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Articles

Evaluating historical trends and influences of meteorological and seasonal climate conditions on lake chlorophyll a using remote sensing

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  • Acuña WC, Gonzalez CJ, Aqueveque VG. 2017. La Chimba, Antofagasta, Chile—oxygen depletion and hydrogen sulfide gas mitigation due to harmful algal blooms. Harmful algal blooms (HABs) and desalination: a guide to impacts, monitoring, and management. In: Anderson DM, Boerlage SFE, Dixon MB, editors. Paris (France): United Nations Educational, Scientific, and Cultural Organization (UNESCO). p. 391–8.
  • Ali K, Witter D, Ortiz J. 2014. Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in case 2 waters of Lake Erie. Environ Earth Sci. 71(9):4209–20. doi:10.1007/s12665-013-2814-0.
  • Allan MG, Hamilton DP, Hicks BJ, Brabyn L. 2011. Landsat remote sensing of chlorophyll a concentrations in central North Island lakes of New Zealand. Int J Remote Sens. 32(7):2037–55. doi:10.1080/01431161003645840.
  • Allan MG, Hamilton DP, Hicks BJ, Brabyn L. 2015. Empirical and semi-analytical chlorophyll a algorithms for multi-temporal monitoring of New Zealand lakes using Landsat. Environ Monit Assess. 187(6):364.
  • Alonso A, Muñoz-Carpena R, Kennedy RE, Murcia C. 2016. Wetland landscape spatio-temporal degradation dynamics using the new Google Earth Engine cloud-based platform: opportunities for non-specialists in remote sensing. Trans ASABE. 59:1331–42.
  • Anderson DM, Glibert PM, Burkholder JM. 2002. Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries. 25(4):704–26. doi:10.1007/BF02804901.
  • Arnow T, Stephens DW. 1990. Hydrologic characteristics of the Great Salt Lake, Utah, 1847-1986. US Geological Survey Water-Supply Paper.
  • Backer LC, McNeel SV, Barber T, Kirkpatrick B, Williams C, Irvin M, Zhou Y, Johnson TB, Nierenberg K, Aubel M, et al. 2010. Recreational exposure to microcystins during algal blooms in two California lakes. Toxicon. 55(5):909–21. doi:10.1016/j.toxicon.2009.07.006.
  • Bailey SW, Werdell PJ. 2006. A multi-sensor approach for the on-orbit validation of ocean color satellite data products. Remote Sens Environ. 102(1-2):12–23. doi:10.1016/j.rse.2006.01.015.
  • Bioeconomics, Inc. 2012. Economic significance of the Great Salt Lake to the State of Utah. Report for the Great Salt Lake Advisory Council. Missoula (MT): Bioeconomics, Inc.
  • Brezonik P, Menken K, Bauer M. 2005. Landsat-based remote sensing of lake water quality characteristics, including chlorophyll and colored dissolved organic matter (CDOM). Lake Reserv Manage. 21(4):373–82. doi:10.1080/07438140509354442.
  • Carlson RE. 1977. A trophic state index for lakes. Limnol Oceanogr. 22(2):361–9. doi:10.4319/lo.1977.22.2.0361.
  • Casterlin ME, Reynolds WW. 1977. Seasonal algal succession and cultural eutrophication in a north temperate lake. Hydrobiologia. 54(2):99–108. doi:10.1007/BF00034983.
  • Chen L, Delatolla R, D’Aoust PM, Wang R, Pick F, Poulain A, Rennie CD. 2017. Hypoxic conditions in stormwater retention ponds: potential for hydrogen sulfide emission. Environ Technol. 40:642–653.
  • Cox RR, Kadlec JA. 1995. Dynamics of potential waterfowl foods in Great Salt Lake marshes during summer. Wetlands. 15(1):1–8. doi:10.1007/BF03160674.
  • Duan H, Ma R, Xu X, Kong F, Zhang S, Kong W, Hao J, Shang L. 2009. Two-decade reconstruction of algal blooms in China’s Lake Taihu. Environ Sci Technol. 43(10):3522–8. doi:10.1021/es8031852.
  • Duan H, Zhang Y, Zhang B, Song K, Wang Z. 2007. Assessment of chlorophyll-a concentration and trophic state for Lake Chagan using Landsat TM and field spectral data. Environ Monit Assess. 129(1-3):295–308. doi:10.1007/s10661-006-9362-y.
  • Esterby SR. 1996. Review of methods for the detection and estimation of trends with emphasis on water quality applications. Hydrol Process. 10(2):127–49. doi:10.1002/(SICI)1099-1085(199602)10:2<127::AID-HYP354>3.0.CO;2-8.
  • Falconer IR. 1999. An overview of problems caused by toxic blue–green algae (cyanobacteria) in drinking and recreational water. Environ Toxicol. 14(1):5–12. doi:10.1002/(SICI)1522-7278(199902)14:1<5::AID-TOX3>3.0.CO;2-0.
  • Giardino C, Pepe M, Brivio PA, Ghezzi P, Zilioli E. 2001. Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imagery. Sci Total Environ. 268(1-3):19–29. doi:10.1016/S0048-9697(00)00692-6.
  • Goel R, Myers L. 2009. Evaluation of cyanotoxins in the Farmington Bay, Great Salt Lake, Utah. Project Report. [accessed 2016 Oct 20]. http://www.cdsewer.org/GSLRes/2009_CYANOBACTERIA_PROJECT_REPORT.pdf
  • Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R. 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ. 202:18–27. doi:10.1016/j.rse.2017.06.031.
  • Gurlin D, Gitelson AA, Moses WJ. 2011. Remote estimation of Chl-a concentration in turbid productive waters—return to a simple two-band NIR-red model? Remote Sens Environ. 115(12):3479–90. doi:10.1016/j.rse.2011.08.011.
  • Hansen CH, Burian SJ, Dennison PE, Williams GP. 2017. Spatiotemporal variability of lake water quality in the context of remote sensing models. Remote Sens. 9(5):409. doi:10.3390/rs9050409.
  • Hansen CH, Williams GP. 2018. Evaluating remote sensing model specification methods for estimating water quality in optically diverse lakes throughout the growing season. Hydrology. 5(4):62. doi:10.3390/hydrology5040062.
  • Hansen CH, Williams GP, Adjei Z, Barlow A, Nelson EJ, Miller AW. 2015. Reservoir water quality monitoring using remote sensing with seasonal models: case study of five central-Utah reservoirs. Lake Reserv Manage. 31(3):225–40. doi:10.1080/10402381.2015.1065937.
  • Heisler J, Glibert PM, Burkholder JM, Anderson DM, Cochlan W, Dennison WC, Dortch Q, Gobler CJ, Heil CA, Humphries E, et al. 2008. Eutrophication and harmful algal blooms: a scientific consensus. Harmful Algae. 8(1):3–13. doi:10.1016/j.hal.2008.08.006.
  • Hirsch RM, Slack JR, Smith RA. 1982. Techniques of trend analysis for monthly water quality data. Water Resour Res. 18(1):107–21. doi:10.1029/WR018i001p00107.
  • Ho JC, Michalak AM. 2017. Phytoplankton blooms in Lake Erie impacted by both long-term and springtime phosphorus loading. J Great Lakes Res. 43(3):221–8. doi:10.1016/j.jglr.2017.04.001.
  • Ho JC, Stumpf RP, Bridgeman TB, Michalak AM. 2017. Using Landsat to extend the historical record of lacustrine phytoplankton blooms: a Lake Erie case study. Remote Sens Environ. 191:273–85. doi:10.1016/j.rse.2016.12.013.
  • Hunter P. 1998. Cyanobacterial toxins and human health. J Appl Microbiol. 84(1):35–40.
  • [IOCCG] International Ocean-Colour Coordinating Group. 2006. Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications. Dartmouth (Canada): Reports of the International Ocean-Colour Coordinating Group, No. 5.
  • Kloiber SM, Brezonik PL, Olmanson LG, Bauer ME. 2002. A procedure for regional lake water clarity assessment using Landsat multispectral data. Remote Sens Environ. 82(1):38–47. doi:10.1016/S0034-4257(02)00022-6.
  • Komsta L. 2013. mblm: median-based linear models. R package version 0.12 [accessed 2018 April 12]. https://CRAN.R-project.org/package=mblm.
  • Larson CA, Belovsky GE. 2013. Salinity and nutrients influence species richness and evenness of phytoplankton communities in microcosm experiments from Great Salt Lake, Utah, USA. J Plankton Res. 35(5):1154–66. doi:10.1093/plankt/fbt053.
  • Lesht BM, Barbiero RP, Warren GJ. 2013. A band-ratio algorithm for retrieving open-lake chlorophyll values from satellite observations of the Great Lakes. J Great Lakes Res. 39(1):138–52. doi:10.1016/j.jglr.2012.12.007.
  • Manzo C, Bresciani M, Giardino C, Braga F, Bassani C. 2015. Sensitivity analysis of a bio-optical model for Italian lakes focused on Landsat-8, Sentinel-2 and Sentinel-3. Eur J Remote Sens. 48(1):17–32. doi:10.5721/EuJRS20154802.
  • Marden B, Miller T, Richards D. 2015. Factors influencing cyanobacteria blooms in Farmington Bay, Great Salt Lake, Utah. A progress report of scientific findings from the 2013 growing season. Kaysville (UT): The Jordan River/Farmington Bay Water Quality Council.
  • Masek JG, Vermote EF, Saleous NE, Wolfe R, Hall FG, Huemmrich KF, Gao F, Kutler J, Lim TK. 2006. A Landsat surface reflectance dataset for North America, 1990-2000. IEEE Geosci Remote Sensing Lett. 3(1):68–72. doi:10.1109/LGRS.2005.857030.
  • Matthews MW. 2011. A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. Int J Remote Sens. 32(21):6855–99. doi:10.1080/01431161.2010.512947.
  • McCullough IM, Loftin CS, Sader SA. 2013. Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010. Freshwater Sci. 32(3):741–52. doi:10.1899/12-070.1.
  • Nelder JA, Wedderburn R. 1972. Generalized linear models. J Roy Statist Soc Ser A (Gen). 135(3):370–84. doi:10.2307/2344614.
  • Olmanson LG, Bauer ME, Brezonik PL. 2008. A 20-year Landsat water clarity census of Minnesota’s 10,000 lakes. Remote Sens Environ. 112(11):4086–97. doi:10.1016/j.rse.2007.12.013.
  • Page BP, Kumar A, Mishra DR. 2018. A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom. Int J Appl Earth Obs Geoinf. 66:69–81. doi:10.1016/j.jag.2017.11.003.
  • Palmer SC, Kutser T, Hunter PD. 2015. Remote sensing of inland waters: challenges, progress and future directions. Remote Sens Environ. 157:1–8. doi:10.1016/j.rse.2014.09.021.
  • Paerl, HW. 1988. Nuisance phytoplankton blooms in coastal, estuarine, and inland waters. Limnology and Oceanography, 33(4, part 2), 823–843.
  • Paerl, HW, Fulton, RS, Moisander, PH, Dyble, J. 2001. Harmful freshwater algal blooms, with an emphasis on cyanobacteria. The Scientific World Journal, 1, 76–113.
  • Paerl, HW, Otten, TG. 2013. Harmful cyanobacterial blooms: causes, consequences, and controls. Microbial Ecology, 65(4), 995–1010.
  • Pekel JF, Cottam A, Gorelick N, Belward AS. 2016. High-resolution mapping of global surface water and its long-term changes. Nature. 540(7633):418–22. doi:10.1038/nature20584.
  • R Core Team. 2018. R: a language and environment for statistical computing. Vienna, (Austria): R Foundation for Statistical Computing. Available from https://www.R-project.org/.
  • Rushforth SR, Squires LE. 1985. New records and comprehensive list of the algal taxa of Utah Lake, Utah, USA. Great Basin Nat. 45:237–54.
  • Rushforth SR, St. Clair LL, Grimes JA, Whiting MC. 1981. Phytoplankton of Utah Lake. Great Basin Nat Mem. 5:85–100.
  • Smith, VH. 2003. Eutrophication of freshwater and coastal marine ecosystems a global problem. Environmental Science and Pollution Research, 10(2), 126–139.
  • Stadelmann TH, Brezonik PL, Kloiber S. 2001. Seasonal patterns of chlorophyll a and Secchi disk transparency in lakes of East-Central Minnesota: implications for design of ground-and satellite-based monitoring programs. Lake Reserv Manage. 17(4):299–314. doi:10.1080/07438140109354137.
  • Strong AE. 1974. Remote sensing of algal blooms by aircraft and satellite in Lake Erie and Utah Lake. Remote Sens Environ. 3(2):99–107. doi:10.1016/0034-4257(74)90052-2.
  • Tellman B, Sullivan J, Kettner A, Brakenridge G, Slayback D, Kuhn C, Doyle C. 2016. Developing a global database of historic flood events to support machine learning flood prediction in Google Earth Engine. AGU Fall Meeting Abstracts.
  • Toming K, Kutser T, Laas A, Sepp M, Paavel B, Nõges T. 2016. First experiences in mapping lake water quality parameters with Sentinel-2 MSI imagery. Remote Sens. 8(8):640. doi:10.3390/rs8080640.
  • Torbick N, Hession S, Hagen S, Wiangwang N, Becker B, Qi J. 2013. Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery. Int J Remote Sens. 34(21):7607–24. doi:10.1080/01431161.2013.822602.
  • [UDEQ] Utah Department of Environmental Quality 2006. Utah Lake report. Watershed Management Program.
  • [UDEQ] Utah Department of Environmental Quality 2018. Harmful algal bloom events. [accessed 2019 Jan 10]. https://deq.utah.gov/legacy/divisions/water-quality/health-advisory/harmful-algal-blooms/bloom-events/index.htm.
  • [USEPA] US Environmental Protection Agency. 2017. Recommendations for cyanobacteria and cyanotoxin monitoring in recreational waters. EPA/820/R-17/001. [accessed 2019 March 8]. https://www.epa.gov/sites/production/files/2017-07/documents/08_july_3_monitoring_document_508c_7.5.17.pdf
  • [USGS] US Geologic Survey. 2018. Landsat 4-7 surface reflectance (LEDAPS) product guide. Version 1.0. Sioux Falls (SD): EROS.
  • [USGS] US Geologic Survey: Utah Water Science Center. 2013. Great Salt Lake—salinity and water quality. [accessed 2017 Apr 5]. https://ut.water.usgs.gov/greatsaltlake/salinity/.
  • Whiting MC, Brotherson JD, Rushforth SR. 1978. Environmental interaction in summer algal communities of Utah Lake. West North Am Nat. 38(1):31–41.
  • Wurtsbaugh WA. 2008. Nutrient loading and eutrophication in the Great Salt Lake. Watershed Sciences Faculty Publications 299. [accessed 2018 June 19]. https://digitalcommons.usu.edu/wats_facpub/299
  • Wurtsbaugh WA, Marcarelli A, Boyer G. 2012. Eutrophication and metal concentrations in three bays of the Great Salt Lake (USA). Final Report to the Utah Division of Water Quality, Salt Lake City, Utah.
  • Xu, H. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International journal of remote sensing, 27(14), 3025–3033.

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