Water color represents the most intuitive visible perception of the color of water bodies that is jointly affected by substances such as suspended particulate matter, chlorophyll, and soluble organic matter. Water color is a water environmental parameter with a long history and plays a critical role in research on the ecosystem of inland and nearshore water bodies. With the progress made in colorimetric research, as well as hyperspectral imaging and satellite remote sensing techniques, the colorimetric method of water color has developed. This study systematically reviewed the colorimetric research progress of inland and nearshore water bodies and elaborated on the theories and practical applications of the colorimetric method from the angles of apparent optical properties (AOP) and inherent optical properties (IOP). Moreover, it presented the colorimetric processing method of satellite remote sensing data. The colorimetric method is a technical method for the quantitative expression of water color. It is also an important branch of water color research and an extension and supplement to the study of water color components, with a broad application prospect. To further improve the application of the colorimetric methods in inland and nearshore water bodies, it is necessary to enhance the construction of bio-optical datasets of water bodies in the future. Moreover, colorimetric studies should be conducted in two dimensions, namely AOP and IOP, and it is necessary to intensify research on domestic satellite-based colorimetric methods and increase the types of relevant water color products.
Wernand M R, Novoa S, van der Woerd H, et al. A centuries-long history of participatory science in optical oceanography:From observation to interpretation of natural water colouring[J]. History of Oceanography Yearbook, 2014, 19(20):61-90.
[2]
Wernand M R. Poseidon’s paintbox:Historical archives of ocean colour in global-change perspective[D]. Utrecht: Utrecht University, 2011.
[3]
Wernand M R, van der Woerd H J. Spectral analysis of the Forel-Ule ocean colour comparator scale[J]. Journal of the European Optical Society-Rapid Publications, 2010, 5(10014S):1-7.
[4]
Wernand M R, Hommersom A, van der Woerd H J. MERIS-based ocean colour classification with the discrete Forel-Ule scale[J]. Ocean Science, 2013, 9(3):477-487.
doi: 10.5194/os-9-477-2013
[5]
Wernand M R, Woerd H J, Gieskes W C. Trends in ocean colour and chlorophyll concentration from 1889 to present[J]. PLOS ONE, 2013, 8(6):1-20.
[6]
Arthur D B. A critical review of the development of the CIE1931 RGB color-matching functions[J]. Color Research and Application, 2004, 29(4),267-272.
doi: 10.1002/(ISSN)1520-6378
Tang J W, Tian G L, Wang X Y, et al. The methods of water spectra measurement and analysis Ⅰ:Above-water method[J]. Journal of Remote Sensing, 2004, 8(1):37-44.
[11]
Woerd H J, Wernand M R. True colour classification of natural waters with medium-spectral resolution satellites:SeaWiFS,MODIS,MERIS and OLCI[J]. Sensors, 2015, 15(10):25663-25680.
doi: 10.3390/s151025663
[12]
Woerd H J, Wernand M R. Hue-angle product for low to medium spatial resolution optical satellite sensors[J]. Remote Sensing, 2018, 10(2):180-198.
doi: 10.3390/rs10020180
[13]
Novoa S, Wernand M R, van der Woerd H J. The Forel-Ule scale revisited spectrally:Preparation protocol,transmission measurements and chromaticity[J]. Journal of the European Optical Society-Rapid publications, 2013(13057):1-8.
[14]
Pitarch J, Bellacicco M, Marullo S, et al. Global maps of Forel-Ule index,hue angle and Secchi disk depth derived from twenty-one years of monthly ESA-OC-CCI data[J]. Earth System Science Data Discussions, 2020(13):1-17.
[15]
Stomp M, Huisman J, Stal L J, et al. Colorful niches of phototrophic microorganisms shaped by vibrations of the water molecule[J]. The ISME Journal, 2007, 1(4):271-282.
doi: 10.1038/ismej.2007.59
[16]
Holtrop T, Huisman J, Stomp M, et al. Vibrational modes of water predict spectral niches for photosynthesis in lakes and oceans[J]. Nature Ecology and Evolution, 2021, 5(1):55-66.
doi: 10.1038/s41559-020-01330-x
pmid: 33168993
[17]
Haverkamp T H A. Shades of red and green:The colorful diversity and ecology of picocyanobacteria in the Baltic Sea[D]. Amsterdam: Royal Netherlands Academy of Arts and Sciences, 2008.
[18]
Rueffler C, van Dooren T J M, Leimar O, et al. Disruptive selection and then what?[J]. Trends in Ecology and Evolution, 2006, 21(5):238-245.
pmid: 16697909
[19]
Smith R C, Goldman T. Optical properties and color of Lake Tahoe and crater lake[J]. Limnology and Oceanography, 1973, 18(2):189-199.
doi: 10.4319/lo.1973.18.2.0189
[20]
Alfoldi T T, Munday J C. Water quality analysis by digital chromaticity mapping of Landsat data[J]. Canadian Journal of Remote Sensing, 1978, 4(2):108-126.
doi: 10.1080/07038992.1978.10854974
[21]
Jaquet J, Zand B. Colour analysis of inland waters using Landsat TM data[J]. European Space Agency Monographs, 1989, 1102(11):57-67
[22]
Sovdat B, Kadunc M, Batic M, et al. Natural color representation of Sentinel-2 data[J]. Remote Sensing of Environment, 2019(255):392-402.
[23]
Jolliff J K, Lewis M D, Ladner S, et al. Observing the ocean submesoscale with enhanced-color GOES-ABI visible band data[J]. Sensors, 2019, 19(3900):1-23.
doi: 10.3390/s19010001
[24]
Novoa S, Wernand M, van der Woerd H J. WACODI:A generic algorithm to derive the intrinsic color of natural waters from digital images[J]. Limnology and Oceanography:Methods, 2015, 13(12):697-711.
doi: 10.1002/lom3.v13.12
[25]
Novoa S, Wernand M R, van der Woerd H J. The modern Forel-Ule scale:A “Do-it-yourself” colour comparator for water monitoring[J]. Journal of the European Optical Society-Rapid Publications, 2014, 9(14025):1-10.
[26]
Busch J A, Price I, Jeansou E, et al. Citizens and satellites:Assessment of phytoplankton dynamics in a NW Mediterranean aquaculture zone[J]. International Journal of Applied Earth Observation and Geoinformation, 2016(47):40-49.
[27]
Busch J A, Bardaji R, Ceccaroni L, et al. Citizen bio-optical observations from coast-and ocean and their compatibility with ocean colour satellite measurements[J]. Remote Sensing, 2016, 8(11):879.
doi: 10.3390/rs8110879
[28]
Malthus T J, Ohmsen R, Woerd H J. An evaluation of citizen science smartphone APPs for inland water quality assessment[J]. Remote Sensing, 2020, 12(1578):1-20.
doi: 10.3390/rs12010001
Duan H T, Luo J H, Cao Z G, et al. Progress in remote sensing of aquatic environments at the watershed scale[J]. Progress in Geography, 2019, 38(8):1182-1195.
doi: 10.18306/dlkxjz.2019.08.007
Duan H T, Cao Z G, Shen M, et al. Review of lake remote sensing research[J]. National Remote Sensing Bulletin, 2019, 26(1):3-18.
[31]
Garaba S P, Friedrichs A, Voß D, et al. Classifying natural waters with the Forel-Ule colour index system:Results,applications,correlations and crowdsourcing[J]. International Journal of Environmental Research and Public Health, 2015, 12(12):16096-16109.
doi: 10.3390/ijerph121215044
[32]
Garaba S P, Voß D, Zielinski O. Physical,bio-optical state and correlations in North-Western European Shelf Seas[J]. Remote Sensing, 2014, 6(6):5042-5066.
doi: 10.3390/rs6065042
[33]
Woerd H J, Wernand M R, Peters M et al. True color analysis of natural waters with SeaWiFS,MODIS,MERIS and OLCI by SNAP[C]// Ocean Optics Conference, 2016.
[34]
Pitarch J, van der Woerd H J, Brewin R J W, et al. Optical properties of Forel-Ule water types deduced from 15 years of global satellite ocean color observations[J]. Remote Sensing of Environment, 2019(231):1-16.
[35]
Petus C, Waterhouse J, Lewis S, et al. A flood of information:Using Sentinel-3 water colour products to assure continuity in the monitoring of water quality trends in the Great Barrier Reef (Australia)[J]. Journal of Environmental Management, 2019(248):1-20.
[36]
Nie Y, Guo J, Sun B, et al. An evaluation of apparent color of seawater based on the in-situ and satellite-derived Forel-Ule color scale[J]. Estuarine,Coastal and Shelf Science, 2020(246):1-10.
[37]
Sung T, Kim Y J, Choi H, et al. Spatial downscaling of ocean colour-climate change initiative (OC-CCI) Forel-Ule index using GOCI satellite image and machine learning technique[J]. Korean Journal of Remote Sensing, 2021, 37(5-1):959-974.
[38]
Zhan J, Zhang D J, Zhou G Q, et al. MODIS-based research on Secchi disk depth using an improved Semianalytical algorithm in the Yellow Sea[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021(14):5964-5972.
[39]
Li M J, Sun Y H, Li X J et al. An improved eutrophication assessment algorithm of estuaries and coastal waters in Liaodong Bay[J]. Remote Sensing, 2021, 13(19):3866-3884.
doi: 10.3390/rs13193866
[40]
Wang S, Li J, Shen Q, et al. MODIS-based radiometric color extraction and classification of inland water with the Forel-Ule scale:A case study of Lake Taihu[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 8(2):907-918.
doi: 10.1109/JSTARS.4609443
[41]
Li J, Wang S, Wu Y, et al. MODIS observations of water color of the largest 10 lakes in China between 2000 and 2012[J]. International Journal of Digital Earth, 2016, 9(8):788-805.
doi: 10.1080/17538947.2016.1139637
[42]
Wang S, Li J, Zhang B, et al. Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index[J]. Remote Sensing of Environment, 2018(217):444-460.
Wang S L. Large-scale and long-time water quality remote sensing monitoring over lakes based on water color index[D]. Beijing: University of Chinese Academy of Sciences, 2018.
[44]
Lehmann M K, Nguyen U, Allan M, et al. Colour classification of 1 486 lakes across a wide range of optical water types[J]. Remote Sensing, 2018, 10(8):1273.
doi: 10.3390/rs10081273
[45]
Jafar S M, Bowers D G, Griffiths J W. Remote sensing observations of ocean colour using the traditional Forel-Ule scale[J]. Estuarine,Coastal and Shelf Science, 2018(215):52-58.
[46]
Wang S, Li J, Zhang B, et al. Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS[J]. Remote Sensing of Environment, 2020(247):1-17.
[47]
Chen Q, Huang M, Tang X. Eutrophication assessment of seasonal urban lakes in China Yangtze River basin using Landsat8-derived Forel-Ule index:A six-year (2013—2018) observation[J]. Science of the Total Environment, 2020(745):135392-135392.
Xu Y. Study on the long-term change of lacustrine water color in the middle and lower basins of the Yangtze river based on Landsat datasets[D]. Wuhan: Wuhan University, 2020.
Xu Y, Wang Y, Lu J Z, et al. Study on water color of Tonle Sap Lake in Cambodia based on FUI model[J]. Journal of Central China Normal University(Natural Science), 2020, 54(3):454-462.
Wang Y. Research on long-time dynamic process of Tonle Sap Lake water environment based on multi-source remote sensing data[D]. Harbin: Harbin Institute of Technology, 2020.
Cao C, Wang S L, Li J S, et al. MODIS-based monitoring of spatial distribution of trophic status in 144 key lakes and reservoirs of China in summer of 2018[J]. Journal of Lake Sciences, 2018, 33(2):405-413.
doi: 10.18307/2021.0203
Jiang Q. Study on the effectiveness evaluation method of satellite remote sensing in the monitoring of lake and reservoir water quality:Take GF-1 satellite as an example[D]. Lanzhou: Lanzhou Jiaotong University, 2020.
Wen S, Wang J, Li Y M, et al. Remote sensing identification of urban black-odor water bodies based on high-resolution images:A case study in Nanjing[J]. Environmental Science, 2018, 39(1):57-67.
doi: 10.1021/es048902d
Yang Z Q, Liu H Q, Lyu H, et al. A comprehensive classification method of urban water by remote sensing based on high-resolution images[J]. Environmental Science, 2021, 42(5):2213-2222.
[55]
Zhao Y, Shen Q, Wang Q, et al. Recognition of water colour anomaly by using hue angle and Sentinel 2 image[J]. Remote Sensing, 2020, 12(4):716-737.
doi: 10.3390/rs12040716
[56]
Sathyendranath S, Brewin B, Mueller D, et al. Ocean colour climate change initiative:Approach and initial results[C]// 2012 IEEE International Geoscience and Remote Sensing Symposium.IEEE, 2012:2024-2027.
[57]
Jackson T, Chuprin A, Sathyendranath S, et al. Ocean colour climate change initiative (OC_CCI)-interim phase[R]. Plymouth: Plymouth Marine Laboratory, 2020.
Zhang B, Li J S, Shen Q, et al. Recent research progress on long time series and large scale optical remote sensing of inland water[J]. National Remote Sensing Bulletin, 2021, 25(1):37-52.
[59]
Wang S, Li J, Zhang W, et al. A dataset of remote-sensed Forel-Ule index for global inland waters during 2000—2018[J]. Scientific Data, 2021, 8(1):1-10.
doi: 10.1038/s41597-020-00786-7
[60]
Boyce D G, Lewis M, Worm B. Integrating global chlorophyll data from 1890 to 2010[J]. Limnology and Oceanography:Methods, 2012(10):840-852.
[61]
Dutkiewicz S, Hickman A E, Jahn O, et al. Ocean colour signature of climate change[J]. Nature Communications, 2019, 10(1):1-13.
doi: 10.1038/s41467-018-07882-8
Xing X G, Zhao D Z, Liu Y G, et al. Process in fluorescence remote sensing of chlorophy-a[J]. Journal of Remote Sensing, 2007, 11(1):137-144.
[63]
Lee Z P. Remote sensing of inherent optical properties:Fundamentals,tests of algorithms,and applications[R]. Dartmouth: International Ocean-Colour Coordinating Group, 2006.
[64]
Friedrichs A, Busch J A, van der Woerd H J, et al. SmartFluo:A method and affordable adapter to measure chlorophyll a fluorescence with smartphones[J]. Sensors, 2017, 17(4):678.
doi: 10.3390/s17040678
[65]
Pozdnyakov D V, Kondratyev K Y. Numerical modelling of natural water colour:Implications for remote sensing and limnological studies[J]. International Journal of Remote Sensing, 1998, 19(10):1913-1932.
doi: 10.1080/014311698215063
[66]
Woźniak S B, Meler J. Modelling water colour characteristics in an optically complex nearshore environment in the Baltic Sea:Quantitative interpretation of the Forel-Ule scale and algorithms for the remote estimation of seawater composition[J]. Remote Sensing, 2020,(12):2851-2885.
[67]
Bukata R P, Jerome J H, Kondratyev K Y, et al. IEEE Conference on Computer Vision and Pattern Recognition.[J]. Journal of Great Lakes Research, 1997, 23(3):254-269.
doi: 10.1016/S0380-1330(97)70910-9
[68]
Leech D M, Pollard A I, Labou S G, et al. Fewer blue lakes and more murky lakes across the continental US:Implications for planktonic food webs[J]. Limnology and Oceanography, 2018, 63(6):2661-2680.
doi: 10.1002/lno.10967
pmid: 31942083
[69]
Ting C S, Rocap G, King J, et al. Cyanobacterial photosynthesis in the oceans:The origins and significance of divergent light-harvesting strategies[J]. Trends in Microbiology, 2002, 10(3):134-142.
doi: 10.1016/S0966-842X(02)02319-3
[70]
Croce R, van Amerongen H. Natural strategies for photosynthetic light harvesting[J]. Nature Chemical Biology, 2014, 10(7):492-501.
doi: 10.1038/nchembio.1555
pmid: 24937067
[71]
Monteith D T, Stoddard J L, Evans C D, et al. Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry[J]. Nature, 2007, 450(7169):537-540.
doi: 10.1038/nature06316
[72]
Weyhenmeyer G A, Müller R A, Norman M, et al. Sensitivity of freshwaters to browning in response to future climate change[J]. Climatic Change, 2016, 134(1-2):225-239.
doi: 10.1007/s10584-015-1514-z
[73]
Kritzberg E S. Centennial-long trends of lake browning show major effect of afforestation[J]. Limnology and Oceanography Letters, 2017, 2(4):105-112.
doi: 10.1002/lol2.v2.4
[74]
Urrutia C P, Ekvall M K, Ratcovich J, et al. Phytoplankton diversity loss along a gradient of future warming and brownification in freshwater mesocosms[J]. Freshwater Biology, 2017, 62(11):1869-1878.
[75]
Wilken S, Soares M, Pablo U C, et al. Primary producers or consumers? Increasing phytoplankton bacterivory along a gradient of lake warming and browning[J]. Limnology and Ceanography, 2018(63):S142-S155.
[76]
FeuchtmayrH, Pottinger T G, Moore A, et al. Effects of brownification and warming on algal blooms,metabolism and higher trophic levels in productive shallow lake mesocosms[J]. Science of the Total Environment, 2019, 678:227-238.
doi: 10.1016/j.scitotenv.2019.04.105
[77]
Deininger A, Faithfull C L, Bergström A K. Phytoplankton response to whole lake inorganic N fertilization along a gradient in dissolved organic carbon[J]. Ecology, 2017, 98(4):982-994.
doi: 10.1002/ecy.1758
pmid: 28144934
[78]
Tan X, Zhang D, Duan Z, et al. Effects of light color on interspecific competition between microcystis aeruginosa and chlorella pyrenoidosa in batch experiment[J]. Environmental Science and Pollution Research, 2020, 27(1):344-352.
doi: 10.1007/s11356-019-06650-5
[79]
Luimstra V M, Verspagen J M H, Xu T, et al. Changes in water color shift competition between phytoplankton species with contrasting light-harvesting strategies[J]. Ecology, 2020, 101(3):1-17.
Li Y M, Zhao H, Bi S, et al. Research progress of remote sensing monitoring of case II water environmental parameters based on water optical classification[J]. National Remote Sensing Bulletin, 2022, 26(1): 19-31.
2023, Vol. 35 
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