Skip to main content

Advertisement

SpringerLink
Log in

Spatiotemporal Analysis of Water Quality Indicators in Small Lakes Using Sentinel-2 Satellite Data: Lake Bloomington and Evergreen Lake, Central Illinois, USA

  • Original Article
  • Published:
Environmental Processes Aims and scope Submit manuscript

Abstract

Lake water quality issue related to algal blooms is a serious problem in basins with abundant agricultural lands, causing harmful effects to freshwater ecosystems and decreasing water quality for human uses. Remote sensing methods have been used to monitor water quality of large lakes and coastal areas; however, few studies have been conducted to understand spectral properties of small lakes. This research explores applicability of Sentinel-2 satellite in understanding spatiotemporal patterns of water quality of two small-sized reservoirs, Lake Bloomington and Evergreen Lake, Central Illinois. We tested the feasibility of Sentinel-2 satellite data for monitoring algal blooms by comparing and calibrating multiple satellite algorithms (e.g., Bottom-of-Atmosphere (BOA) reflectance, Maximum Chlorophyll Index (MCI), and band ratios) against lake water quality indicator variables (e.g., chlorophyll-a, turbidity, secchi depth) obtained from water sample analysis in the laboratory or field measurements. The regression models performed better for Evergreen Lake than Lake Bloomington. Comparison of chlorophyll-a and turbidity with satellite reflectance values showed that suspended sediments contribute to the turbidity in the case of Lake Bloomington, while the algae contribute to the turbidity in Evergreen Lake. Using regression models, water quality indicator maps were created, showing the spatial pattern of algae in the lakes, generally, showing heterogeneous chlorophyll-a distribution, lower in downstream and higher in upstream areas. The study confirmed suitability of Sentinel-2 data for monitoring water quality of less turbid small-sized lake.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data Availability

The data that support the findings of this study are available from the corresponding author on request.

References

  • Anderson DM, Glibert PM, Burkholder JM (2002) Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries 25:704–726

    Article  Google Scholar 

  • Bartram J, Chorus I (1999) Toxic cyanobacteria in water: a guide to their public health consequences, monitoring and management. E & FN Spon, London

    Book  Google Scholar 

  • Braig IVEC, Conroy J, Lichtkoppler F, Lynch WE Jr, Merchant-Masonbrink L (2011) Harmful algal blooms in Ohio waters. Ohio Sea Grant, Fact Sheet. The Ohio State University, Columbus, pp 1–4

    Google Scholar 

  • Bresciani M, Cazzaniga I, Austoni M, Sforzi T, Buzzi F, Morabito G, Giardino C (2018) Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8. Hydrobiologia 824:197–214

    Article  Google Scholar 

  • Campbell JB, Wynne RH (2011) Introduction to remote sensing. Guilford Press, New York

    Google Scholar 

  • Carmichael W (2008) A world overview—One-hundred-twenty-seven years of research on toxic cyanobacteria—Where do we go from here? In: Hudnell HK (eds) Cyanobacterial Harmful Algal Blooms: State of the Science and Research Needs. Advances in Experimental Medicine and Biology, vol 619. Springer, New York, NY. pp 105–125. https://doi.org/10.1007/978-0-387-75865-7_4

  • Chen J, Zhu W, Tian YQ, Yu Q, Zheng Y, Huang L (2017) Remote estimation of colored dissolved organic matter and chlorophyll-a in Lake Huron using Sentinel-2 measurements. J Appl Remote Sens 11:036007

    Google Scholar 

  • Clark JM, Schaeffer BA, Darling JA, Urquhart EA, Johnston JM, Ignatius AR, Myer MH, Loftin KA, Werdell PJ, Stumpf RP (2017) Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources. Ecol Indic 80:84–95

    Article  Google Scholar 

  • Collman RD, Cochran CC, Werner SE (2002) Soil Survey of McLean County, Illinois. Natural Resources Conservation Service, United States Department of Agriculture, in cooperation with the Illinois Agricultural Experiment Station, Washington, DC

  • Copernicus Open Access Hub (n.d.) Sentinel-2 Data. Reterieved from Copernicus Open Access Hub, https://www.scihubcopernicuseu/. Accessed 13 Oct 2019

  • Delegido J, Verrelst J, Alonso L, Moreno J (2011) Evaluation of sentinel-2 red-edge bands for empirical estimation of green LAI and chlorophyll content. Sensors 11:7063–7081

    Article  Google Scholar 

  • Djamai N, Fernandes R (2018) Comparison of SNAP-derived Sentinel-2A L2A product to ESA product over Europe. Remote Sens 10:926

    Article  Google Scholar 

  • Doxaran D, Froidefond J-M, Lavender S, Castaing P (2002) Spectral signature of highly turbid waters: Application with SPOT data to quantify suspended particulate matter concentrations. Remote Sens Environ 81:149–161. https://doi.org/10.1016/S0034-4257(01)00341-8

    Article  Google Scholar 

  • Feng L, Hu C, Chen X, Song Q (2014) Influence of the Three Gorges Dam on total suspended matters in the Yangtze Estuary and its adjacent coastal waters: Observations from MODIS. Remote Sens Environ 140:779–788. https://doi.org/10.1016/j.rse.2013.10.002

    Article  Google Scholar 

  • Fu FX, Tatters AO, Hutchins DA (2012) Global change and the future of harmful algal blooms in the ocean. Mar Ecol Prog Ser 470:207–233

    Article  Google Scholar 

  • Glibert PM, Anderson DM, Gentien P, Granéli E, Sellner KG (2005) The global, complex phenomena of harmful algal blooms. Oceanography 18:136–147. https://doi.org/10.5670/oceanog.2005.49

    Article  Google Scholar 

  • Gomaa MN, Mulla DJ, Galzki JC, Sheikho KM, Alhazmi NM, Mohamed HE, Hannachi I, Abouwarda AM, Hassan EA, Carmichael WW (2020) Red sea MODIS estimates of chlorophyll a and phytoplankton biomass risks to Saudi Arabian coastal desalination plants. J Mar Sci Eng 9. https://doi.org/10.3390/jmse9010011

  • Gower J, Doerffer R, Borstad G (1999) Interpretation of the 685nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS. Int J Remote Sens 20:1771–1786

    Article  Google Scholar 

  • Guo F, Kainz MJ, Sheldon F, Bunn SE (2016) The importance of high-quality algal food sources in stream food webs–current status and future perspectives. Freshwat Biol 61:815–831

    Article  Google Scholar 

  • Gupta RP (2003) Remote sensing geology, 2 edn. Springer, Verlag Berlin Heidelberg

    Book  Google Scholar 

  • Ha NTT, Thao NTP, Koike K, Nhuan MT (2017) Selecting the best band ratio to estimate chlorophyll-a concentration in a tropical freshwater lake using sentinel 2A images from a case study of Lake Ba Be (Northern Vietnam). ISPRS Int J Geo Inf 6:290

    Article  Google Scholar 

  • Hajigholizadeh M, Moncada A, Kent S, Melesse AM (2021) Land–lake linkage and remote sensing application in water quality monitoring in Lake Okeechobee, Florida, USA. Land 10. https://doi.org/10.3390/land10020147

  • Hanna LA (2013) Dissolved and suspended sediment transport dynamics in two agriculturally dominated watersheds, McLean County, Illinois. Thesis, Illinois State University

  • Havens KE (2008) Cyanobacteria blooms: effects on aquatic ecosystems. Adv Exp Med Biol 619:733–747. https://doi.org/10.1007/978-0-387-75865-7_33

    Article  Google Scholar 

  • Hilborn ED, Roberts VA, Backer L, Wade T, Yoder J, Hlavsa M (2014) Algal bloom-associated disease outbreaks among users of freshwater lakes-United States, 2009–2010. MMWR Morbidity and mortality weekly report. U.S. Department of Health and Human Services, Washington, DC, pp 11–25

    Google Scholar 

  • Hudnell HK (2008) Cyanobacterial Harmful Algal Blooms: State of the Science and Research Needs, 1 edn. Springer-Verlag, New York

    Book  Google Scholar 

  • Huovinen P, Ramírez J, Caputo L, Gómez I (2019) Mapping of spatial and temporal variation of water characteristics through satellite remote sensing in Lake Panguipulli, Chile. Sci Total Environ 679:196–208. https://doi.org/10.1016/j.scitotenv.2019.04.367

    Article  Google Scholar 

  • Isenstein EM, Trescott A, Park M-H (2014) Multispectral remote sensing of harmful algal blooms in Lake Champlain, USA. Water Environ Res 86:2271–2278

    Article  Google Scholar 

  • Kelly T, Herida J, Mothes J (1998) Sampling of the Mackinaw River in central Illinois for physicochemical and bacterial indicators of pollution. Trans Ill State Acad Sci 91:145–154

    Google Scholar 

  • Kilham NE, Roberts D, Singer MB (2012) Remote sensing of suspended sediment concentration during turbid flood conditions on the Feather River, California—A modeling approach. Water Resour Res 48. https://doi.org/10.1029/2011WR010391

  • Kloiber SM, Brezonik PL, Olmanson LG, Bauer ME (2002) A procedure for regional lake water clarity assessment using Landsat multispectral data. Remote Sens Environ 82:38–47

    Article  Google Scholar 

  • Li R, Li J (2004) Satellite remote sensing technology for lake water clarity monitoring: an overview. Environ Inf Arch 2:893–901

    Google Scholar 

  • Lim J, Choi M (2015) Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea. Environ Monit Assess 187:384

    Article  Google Scholar 

  • Liu H, Li Q, Shi T, Hu S, Wu G, Zhou Q (2017) Application of sentinel 2 MSI images to retrieve suspended particulate matter concentrations in Poyang Lake. Remote Sens 9:761

    Article  Google Scholar 

  • Ma J, Jin S, Li J, He Y, Shang W (2021) Spatio-temporal variations and driving forces of harmful algal blooms in Chaohu Lake: a multi-source remote sensing approach. Remote Sens 13:427–450. https://doi.org/10.3390/rs13030427

    Article  Google Scholar 

  • Main-Knorn M, Pflug B, Debaecker V, Louis J (2015) Calibration and validation plan for the L2A processor and products of the SENTINEL-2 mission. ISPRS - Int Arch Photogramm Remote Sens Spat Inf Sci XL7:1249. https://doi.org/10.5194/isprsarchives-XL-7-W3-1249-2015

  • Martimort P, Arino O, Berger M, Biasutti R, Carnicero B, Del Bello U, Fernandez V, Gascon F, Greco B, Silvestrin P (2007) Sentinel-2 optical high resolution mission for GMES operational services. 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain. IEEE, pp 2677–2680

  • Matthews MW, Bernard S, Winter K (2010) Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS. Remote Sens Environ 114:2070–2087

    Article  Google Scholar 

  • Meyers MD (2014) The relationship between environmental factors and cyanobacteria population in Lake Bloomington and Evergreen Lake in McLean County, Illinois. Thesis, Illinois State University

  • Muller-Wilm U, Louis J, Richter R, Gascon F, Niezette M (2013) Sentinel-2 level 2A prototype processor: Architecture, algorithms and first results. ESA Living Planet Symposium 2013, Edinburgh, UK, pp 9–13

  • Nechad B, Ruddick KG, Park Y (2010) Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sens Environ 114:854–866. https://doi.org/10.1016/j.rse.2009.11.022

    Article  Google Scholar 

  • Olmanson LG, Bauer ME, Brezonik PL (2002) Use of Landsat imagery to develop a water quality atlas of Minnesota’s 10,000 lakes. Proceedings of FIEOS 2002, Conference/Land Satellite Information IV/ISPRS Commission I, April 25–27, 2002, Washington, DC

  • Papenfus M, Schaeffer B, Pollard AI, Loftin K (2020) Exploring the potential value of satellite remote sensing to monitor chlorophyll-a for US lakes and reservoirs. Environ Monit Assess 192:808. https://doi.org/10.1007/s10661-020-08631-5

    Article  Google Scholar 

  • Pettersson K (1998) Mechanisms for internal loading of phosphorus in lakes. Hydrobiologia 373:21–25

    Article  Google Scholar 

  • Raman RK, Twait RM (1994) Water quality characteristics of Lake Bloomington and Lake Evergreen. ISWS Contract Report CR-569. Illinois State Water Survey. Division of the Illinois Department of Energy and Natural Resources, Champaign

    Google Scholar 

  • RBINS ACOLITE (2020) Atmospheric Correction Processor. https://odnature.naturalsciences.be/remsem/software-and-data/acolite. Accessed July 2020

  • Richards JA, Richards J (1999) Remote sensing digital image analysis. Springer, Berlin

    Book  Google Scholar 

  • Richardson LL (1996) Remote sensing of algal bloom dynamics. Bioscience 46:492–501

    Article  Google Scholar 

  • Ritchie JC, Zimba PV, Everitt JH (2003) Remote sensing techniques to assess water quality. Photogramm Eng Remote Sens 69:695–704

    Article  Google Scholar 

  • Roberts WJ (1948) Hydrology of five Illinois water supply reservoirs. Bulletin (Illinois State Water Survey) no 38. Illinois State Water Survey, Urbana, p 262

    Google Scholar 

  • Seyoum WM (2018) Characterizing water storage trends and regional climate influence using GRACE observation and satellite altimetry data in the Upper Blue Nile River Basin. J Hydrol 566:274–284. https://doi.org/10.1016/j.jhydrol.2018.09.025

    Article  Google Scholar 

  • SNAP (2018) ESA Sentinel Application Platform v8.0.0. https://step.esa.int/main/toolboxes/snap/. Accessed Oct 2019

  • Seyoum MW, Kwon D, Milewski MA (2019) Downscaling GRACE TWSA Data into high-resolution groundwater level anomaly using machine learning-based models in a glacial aquifer system. Remote Sens 11. https://doi.org/10.3390/rs11070824

  • Seyoum WM, Milewski AM (2016) Monitoring and comparison of terrestrial water storage changes in the northern high plains using GRACE and in-situ based integrated hydrologic model estimates. Adv Water Resour 94:31–44. https://doi.org/10.1016/j.advwatres.2016.04.014

    Article  Google Scholar 

  • Seyoum WM, Milewski AM, Durham MC (2015) Understanding the relative impacts of natural processes and human activities on the hydrology of the Central Rift Valley lakes, East Africa. Hydrol Process 29:4312–4324. https://doi.org/10.1002/hyp.10490

    Article  Google Scholar 

  • Shen M, Wang S, Li Y, Tang M, Ma Y (2021) Pattern of turbidity change in the middle reaches of the Yarlung Zangbo River, Southern Tibetan Plateau, from 2007 to 2017. Remote Sens 13. https://doi.org/10.3390/rs13020182

  • 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 Manag 17:299–314

    Article  Google Scholar 

  • Stall JB, Rupani NL, Kandaswamy P (1958) Sediment transport in Money Creek. J Hydraul Div, Proc Am Soc Civ Eng 84:1–27

  • Stevenson J (2014) Ecological assessments with algae: a review and synthesis. J Phycol 50:437–461

    Article  Google Scholar 

  • Stumpf RP, Davis TW, Wynne TT, Graham JL, Loftin KA, Johengen TH, Gossiaux D, Palladino D, Burtner A (2016) Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria. Harmful Algae 54:160–173

    Article  Google Scholar 

  • 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 8:640

    Article  Google Scholar 

  • Watanabe F, Alcantara E, Rodrigues T, Rotta L, Bernardo N, Imai N (2018) Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil). An Acad Bras Cienc 90:1987–2000

    Article  Google Scholar 

  • Wetzel RG, Likens GE (2013) Limnological analyses, 3rd edn. Springer Science & Business Media, New York

    Google Scholar 

  • Zhu W, Yu Q, Tian YQ, Becker BL, Carrick H (2014) Issues and potential improvement of multiband models for remotely estimating chlorophyll-a in complex inland waters. IEEE J Sel Top Appl Earth Obs Remote Sens 8:562–575

    Article  Google Scholar 

Download references

Acknowledgements

We greatly acknowledged the City of Bloomington and Illinois Lake Management Association for providing support to conduct this research.

Author information

Authors and Affiliations

  1. Department of Geography, Geology, and the Environment, Illinois State University, Normal, IL, USA

    Gare Ambrose-Igho, Wondwosen M. Seyoum & Catherine M. O’Reilly

  2. School of Biological Sciences, Illinois State University, Normal, IL, USA

    William L. Perry

Authors
  1. Gare Ambrose-Igho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wondwosen M. Seyoum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. William L. Perry
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Catherine M. O’Reilly
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Gare Ambrose-Igho with the support and guidance from Wondwosen M. Seyoum, William L. Perry, and Catherin M. O’Reilly. The first draft of the manuscript was written by Gare Ambrose-Igho and all authors commented and revised all previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wondwosen M. Seyoum.

Ethics declarations

Conflict of Interest

The authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ambrose-Igho, G., Seyoum, W.M., Perry, W.L. et al. Spatiotemporal Analysis of Water Quality Indicators in Small Lakes Using Sentinel-2 Satellite Data: Lake Bloomington and Evergreen Lake, Central Illinois, USA. Environ. Process. 8, 637–660 (2021). https://doi.org/10.1007/s40710-021-00519-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40710-021-00519-x

Keywords

Search

Navigation