Show simple item record

Application of the Beer–Lambert Model to Attenuation of Photosynthetically Active Radiation in a Shallow, Eutrophic Lake

dc.contributor.authorWeiskerger, Chelsea J.
dc.contributor.authorRowe, Mark D.
dc.contributor.authorStow, Craig A.
dc.contributor.authorStuart, Dack
dc.contributor.authorJohengen, Tom
dc.date.accessioned2019-01-15T20:29:42Z
dc.date.available2020-01-06T16:40:59Zen
dc.date.issued2018-11
dc.identifier.citationWeiskerger, Chelsea J.; Rowe, Mark D.; Stow, Craig A.; Stuart, Dack; Johengen, Tom (2018). "Application of the Beer–Lambert Model to Attenuation of Photosynthetically Active Radiation in a Shallow, Eutrophic Lake." Water Resources Research 54(11): 8952-8962.
dc.identifier.issn0043-1397
dc.identifier.issn1944-7973
dc.identifier.urihttps://hdl.handle.net/2027.42/147097
dc.description.abstractModels of primary production in aquatic systems must include a means to estimate subsurface light. Such models often use the Beer–Lambert law, assuming exponential attenuation of light with depth. It is further assumed that the diffuse attenuation coefficient may be estimated as a summation of scattering/absorbing constituent concentrations multiplied by their respective specific attenuation coefficients. While theoretical deviations from these assumptions have been documented, it is useful to consider the empirical performance of this common approach. Photosynthetically active radiation (PAR) levels and water quality conditions were recorded weekly from six to eight monitoring stations in western Lake Erie between 2012 and 2016. Exponential PAR extinction models yielded a mean attenuation coefficient of 1.55 m (interquartile range = 0.74–1.90 m). While more complex light attenuation models are available, analysis of residuals indicated that the simple Beer–Lambert model is adequate for shallow, eutrophic waters similar to western Lake Erie (R2 > 0.9 for 96% of samples). Three groups of water quality variables were predictive of PAR attenuation: total and nonvolatile suspended particles, dissolved organic substances (dissolved organic carbon and chromophoric dissolved organic matter), and organic solids (volatile suspended solids and chlorophyll). Multiple regression models using these variables predicted 3–90% of the variability in PAR attenuation, with a median adjusted R2 = 0.86. Explanatory variables within these groups may substitute for each other while maintaining similar model performance, indicating that various combinations of water quality variables may be useful to predict PAR attenuation, depending on availability within a model framework or monitoring program.Key PointsThe Beer–Lambert law effectively models photosynthetically active radiation in western Lake Erie, despite some systematic deviationsField‐obtained water quality parameters can predict photosynthetically active radiation attenuation with a high degree of confidenceSuspended particle concentration is most predictive of photosynthetically active radiation attenuation in this turbid, eutrophic basin
dc.publisherAmerican Public Health Association
dc.publisherWiley Periodicals, Inc.
dc.subject.otherBeer–Lambert law
dc.subject.otherwestern Lake Erie
dc.subject.otherbiophysical model applications
dc.subject.otherwater quality
dc.subject.otherphotosynthetically active radiation
dc.titleApplication of the Beer–Lambert Model to Attenuation of Photosynthetically Active Radiation in a Shallow, Eutrophic Lake
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelNatural Resources and Environment
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/1/wrcr23654_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/2/wrcr23654-sup-0001-2018WR023024-SI.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/3/wrcr23654.pdf
dc.identifier.doi10.1029/2018WR023024
dc.identifier.sourceWater Resources Research
dc.identifier.citedreferenceSafaie, A., Wendzel, A., Ge, Z. F., Nevers, M. B., Whitman, R. L., Corsi, S. R., & Phanikumar, M. S. ( 2016 ). Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan. Environmental Science & Technology, 50 ( 5 ), 2442 – 2449. https://doi.org/10.1021/acs.est.5b05378
dc.identifier.citedreferenceMouw, C., & Barnett, A. ( 2014 ). CDOM Absorption—Sample Collection and Analysis (pp. 1 – 9 ). MI: Michigan Technological University Houghton.
dc.identifier.citedreferencePaulson, C. A., & Simpson, J. J. ( 1977 ). Irradiance measurements in upper ocean. Journal of Physical Oceanography, 7 ( 6 ), 952 – 956. https://doi.org/10.1175/1520‐0485(1977)007<0952:IMITUO>2.0.CO;2
dc.identifier.citedreferencePegau, W. S., Gray, D., & Zaneveld, J. R. V. ( 1997 ). Absorption and attenuation of visible and near‐infrared light in water: Dependence on temperature and salinity. Applied Optics, 36 ( 24 ), 6035 – 6046. https://doi.org/10.1364/AO.36.006035
dc.identifier.citedreferencePierson, D. C., Kratzer, S., Strombeck, N., & Hakansson, B. ( 2008 ). Relationship between the attenuation of downwelling irradiance at 490 nm with the attenuation of PAR (400 nm–700 nm) in the Baltic Sea. Remote Sensing of Environment, 112 ( 3 ), 668 – 680. https://doi.org/10.1016/j.rse.2007.06.009
dc.identifier.citedreferencePorta, D., Fitzpatrick, M. A. J., & Haffner, G. D. ( 2005 ). Annual variability of phytoplankton primary production in the western basin of Lake Erie (2002–2003). Journal of Great Lakes Research, 31, 63 – 71. https://doi.org/10.1016/S0380‐1330(05)70305‐1
dc.identifier.citedreferenceRowe, M. D., Anderson, E. J., Vanderploeg, H. A., Pothoven, S. A., Elgin, A. K., Wang, J., & Yousef, F. ( 2017 ). Influence of invasive quagga mussels, phosphorus loads, and climate on spatial and temporal patterns of productivity in Lake Michigan: A biophysical modeling study. Limnology and Oceanography, 62 ( 6 ), 2629 – 2649. https://doi.org/10.1002/lno.10595
dc.identifier.citedreferenceRowe, M. D., Anderson, E. J., Wynne, T. T., Stumpf, R. P., Fanslow, D. L., Kijanka, K., Vanderploeg, H. A., Strickler, J. R., & Davis, T. W. ( 2016 ). Vertical distribution of buoyant Microcystis blooms in a Lagrangian particle tracking model for short‐term forecasts in Lake Erie. Journal of Geophysical Research: Oceans, 121, 5296 – 5314. https://doi.org/10.1002/2016JC011720
dc.identifier.citedreferenceSaulquin, B., Hamdi, A., Gohin, F., Populus, J., Mangin, A., & d’Andon, O. F. ( 2013 ). Estimation of the diffuse attenuation coefficient K‐dPAR using MERIS and application to seabed habitat mapping. Remote Sensing of Environment, 128, 224 – 233. https://doi.org/10.1016/j.rse.2012.10.002
dc.identifier.citedreferenceSiegel, D. A., Maritorena, S., Nelson, N. B., & Behrenfeld, M. J. ( 2005 ). Independence and interdependencies among global ocean color properties: Reassessing the bio‐optical assumption. Journal of Geophysical Research, 110, C07011. https://doi.org/10.1029/2004JC002527
dc.identifier.citedreferenceSmith, R. C., & Baker, K. S. ( 1978 ). Optical classification of natural waters. Limnology and Oceanography, 23 ( 2 ), 260 – 267. https://doi.org/10.4319/lo.1978.23.2.0260
dc.identifier.citedreferenceSmith, R. E. H., Hiriart‐Baer, V. P., Higgins, S. N., Guildford, S. J., & Charlton, M. N. ( 2005 ). Planktonic primary production in the offshore waters of dreissenid‐infested Lake Erie in 1997. Journal of Great Lakes Research, 31, 50 – 62. https://doi.org/10.1016/S0380‐1330(05)70304‐X
dc.identifier.citedreferenceSmith, W. O. ( 1982 ). The relative importance of chlorophyll, dissolved and particulate material, and seawater to the vertical extinction of light. Estuarine, Coastal and Shelf Science, 15 ( 4 ), 459 – 465. https://doi.org/10.1016/0272‐7714(82)90054‐3
dc.identifier.citedreferenceSpeziale, B. J., Schreiner, S. P., Giammatteo, P. A., & Schindler, J. E. ( 1984 ). Comparison of N,N‐dimethylformamide, dimethylsulfoxide, and acetone for extraction of phytoplankton chlorophyll. Canadian Journal of Fisheries and Aquatic Sciences, 41 ( 10 ), 1519 – 1522. https://doi.org/10.1139/f84‐187
dc.identifier.citedreferenceStavn, R. H. ( 1988 ). Lambert‐Beer law in ocean waters: Optical‐properties of water and of dissolved/suspended material, optical energy budgets. Applied Optics, 27 ( 2 ), 222 – 231. https://doi.org/10.1364/AO.27.000222
dc.identifier.citedreferenceStefan, H. G., Cardoni, J. J., Schiebe, F. R., & Cooper, C. M. ( 1983 ). Model of light penetration in a turbid lake. Water Resources Research, 19 ( 1 ), 109 – 120. https://doi.org/10.1029/WR019i001p00109
dc.identifier.citedreferenceStramski, D., Bricaud, A., & Morel, A. ( 2001 ). Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community. Applied Optics, 40 ( 18 ), 2929 – 2945. https://doi.org/10.1364/AO.40.002929
dc.identifier.citedreferenceStumpf, R. P., Wynne, T. T., Baker, D. B., & Fahnenstiel, G. L. ( 2012 ). Interannual variability of cyanobacterial blooms in Lake Erie. PLoS One, 7 ( 8 ), 11.
dc.identifier.citedreferenceSwain, A. ( 1980 ). Material budgets in Lake Chicot, Arkansas, University of Mississippi, Oxford.
dc.identifier.citedreferenceTwardowski, M. S., Boss, E., Macdonald, J. B., Pegau, W. S., Barnard, A. H., & Zaneveld, J. R. V. ( 2001 ). A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research, 106 ( C7 ), 14,129 – 14,142. https://doi.org/10.1029/2000JC000404
dc.identifier.citedreferenceUSEPA ( 2005 ). Method 415.3: Measurement of total organic carbon, dissolved organic carbon and specific UV absorbance at 254 nm in source water and drinking water. Washington, DC: United States Environmental Protection Agency.
dc.identifier.citedreferenceVerhamme, E. M., Redder, T. M., Schlea, D. A., Grush, J., Bratton, J. F., & DePinto, J. V. ( 2016 ). Development of the Western Lake Erie ecosystem model (WLEEM): Application to connect phosphorus loads to cyanobacteria biomass. Journal of Great Lakes Research, 42 ( 6 ), 1193 – 1205. https://doi.org/10.1016/j.jglr.2016.09.006
dc.identifier.citedreferenceWang, M. Z., Lyzenga, D. R., & Klemas, V. V. ( 1996 ). Measurement of optical properties in the Delaware estuary. Journal of Coastal Research, 12 ( 1 ), 211 – 228.
dc.identifier.citedreferenceXu, J. T., Hood, R. R., & Chao, S. Y. ( 2005 ). A simple empirical optical model for simulating light attenuation variability in a partially mixed estuary. Estuaries, 28 ( 4 ), 572 – 580. https://doi.org/10.1007/BF02696068
dc.identifier.citedreferenceAPHA ( 1998 ). Standard Methods for the Examination of Water and Wastewater. Washington, DC: American Public Health Association.
dc.identifier.citedreferenceBeletsky, D., Schwab, D. J., Roebber, P. J., McCormick, M. J., Miller, G. S., & Saylor, J. H. ( 2003 ). Modeling wind‐driven circulation during the March 1998 sediment resuspension event in Lake Michigan. Journal of Geophysical Research, 108 ( C2 ), 3038. https://doi.org/10.1029/2001JC001159
dc.identifier.citedreferenceBinding, C. E., Greenberg, T. A., Watson, S. B., Rastin, S., & Gould, J. ( 2015 ). Long term water clarity changes in North America’s Great Lakes from multi‐sensor satellite observations. Limnology and Oceanography, 16, 1976 – 1995.
dc.identifier.citedreferenceBocaniov, S. A., Leon, L. F., Rao, Y. R., Schwab, D. J., & Scavia, D. ( 2016 ). Simulating the effect of nutrient reduction on hypoxia in a large lake (Lake Erie, USA‐Canada) with a three‐dimensional lake model. Journal of Great Lakes Research, 42 ( 6 ), 1228 – 1240. https://doi.org/10.1016/j.jglr.2016.06.001
dc.identifier.citedreferenceBorsuk, M. E., & Stow, C. A. ( 2000 ). Bayesian parameter estimation in a mixed‐order model of BOD decay. Water Research, 34 ( 6 ), 1830 – 1836. https://doi.org/10.1016/S0043‐1354(99)00346‐2
dc.identifier.citedreferenceBranco, A. B., & Kremer, J. N. ( 2005 ). The relative importance of chlorophyll and colored dissolved organic matter (CDOM) to the prediction of the diffuse attenuation coefficient in shallow estuaries. Estuaries, 28 ( 5 ), 643 – 652. https://doi.org/10.1007/BF02732903
dc.identifier.citedreferenceBuiteveld, H. ( 1995 ). A model for calculation of diffuse light attenuation (PAR) and Secchi depth. Netherlands Journal of Aquatic Ecology, 29 ( 1 ), 55 – 65. https://doi.org/10.1007/BF02061789
dc.identifier.citedreferenceCerco, C. F., & Meyers, M. ( 2000 ). Tributary refinements to Chesapeake Bay model. Journal of Environmental Engineering‐Asce, 126 ( 2 ), 164 – 174. https://doi.org/10.1061/(ASCE)0733‐9372(2000)126:2(164)
dc.identifier.citedreferenceChandler, D. C. ( 1942 ). Limnological studies of western Lake Erie II. Light penetration and its relation to turbidity. Ecology, 23 ( 1 ), 41 – 52. https://doi.org/10.2307/1930871
dc.identifier.citedreferenceChen, C. S., Liu, H. D., & Beardsley, R. C. ( 2003 ). An unstructured grid, finite‐volume, three‐dimensional, primitive equations ocean model: Application to coastal ocean and estuaries. Journal of Atmospheric and Oceanic Technology, 20 ( 1 ), 159 – 186. https://doi.org/10.1175/1520‐0426(2003)020<0159:AUGFVT>2.0.CO;2
dc.identifier.citedreferenceChristian, D., & Sheng, Y. P. ( 2003 ). Relative influence of various water quality parameters on light attenuation in Indian River lagoon. Estuarine, Coastal and Shelf Science, 57 ( 5–6 ), 961 – 971. https://doi.org/10.1016/S0272‐7714(03)00002‐7
dc.identifier.citedreferenceDahl, J. A., Graham, D. M., Dermott, R., Johannsson, O. E., Millard, E. S., & Myles, D. D. ( 1995 ). Lake Erie 1993, western, west central and eastern basins: Change in trophic status, and assessment of the abundance, biomass and production of the lower trophic levels. Canadian Technical Report of Fisheries and Aquatic Sciences, 2070 ( i‐xii ), 1 – 118.
dc.identifier.citedreferenceDennison, W. C., Orth, R. J., Moore, K. A., Stevenson, J. C., Carter, V., Kollar, S., Bergstrom, P. W., & Batiuk, R. A. ( 1993 ). Assessing water‐quality with submersed aquatic vegetation. Bioscience, 43 ( 2 ), 86 – 94. https://doi.org/10.2307/1311969
dc.identifier.citedreferenceDevlin, M. J., Barry, J., Mills, D. K., Gowen, R. J., Foden, J., Sivyer, D., Greenwood, N., Pearce, D., & Tett, P. ( 2009 ). Estimating the diffuse attenuation coefficient from optically active constituents in UK marine waters. Estuarine, Coastal and Shelf Science, 82 ( 1 ), 73 – 83. https://doi.org/10.1016/j.ecss.2008.12.015
dc.identifier.citedreferenceEnsor, D. S., & Pilat, M. J. ( 1971 ). Effect of particle size distribution on light transmittance measurement. American Industrial Hygiene Association Journal, 32 ( 5 ), 287 – 292. https://doi.org/10.1080/0002889718506462
dc.identifier.citedreferenceFitzpatrick, M. A. J., Munawar, M., Leach, J. H., & Haffner, G. D. ( 2007 ). Factors regulating primary production and phytoplankton dynamics in western Lake Erie. Fundamental and Applied Limnology, 169 ( 2 ), 137 – 152. https://doi.org/10.1127/1863‐9135/2007/0169‐0137
dc.identifier.citedreferenceGe, Z. F., Whitman, R. L., Nevers, M. B., Phanikumar, M. S., & Byappanahalli, M. N. ( 2012 ). Nearshore hydrodynamics as loading and forcing factors for Escherichia coli contamination at an embayed beach. Limnology and Oceanography, 57 ( 1 ), 362 – 381. https://doi.org/10.4319/lo.2012.57.1.0362
dc.identifier.citedreferenceGordon, H. R. ( 1989 ). Can the Lambert‐Beer law be applied to the diffuse attenuation coefficient of ocean water? Limnology and Oceanography, 34 ( 8 ), 1389 – 1409. https://doi.org/10.4319/lo.1989.34.8.1389
dc.identifier.citedreferenceGordon, H. R., & McCluney, W. R. ( 1975 ). Estimation of depth of sunlight penetration in sea for remote‐sensing. Applied Optics, 14 ( 2 ), 413 – 416. https://doi.org/10.1364/AO.14.000413
dc.identifier.citedreferenceHondzo, M., & Stefan, H. G. ( 1993 ). Lake water temperature simulation‐model. Journal of Hydraulic Engineering, 119 ( 11 ), 1251 – 1273. https://doi.org/10.1061/(ASCE)0733‐9429(1993)119:11(1251)
dc.identifier.citedreferenceHouser, J. N. ( 2006 ). Water color affects the stratification, surface temperature, heat content, and mean epilimnetic irradiance of small lakes. Canadian Journal of Fisheries and Aquatic Sciences, 63 ( 11 ), 2447 – 2455. https://doi.org/10.1139/f06‐131
dc.identifier.citedreferenceHutchinson, G. E., & Edmondson, Y. H. ( 1957 ). A Treatise on Limnology. New York: Wiley, University of California.
dc.identifier.citedreferenceIngle, J. D., & Crouch, S. R. ( 1988 ). Spectrochemical Analysis. Prentice Hall, NJ. Englewood Cliffs.
dc.identifier.citedreferenceJerlov, N. G. ( 1968 ). Optical Oceanography. Amsterdam: Elsevier Publishing Company.
dc.identifier.citedreferenceJi, R. B., Davis, C., Chen, C. S., & Beardsley, R. ( 2008 ). Influence of local and external processes on the annual nitrogen cycle and primary productivity on Georges Bank: A 3‐D biological‐physical modeling study. Journal of Marine Systems, 73 ( 1–2 ), 31 – 47. https://doi.org/10.1016/j.jmarsys.2007.08.002
dc.identifier.citedreferenceKarlsson, J., Bystrom, P., Ask, J., Ask, P., Persson, L., & Jansson, M. ( 2009 ). Light limitation of nutrient‐poor lake ecosystems. Nature, 460 ( 7254 ), 506 – 509. https://doi.org/10.1038/nature08179
dc.identifier.citedreferenceKemp, W. M., Boynton, W. R., Adolf, J. E., Boesch, D. F., Boicourt, W. C., Brush, G., Cornwell, J. C., Fisher, T. R., Glibert, P. M., Hagy, J. D., Harding, L. W., Houde, E. D., Kimmel, D. G., Miller, W. D., Newell, R. I. E., Roman, M. R., Smith, E. M., & Stevenson, J. C. ( 2005 ). Eutrophication of Chesapeake Bay: Historical trends and ecological interactions. Marine Ecology Progress Series, 303, 1 – 29. https://doi.org/10.3354/meps303001
dc.identifier.citedreferenceKirk, J. T. O. ( 1983 ). Light and Photosynthesis in Aquatic Ecosystems (Vol. i‐xi, pp. 1 – 401 ). Cambridge: Cambridge University Press.
dc.identifier.citedreferenceKirk, J. T. O. ( 1984 ). Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnology and Oceanography, 29 ( 2 ), 350 – 356. https://doi.org/10.4319/lo.1984.29.2.0350
dc.identifier.citedreferenceMarkager, S., & Vincent, W. F. ( 2000 ). Spectral light attenuation and the absorption of UV and blue light in natural waters. Limnology and Oceanography, 45 ( 3 ), 642 – 650. https://doi.org/10.4319/lo.2000.45.3.0642
dc.identifier.citedreferenceMcMahon, T. G., Raine, R. C. T., Fast, T., Kies, L., & Patching, J. W. ( 1992 ). Phytoplankton biomass, light attenuation and mixing in the Shannon estuary, Ireland. Journal of the Marine Biological Association of the United Kingdom, 72 ( 03 ), 709 – 720. https://doi.org/10.1017/S0025315400059464
dc.identifier.citedreferenceMedrano, E. A., Uittenbogaard, R. E., Pires, L. M. D., van de Wiel, B. J. H., & Clercx, H. J. H. ( 2013 ). Coupling hydrodynamics and buoyancy regulation in Microcystis aeruginosa for its vertical distribution in lakes. Ecological Modelling, 248, 41 – 56. https://doi.org/10.1016/j.ecolmodel.2012.08.029
dc.identifier.citedreferenceMitchell, B. G., Kahru, M., Wieland, J., & Stramska, M. ( 2003 ). In J. L. Mueller, G. S. Fargion, & C. R. McClain (Eds.), Ocean Optics Protocols of Satellite Ocean Color Sensor Validation (pp. 39 – 64 ). Greenbelt, MD, USA: NASA.
dc.identifier.citedreferenceMobley, C. D., Stramski, D., Bissett, W. P., & Boss, E. ( 2004 ). Optical modeling of ocean water: Is the case 1‐case 2 classification still useful? Oceanography, 17 ( 2 ), 61 – 67.
dc.identifier.citedreferenceMorel, A. ( 1988 ). Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters). Journal of Geophysical Research, 93 ( C9 ), 10,749 – 10,768. https://doi.org/10.1029/JC093iC09p10749
dc.identifier.citedreferenceMorel, A., & Prieur, L. ( 1977 ). Analysis of variations in ocean color. Limnology and Oceanography, 22 ( 4 ), 709 – 722. https://doi.org/10.4319/lo.1977.22.4.0709
dc.identifier.citedreferenceMortimer, C. H. ( 1987 ). 50 years of physical investigations and related limnological studies on Lake Erie, 1928–1977. Journal of Great Lakes Research, 13 ( 4 ), 407 – 435. https://doi.org/10.1016/S0380‐1330(87)71664‐5
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.