZhao, Hongli|en_UK
local.rioxx.authorWu, Yanhong|en_UK
local.rioxx.authorZhu, Liping|en_UK
local.rioxx.authorJia, Liming|en_UK
local.rioxx.authorWan, Wei|en_UK
local.rioxx.authorZhang, Fangfang|en_UK
local.rioxx.authorShen, Qian|en_UK
local.rioxx.authorTyler, Andrew N|0000-0003-0604-5827en_UK
local.rioxx.authorZhang, Xianfeng|en_UK
local.rioxx.projectProject ID unknown|Chinese Arbitration Association|en_UK
local.rioxx.freetoreaddate2020-07-13en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nc-nd/4.0/|2020-07-13|en_UK
local.rioxx.filename1-s2.0-S0034425720303199-main.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1879-0704en_UK
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