{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T05:42:09Z","timestamp":1761198129825,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Project of China","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Young Scientist Group Project of Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}]},{"name":"Chinese Academy of Sciences granted to Yingxin Shang, Central Government Guides Local Funds for Scientific and Technological Development","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}]},{"name":"Research instrument and equipment development project of Chinese Academy of Sciences","award":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"],"award-info":[{"award-number":["2021YFD1500101","42171374","42171385","42071336","2020M681056","2022QNXZ03","202002047JC","YJKYYQ20190044"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water clarity (Secchi disk depth, SDD) provides a sensitive tool to examine the spatial pattern and historical trend in lakes\u2019 trophic status. However, this metric has been insufficiently explored despite the availability of remotely-sensed data. Based on the published SDD datasets derived from Landsat images, we analyzed the spatial and inter-annual variations in water clarity and examined the impact of natural and anthropogenic factors on these trends at multiple scales, i.e., five lake regions, provinces, and watersheds. Lake clarity was lowest in Northeast (0.60 \u00b1 0.09 m) and East China (1.23 \u00b1 0.17 m) and highest in the Tibet Plateau (3.32 \u00b1 0.38 m). Over the past 35 years, we found a significant trend of increased SDD in 18 (out of 32) provinces (only Yunnan province exhibited a significant decreasing trend) and in 77 (out of 155) watersheds (only 5 watersheds showed a significant decreasing trend). Lakes in eastern-northeastern China exhibited a higher probability of decreasing trend, while the trend was inverse for lakes in the Tibet-Qinghai region. The results of water clarity interannual change trends showed they were closely related to the spatial scale of analysis. At the watershed level, these trends were mainly driven by anthropogenic factors, with night-time brightness (13.84%), agricultural fertilizer use (11.17%), and wastewater (9.64%) being the most important. Natural factors (temperature, wind, and NDVI) explained about 18.2% of the SDD variance. Our findings for the SDD spatio-temporal trend provide valuable information for guiding water protection management policy-making and reinforcement in China.<\/jats:p>","DOI":"10.3390\/rs14205091","type":"journal-article","created":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T22:45:29Z","timestamp":1665614729000},"page":"5091","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Analysis of Spatio-Temporal Dynamics of Chinese Inland Water Clarity at Multiple Spatial Scales between 1984 and 2018"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0821-1473","authenticated-orcid":false,"given":"Hui","family":"Tao","sequence":"first","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"School of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaishan","family":"Song","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"College of Urban Research and Planning, Liaocheng University, Liaocheng 252000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ge","family":"Liu","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"School of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8801-5324","authenticated-orcid":false,"given":"Zhidan","family":"Wen","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junbin","family":"Hou","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingxin","family":"Shang","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sijia","family":"Li","sequence":"additional","affiliation":[{"name":"Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,12]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Limnology: Lake and River Ecosystems","volume":"21","author":"Wetzel","year":"2001","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"25491","DOI":"10.1073\/pnas.1910872116","article-title":"Inland water bodies in China: Features discovered in the long-term satellite data","volume":"116","author":"Feng","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1016\/j.envpol.2016.08.078","article-title":"Deep challenges for China\u2019s war on water pollution","volume":"218","author":"Han","year":"2016","journal-title":"Environ. Pollut."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1038\/ngeo2967","article-title":"Decline in Chinese lake phosphorus concentration accompanied by shift in sources since 2006","volume":"10","author":"Tong","year":"2017","journal-title":"Nat. Geosci."},{"doi-asserted-by":"crossref","unstructured":"Ma, T., Zhao, N., Ni, Y., Yi, J.W., Wilson, J.P., He, L.H., Du, Y.Y., Pei, T., Zhou, C.H., and Song, C. (2020). China\u2019s improving inland surface water quality since 2003. Sci. Adv., 6.","key":"ref_6","DOI":"10.1126\/sciadv.aau3798"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s10666-015-9472-4","article-title":"Eutrophication Prediction Using a Markov Chain Model: Application to Lakes in the Yangtze River Basin, China","volume":"21","author":"Huang","year":"2016","journal-title":"Environ. Model. Assess."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2327","DOI":"10.1111\/gcb.16077","article-title":"Global divergent trends of algal blooms detected by satellite during 1982\u20132018","volume":"28","author":"Fang","year":"2022","journal-title":"Glob. Chang. Biol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"11566","DOI":"10.1073\/pnas.1920759117","article-title":"Improvement in municipal wastewater treatment alters lake nitrogen to phosphorus ratios in populated regions","volume":"117","author":"Tong","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1038\/s41893-019-0220-7","article-title":"China and India lead in greening of the world through land-use management","volume":"2","author":"Chen","year":"2019","journal-title":"Nat. Sustain."},{"unstructured":"SOEE (2018). Report on the State of the Ecology and Environment of China in 2018, Environmental Publishing House.","key":"ref_11"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"598","DOI":"10.2134\/jeq2010.0300","article-title":"Monitoring Nitrogen Loading and Retention in an Urban Stormwater Detention Pond","volume":"40","author":"Rosenzweig","year":"2011","journal-title":"J. Environ. Qual."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"361","DOI":"10.4319\/lo.1977.22.2.0361","article-title":"A Trophic State Index for Lakes","volume":"22","author":"Carlson","year":"1977","journal-title":"Limnol. Oceanogr."},{"doi-asserted-by":"crossref","unstructured":"Pu, J., Song, K., Lv, Y., Liu, G., Fang, C., Hou, J., and Wen, Z. (2022). Distinguishing Algal Blooms from Aquatic Vegetation in Chinese Lakes Using Sentinel 2 Image. Remote Sens., 14.","key":"ref_14","DOI":"10.3390\/rs14091988"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/j.envpol.2018.11.058","article-title":"Quantifying the trophic status of lakes using total light absorption of optically active components","volume":"245","author":"Wen","year":"2019","journal-title":"Environ. Pollut."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"111950","DOI":"10.1016\/j.rse.2020.111950","article-title":"Sentinel-3 OLCI observations of water clarity in large lakes in eastern China: Implications for SDG 6.3.2 evaluation","volume":"247","author":"Shen","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2461","DOI":"10.1016\/j.watres.2010.01.012","article-title":"Spectral fluorometric characterization of phytoplankton community composition using the Algae Online Analyser (R)","volume":"44","author":"Richardson","year":"2010","journal-title":"Water Res."},{"doi-asserted-by":"crossref","unstructured":"Olmanson, L.G., Brezonik, P.L., and Bauer, M.E. (2011). Evaluation of medium to low resolution satellite imagery for regional lake water quality assessments. Water Resour. Res., 47.","key":"ref_18","DOI":"10.1029\/2011WR011005"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.isprsjprs.2020.10.014","article-title":"Water clarity changes in 64 large alpine lakes on the Tibetan Plateau and the potential responses to lake expansion","volume":"170","author":"Pi","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"111800","DOI":"10.1016\/j.rse.2020.111800","article-title":"Quantification of lake clarity in China using Landsat OLI imagery data","volume":"243","author":"Song","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/S0034-4257(02)00022-6","article-title":"A procedure for regional lake water clarity assessment using Landsat multispectral data","volume":"82","author":"Kloiber","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4086","DOI":"10.1016\/j.rse.2007.12.013","article-title":"A 20-year Landsat water clarity census of Minnesota\u2019s 10,000 lakes","volume":"112","author":"Olmanson","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1364\/AO.22.000020","article-title":"Phytoplankton pigment concentrations in the middle Atlantic Bight\u2014Comparison of ship determinations and CZCS estimates","volume":"22","author":"Gordon","year":"1983","journal-title":"Appl. Opt."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2015.08.002","article-title":"Secchi disk depth: A new theory and mechanistic model for underwater visibility","volume":"169","author":"Lee","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2012.03.006","article-title":"Combining lake and watershed characteristics with Landsat TM data for remote estimation of regional lake clarity","volume":"123","author":"McCullough","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"116844","DOI":"10.1016\/j.watres.2021.116844","article-title":"Remote sensing estimation of water clarity for various lakes in China","volume":"192","author":"Zhang","year":"2021","journal-title":"Water Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"151188","DOI":"10.1016\/j.scitotenv.2021.151188","article-title":"A unified model for high resolution mapping of global lake (>1 ha) clarity using Landsat imagery data","volume":"810","author":"Song","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.rse.2018.12.007","article-title":"Monitoring and understanding the water transparency changes of fifty large lakes on the Yangtze Plain based on long-term MODIS observations","volume":"221","author":"Feng","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"111299","DOI":"10.1016\/j.envres.2021.111299","article-title":"Songhua River basin\u2019s improving water quality since 2005 based on Landsat observation of water clarity","volume":"199","author":"Tao","year":"2021","journal-title":"Environ. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.watres.2017.04.035","article-title":"Improving water quality in China: Environmental investment pays dividends","volume":"118","author":"Zhou","year":"2017","journal-title":"Water Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"79","DOI":"10.5194\/essd-14-79-2022","article-title":"A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018","volume":"14","author":"Tao","year":"2022","journal-title":"Earth Syst. Sci. Data."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s11430-010-4052-6","article-title":"China\u2019s lakes at present: Number, area and spatial distribution","volume":"54","author":"Ma","year":"2011","journal-title":"Sci. China-Earth Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.rse.2018.11.038","article-title":"Regional differences of lake evolution across China during 1960s\u20132015 and its natural and anthropogenic causes","volume":"221","author":"Zhang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.envint.2018.11.048","article-title":"How successful are the restoration efforts of China\u2019s lakes and reservoirs?","volume":"123","author":"Huang","year":"2019","journal-title":"Environ. Int."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.rse.2011.12.015","article-title":"Evaluation of Earth Observation based global long term vegetation trends\u2014Comparing GIMMS and MODIS global NDVI time series","volume":"119","author":"Fensholt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.rse.2017.01.005","article-title":"Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socio-economic dynamics","volume":"192","author":"Bennett","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1111\/2041-210X.13800","article-title":"Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package","volume":"13","author":"Lai","year":"2022","journal-title":"Methods Ecol Evol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.rse.2014.04.033","article-title":"Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters","volume":"157","author":"Brezonik","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_39","first-page":"102187","article-title":"Observations of water transparency in China\u2019s lakes from space","volume":"92","author":"Liu","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111349","DOI":"10.1016\/j.rse.2019.111349","article-title":"A semi-analytical approach for remote sensing of trophic state in inland waters: Bio-optical mechanism and application","volume":"232","author":"Shi","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1016\/j.watres.2011.08.002","article-title":"Climate change: Links to global expansion of harmful cyanobacteria","volume":"46","author":"Paerl","year":"2012","journal-title":"Water Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/j.watres.2011.11.013","article-title":"Contributions of meteorology to the phenology of cyanobacterial blooms: Implications for future climate change","volume":"46","author":"Zhang","year":"2012","journal-title":"Water Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1080\/17538947.2013.822026","article-title":"Modeling the spatiotemporal dynamics of electric power consumption in Mainland China using saturation-corrected DMSP\/OLS night-time stable light data","volume":"7","author":"He","year":"2014","journal-title":"Int. J. Digital Earth"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jhydrol.2019.06.028","article-title":"Characterization of CDOM in reservoirs and its linkage to trophic status assessment across China using spectroscopic analysis","volume":"576","author":"Shang","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1007\/s11270-011-0959-6","article-title":"Hyperspectral Remote Sensing of Total Phosphorus (TP) in Three Central Indiana Water Supply Reservoirs","volume":"223","author":"Song","year":"2012","journal-title":"Water Air Soil Pollut."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2017.03.003","article-title":"Spatiotemporally enhancing time-series DMSP\/OLS night-time light imagery for assessing large-scale urban dynamics","volume":"128","author":"Xie","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1126\/science.aaf2295","article-title":"Improvements in ecosystem services from investments in natural capital","volume":"352","author":"Ouyang","year":"2016","journal-title":"Science."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1111\/gcb.12795","article-title":"Detection and attribution of vegetation greening trend in China over the last 30 years","volume":"21","author":"Piao","year":"2015","journal-title":"Glob. Chang. Biol"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5091\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:52:43Z","timestamp":1760143963000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5091"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,12]]},"references-count":48,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14205091"],"URL":"https:\/\/doi.org\/10.3390\/rs14205091","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,10,12]]}}}