Exploiting high frequency monitoring and satellite imagery for assessing chlorophyll-a dynamics in a shallow eutrophic lake

Submitted: 8 May 2021
Accepted: 15 June 2021
Published: 13 July 2021
Abstract Views: 1399
PDF: 252
Supplementary 1: 48
Supplementary 2: 53
Supplementary 3: 52
HTML: 59
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Freshwater ecosystems are challenged by cultural eutrophication across the globe, and it is a priority for water managers to implement water quality monitoring at different spatio-temporal scales to control and mitigate the eutrophication process. Phytoplankton abundance is a key indicator of the trophic and water quality status of lakes. Phytoplankton dynamics are characterized by high spatio-temporal variation, driven by physical, chemical and biological factors, that challenge the capacity of routine monitoring with conventional sampling techniques (i.e., boat based sampling) to characterise these complex relationships. In this study, high frequency in situ measurements and multispectral satellite data were used in a synergistic way to explore temporal (diurnal and seasonal) dynamics and spatial distribution of Chlorophyll-a (Chl-a) concentration, a proxy of phytoplankton abundance, together with physico-chemical water parameters in a shallow fluvial-lake system (Mantua Lakes). A good agreement was found between Chl-a retrieved by remote sensing data and Chl-a fluorescence data recorded by multi-parameters probes (R2 = 0.94). The Chl-a maps allowed a seasonal classification of the Mantua Lakes system as eutrophic or hypertrophic. Along the Mantua lakes system an increasing gradient in Chl-a concentration was recorded following the transition from a fluvial to lacustrine system. There was significant seasonal heterogeneity among the sub-basins, probably due to different hydrodynamics, influenced also by macrophyte stands. High-frequency data revealed the importance of rainfall events in the timing and growth dynamics of phytoplankton, particularly for spring and late summer blooms. Combining temporal and spatial data at high resolution improves the understanding of complex fluvial-lake systems. This technique can allow managers to target blooms in near-real time as they move through a system and guide them to localized hot spots enabling timely management action in ecosystems of high conservation and recreational value.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

APHA, AWWA, WPCF, 1981. Standard methods for the examination of water and wastewater. Washington, American Public Health Association.
Arheimer B, Brandt M, 1998. Modelling nitrogen transport and retention in the catchments of Southern Sweden. Ambio 27:471-480.
Ansper A, Alikas K, 2019. Retrieval of chlorophyll a from Sentinel-2 MSI data for the European Union water framework directive reporting purposes. Remote Sens.-Basel 11:64. DOI: https://doi.org/10.3390/rs11010064
Avigliano L, Vinocour A, Chaparro G, Tell G, Allende L, 2014. Influence of re-flooding on phytoplankton assemblages in a temperate wetland following prolonged drought. J. Limnol. 73:838. DOI: https://doi.org/10.4081/jlimnol.2014.838
Beniston M, Stephenson DB, Christensen OB, Ferro CA, Frei C, Goyette S, et al., 2007. Future extreme events in European climate: an exploration of regional climate model projections. Climatic Change 81:71-95. DOI: https://doi.org/10.1007/s10584-006-9226-z
Bennett MG, Schofield KA, Lee SS, Norton SB, 2017. Response of chlorophyll a to total nitrogen and total phosphorus concentrations in lotic ecosystems: a systematic review protocol. Environ. Evid. 6:1-3. DOI: https://doi.org/10.1186/s13750-017-0097-8
Bergamino N, Horion S, Stenuite S, Cornet Y, Loiselle S, Plisnier PD, Descy JP, 2010. Spatio-temporal dynamics of phytoplankton and primary production in Lake Tanganyika using a MODIS based bio-optical time series. Remote Sens. Environ. 114:772-780. DOI: https://doi.org/10.1016/j.rse.2009.11.013
Boggero A, Fontaneto D, Morabito G, Volta P, 2014. Limnology in the 21st century: the importance of freshwater ecosystems as model systems in ecology and evolution. J. Limnol. 73:948. DOI: https://doi.org/10.4081/jlimnol.2014.948
Bolpagni R, Bresciani M, Laini A et al., 2014. Remote sensing of phytoplankton-macrophyte coexistence in shallow hypereutrophic fluvial lakes. Hydrobiologia 737:67-76. DOI: https://doi.org/10.1007/s10750-013-1800-6
Bowes MJ, Loewenthal M, Read DS, Hutchins MG, Prudhomme C, Armstrong LK, Harman SA, Wickham HD, Gozzard E, Carvalho L, 2016. Identifying multiple stressor controls on phytoplankton dynamics in the River Thames (UK) using high-frequency water quality data. Sci. Total Environ. 569:1489-1499. DOI: https://doi.org/10.1016/j.scitotenv.2016.06.239
Brentrup JA, Williamson CE, Colom-Montero W, Eckert W, de Eyto E, Grossart HP, Huot Y, Isles PD, Knoll LB, Leach TH, McBride CG, 2016. The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: an extension of the Plankton Ecology Group (PEG) model. Inland Waters 6:565-580. DOI: https://doi.org/10.5268/IW-6.4.890
Bresciani M, Rossini M, Morabito G, Matta E, Pinardi M, Cogliati S, et al., 2013. Analysis of within-and between-day chlorophyll-a dynamics in Mantua Superior Lake, with a continuous spectroradiometric measurement. Mar. Freshw. Res. 64:303-316. DOI: https://doi.org/10.1071/MF12229
Bresciani M, Giardino C, Lauceri R, Matta E, Cazzaniga I, Pinardi M, Lami A, Austoni M, Viaggiu E, Congestri R, Morabito G, 2017. Earth observation for monitoring and mapping of cyanobacteria blooms. Case studies on five Italian lakes. J Limnol. 76:1565. DOI: https://doi.org/10.4081/jlimnol.2016.1565
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. DOI: https://doi.org/10.1007/s10750-017-3462-2
Bresciani M, Pinardi M, Free G, Luciani G, Ghebrehiwot S, Laanen M, et al., 2020. The use of multisource optical sensors to study phytoplankton spatio-temporal variation in a Shallow Turbid Lake. Water 12:284. DOI: https://doi.org/10.3390/w12010284
Bukata RP, 2005. Satellite monitoring of inland and coastal water quality: retrospection, introspection, future directions. CRC Press: 272 pp. DOI: https://doi.org/10.1201/9780849333569
Carpenter SR, Stanley EH, Vander Zanden MJ, 2011. State of the world’s freshwater ecosystems: physical, chemical, and biological changes. Annu. Rev. Environ. Resour. 36:75-99. DOI: https://doi.org/10.1146/annurev-environ-021810-094524
Carpenter SR, 2008. Phosphorus control is critical to mitigating eutrophication. Proc. Natl. Acad. Sci. USA 105:11039–11040. DOI: https://doi.org/10.1073/pnas.0806112105
Carstensen J, Henriksen P, Heiskanen AS, 2007. Summer algal blooms in shallow estuaries: definition, mechanisms, and link to eutrophication. Limnol. Oceanogr. 52:370-384. DOI: https://doi.org/10.4319/lo.2007.52.1.0370
Carvalho L, Mackay EB, Cardoso AC, Baattrup-Pedersen A, Birk S, Blackstock KL, Borics G, Borja A, Feld CK, Ferreira MT, 2019. Protecting and restoring Europe’s waters: An analysis of the future development needs of the water framework directive. Sci. Total Environ. 658:1228–38. DOI: https://doi.org/10.1016/j.scitotenv.2018.12.255
Carvalho L, McDonald C, de Hoyos C, Mischke U, Phillips G, Borics G, Poikane S, Skjelbred B, Solheim AL, van Wichelen J, Cardoso AC, Cadotte M, 2013. Sustaining recreational quality of European lakes: minimizing the health risks from algal blooms through phosphorus control. J. Appl. Ecol. 50:315-323. DOI: https://doi.org/10.1111/1365-2664.12059
Catherine A, Escoffier N, Belhocine A, Nasri AB, Hamlaoui S, Yéprémian C, Bernard C, Troussellier M, 2012. On the use of the FluoroProbe®, a phytoplankton quantification method based on fluorescence excitation spectra for large-scale surveys of lakes and reservoirs. Water Res. 46:1771-84. DOI: https://doi.org/10.1016/j.watres.2011.12.056
Conley DJ, Paerl HW, Howarth RW, Boesch DF, Seitzinger SP, Havens KE, et al. 2009. Controlling eutrophication: nitrogen and phosphorus. Science 323:1014–5. DOI: https://doi.org/10.1126/science.1167755
De Tezanos Pinto P, O'Farrell I, 2014. Regime shifts between free-floating plants and phytoplankton: a review. Hydrobiologia 740:13-24. DOI: https://doi.org/10.1007/s10750-014-1943-0
Dörnhöfer K, Oppelt N, 2016. Remote sensing for lake research and monitoring–Recent advances. Ecol. Indic. 64:105-122. DOI: https://doi.org/10.1016/j.ecolind.2015.12.009
Dörnhöfer K, Klinger P, Heege T, Oppelt N, 2018. Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake. Sci. Total Environ. 612:1200-1214. DOI: https://doi.org/10.1016/j.scitotenv.2017.08.219
Duan HT, Ma RH, Xu XF, Kong FX, Zhang SX, Kong WJ, et al., 2009. Two decade reconstruction of algal blooms in China's Lake Taihu. Environ. Sci. Technol. 43:3522-3528. DOI: https://doi.org/10.1021/es8031852
European Commission, 2000. Directive 2000/60/EC of the European Parliament and of the council of 23rd October 2000 establishing a framework for community action in the field of water policy. Official Journal of the European Communities, L327/1, Brussels.
Falkowski P, Kiefer DA, 1985. Chlorophyll a fluorescence in phytoplankton: relationship to photosynthesis and biomass. J. Plankton Res. 7:715-31. DOI: https://doi.org/10.1093/plankt/7.5.715
Gilerson AA, Gitelson AA, Zhou J, Gurlin D, Moses W, Ioannou I, Ahmed SA, 2010. Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands. Opt.Express 18:24109-24125. DOI: https://doi.org/10.1364/OE.18.024109
Gillett ND, Luttenton MR, Steinman AD, 2015. Spatial and temporal dynamics of phytoplankton communities in a Great Lakes drowned river-mouth lake (Mona Lake, USA). J. Limnol. 74:1055. DOI: https://doi.org/10.4081/jlimnol.2015.1055
Ha NTT, Koike K, Nhuan MT, Canh BD, Thao NTP, Parsons M, 2017. Landsat 8/OLI two bands ratio algorithm for chlorophyll a concentration mapping in hypertrophic waters: An application to West Lake in Hanoi (Vietnam). IEEE J. Sel. Top. Appl. 10:4919-4929. DOI: https://doi.org/10.1109/JSTARS.2017.2739184
Hamilton DP, O’Brien KR, Burford MA, Brookes JD, McBride CG, 2010. Vertical distributions of chlorophyll in deep, warm monomictic lakes. Aquat. Sci. 72:295-307. DOI: https://doi.org/10.1007/s00027-010-0131-1
Hanjra MA, Qureshi ME, 2010. Global water crisis and future food security in an era of climate change. Food Pol. 35:365-377. DOI: https://doi.org/10.1016/j.foodpol.2010.05.006
Hestir EL, Brando VE, Bresciani M, Giardino C, Matta E, Villa P, Dekker AG, 2015. Measuring freshwater aquatic ecosystems: The need for a hyperspectral global mapping satellite mission. Remote Sens. Environ. 167:181-195. DOI: https://doi.org/10.1016/j.rse.2015.05.023
Huang C, Shi K, Yang H, Li Y, Zhu AX, Sun D, Xu L, Chen X, 2015. Satellite observation of hourly dynamic characteristics of algae with Geostationary Ocean Color Imager (GOCI) data in Lake Taihu. Remote Sens. Environ. 159:278-287. DOI: https://doi.org/10.1016/j.rse.2014.12.016
Huot Y, Babin M, 2010. Overview of fluorescence protocols: theory, basic concepts, and practice, p. 31-74. In: D.J. Suggett, M.A. Borowitzka and O. Prášil (eds.), Chlorophyll a fluorescence in aquatic sciences: Methods and applications. Dordrecht, Springer. DOI: https://doi.org/10.1007/978-90-481-9268-7_3
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. DOI: https://doi.org/10.1016/j.scitotenv.2019.04.367
Jennings E, Jones S, Arvola L, Staehr PA, Gaiser E, Jones ID, et al., 2012. Effects of weather‐related episodic events in lakes: An analysis based on high‐frequency data. Freshwater Biol. 57:589-601. DOI: https://doi.org/10.1111/j.1365-2427.2011.02729.x
Jeppesen E, Jensen JP, Jensen C, Faafeng B, Hessen DO, Søndergaard M, Lauridsen T, Brettum P, Christoffersen K, 2003. The impact of nutrient state and lake depth on top-down control in the pelagic zone of lakes: a study of 466 lakes from the temperate zone to the Arctic. Ecosystems 6:313-325. DOI: https://doi.org/10.1007/PL00021503
Jindal R, Thakur RK, 2013. Diurnal variations of plankton diversity and physico-chemical characteristics of Rewalsar Wetland, Himachal Pradesh, India. Rec. Res. Sci. Technol. 5:4-9.
Jones ID, Elliott JA, 2007. Modelling the effects of changing retention time on abundance and composition of phytoplankton species in a small lake. Freshwater Biol. 52:988–997. DOI: https://doi.org/10.1111/j.1365-2427.2007.01746.x
Kaplan DM, Largier JL, Navarrete S, Guiñez R, Castilla JC, 2003. Large diurnal temperature fluctuations in the nearshore water column. Estuar. Coast. Shelf S. 57:385-398. DOI: https://doi.org/10.1016/S0272-7714(02)00363-3
Kiefer I, Odermatt D, Anneville O, Wüest A, Bouffard D, 2015. Application of remote sensing for the optimization of in-situ sampling for monitoring of phytoplankton abundance in a large lake. Sci. Total Environ. 527:493-506. DOI: https://doi.org/10.1016/j.scitotenv.2015.05.011
Klemas V, 2013. Remote sensing of emergent and submerged wetlands: an overview. Int. J. Remote Sens. 34:6286-6320. DOI: https://doi.org/10.1080/01431161.2013.800656
Izaguirre I, Pizarro H, de Tezanos Pinto P, Rodríguez P, O'Farrell I, Unrein F, Gasol JM, 2010. Macrophyte influence on the structure and productivity of photosynthetic picoplankton in wetlands. J. Plankton Res. 32:221-238. DOI: https://doi.org/10.1093/plankt/fbp115
Laney SR, 2010. In situ measurement of variable fluorescence transients, p. 19-30. In: D.J. Suggett, M.A. Borowitzka and O. Prášil (eds.), Chlorophyll a fluorescence in aquatic sciences: Methods and applications. Dordrecht, Springer. DOI: https://doi.org/10.1007/978-90-481-9268-7_2
Leal MC, Sá C, Nordez S, Brotas V, Paula J, 2009. Distribution and vertical dynamics of planktonic communities at Sofala Bank, Mozambique. Estuar. Coast. Shelf S. 84:605-616. DOI: https://doi.org/10.1016/j.ecss.2009.07.028
Lindell T, Pierson D, Premazzi G, 1999. Manual for monitoring European lakes using remote sensing techniques. Joint Research Centre, ISPRA: 161 pp.
Liu X, Wang M, Shi W, 2009. A study of a Hurricane Katrina-induced phytoplankton bloom using satellite observations and model simulations. J. Geophys. Res.-Oceans 114:4934. DOI: https://doi.org/10.1029/2008JC004934
Matthews MW, 2017. Bio-optical modeling of phytoplankton chlorophyll-a, p. 157-188. In: D.R. Mishra, I. Ogashawara and A.A. Gitelson (eds.), Bio-optical modeling and remote sensing of inland waters. Amsterdam, Elsevier. DOI: https://doi.org/10.1016/B978-0-12-804644-9.00006-9
McCune B, 2011. Nonparametric multiplicative regression for habitat modeling. Oregon State University.
Mobley CD, 1999. Estimation of the remote-sensing reflectance from above-surface measurements. Appl. Opt. 38:7442-7455. DOI: https://doi.org/10.1364/AO.38.007442
Moore SK, Trainer VL, Mantua NJ, Parker MS, Laws EA, Backer LC, Fleming LE, 2008. Impacts of climate variability and future climate change on harmful algal blooms and human health. Environ. Health 7:1-12. DOI: https://doi.org/10.1186/1476-069X-7-S2-S4
Morrison JR, 2003. In situ determination of the quantum yield of phytoplankton chlorophyll a fluorescence: A simple algorithm, observations, and a model. Limnol. Oceanogr. 48:618-631. DOI: https://doi.org/10.4319/lo.2003.48.2.0618
Moss B, 2012. Cogs in the endless machine: lakes, climate change and nutrient cycles: a review. Sci. Total Environt. 434:130-142. DOI: https://doi.org/10.1016/j.scitotenv.2011.07.069
Naselli-Flores L, Barone R, 2012. Phytoplankton dynamics in permanent and temporary Mediterranean waters: is the game hard to play because of hydrological disturbance? Hydrobiologia 701:219:233. DOI: https://doi.org/10.1007/978-94-007-5790-5_12
Nõges P, Tuvikene L, 2012. Spatial and annual variability of environmental and phytoplankton indicators in Lake Võrtsjärv: implications for water quality monitoring. Est. J. Ecol. 61:227-246. DOI: https://doi.org/10.3176/eco.2012.4.01
Odermatt D, Pomati F, Pitarch J, Carpenter J, Kawka M, Schaepman M, Wüest A, 2012. MERIS observations of phytoplankton blooms in a stratified eutrophic lake. Remote Sens. Environ. 126:232-239. DOI: https://doi.org/10.1016/j.rse.2012.08.031
Organization for Economic Cooperation and Development (OECD), 1982. Eutrophication of waters. Monitoring, assessment and control. Final report, OECD cooperative programme on monitoring of inland waters (eutrophication control). Paris, OECD: 154 pp.
Oppelt N, Scheiber R, Wegmann M, Taubenböck H, Gege P, Berger M, 2015. Fundamentals of remote sensing for terrestrial applications: evolution, current state-of-art and future possibilities, p. 61-86. In: T.S. Thenkabail (ed.), Remotely sensed data characterization, classification, and accuracies. CRC Press.
Paidere J, Gruberts D, Škute A, Druvietis I, 2007. Impact of two different flood pulses on planktonic communities of the largest floodplain lakes of the Daugava River (Latvia). Hydrobiologia 592:303-314. DOI: https://doi.org/10.1007/s10750-007-0770-y
Palmer SC, Kutser T, Hunter PD, 2015. Remote sensing of inland waters: Challenges, progress and future directions. Remote Sens. Environ. 157:1-8. DOI: https://doi.org/10.1016/j.rse.2014.09.021
Pan Y, Qiu L, 2019. A submersible in-situ highly sensitive chlorophyll fluorescence detection system. IOP Conference Series: Materials Science and Engineering 677:022065. DOI: https://doi.org/10.1088/1757-899X/677/2/022065
Pearson RK, Neuvo Y, Astola J, Gabbouj M, 2016, Generalized hampel filters. EURASIP J. Adv. Sign. Process. 1:1-8. DOI: https://doi.org/10.1186/s13634-016-0383-6
Pinardi M, Bartoli M, Longhi D, Viaroli P, 2011. Net autotrophy in a fluvial lake: the relative role of phytoplankton and floating-leaved macrophytes. Aquat. Sci. 73:389-403. DOI: https://doi.org/10.1007/s00027-011-0186-7
Pinardi M, Fenocchi A, Giardino C, Sibilla S, Bartoli M, Bresciani M, 2015. Assessing potential algal blooms in a shallow fluvial lake by combining hydrodynamic modelling and remote-sensed images. Water 7:1921-1942. DOI: https://doi.org/10.3390/w7051921
Pinardi M, Bresciani M, Villa P, Cazzaniga I, Laini A, Tóth V, et al., 2018. Spatial and temporal dynamics of primary producers in shallow lakes as seen from space: Intra-annual observations from Sentinel-2A. Limnologica 72:32-43. DOI: https://doi.org/10.1016/j.limno.2018.08.002
Pinardi M, Soana E, Bresciani M, Villa P, Bartoli M, 2020. Upscaling nitrogen removal processes in fluvial wetlands and irrigation canals in a patchy agricultural watershed. Wetlands Ecol. Manage. 28:297-313. DOI: https://doi.org/10.1007/s11273-020-09714-3
Pinardi M, Villa P, Free G, Giardino C, Bresciani M, 2021. Evolution of native and alien macrophytes in a fluvial‐wetland system using long‐term satellite data. Wetlands 41:1-14. DOI: https://doi.org/10.1007/s13157-021-01395-9
Polat SEVİM, Akiz A, Olgunoglu MP, 2005. Daily variations of coastal phytoplankton assemblages in summer conditions of the northeastern Mediterranean (Bay of İskenderun). Pak. J. Botany 37:715.
Reynolds CS, 2006. The ecology of freshwater phytoplankton. Cambridge: Cambridge University Press: 551 pp.
Samuelsson P, 2010. Using regional climate models to quantify the impact of climate change on lakes, p. 15-32. In: G. George (ed.), The impact of climate change on European Lakes. Dordrecht, Springer. DOI: https://doi.org/10.1007/978-90-481-2945-4_2
Schaeffer BA, Schaeffer KG, Keith D, Lunetta RS, Conmy R, Gould RW, 2013. Barriers to adopting satellite remote sensing for water quality management. Int. J. Remote Sens. 34:7534-7544. DOI: https://doi.org/10.1080/01431161.2013.823524
Sharaf N, Fadel A, Bresciani M, Giardino C, Lemaire BJ, Slim K, et al., 2019. Lake surface temperature retrieval from Landsat-8 and retrospective analysis in Karaoun Reservoir, Lebanon. J. Appl. Remote Sens. 13:044505. DOI: https://doi.org/10.1117/1.JRS.13.044505
Smith V, 2003. Eutrophication of freshwater and coastal marine ecosystems a global problem. Environ. Sci. Pollut. Res.10:126–39. DOI: https://doi.org/10.1065/espr2002.12.142
Staehr PA, Sand‐Jensen KAJ, 2006. Seasonal changes in temperature and nutrient control of photosynthesis, respiration and growth of natural phytoplankton communities. Freshwater Biol. 51:249-262. DOI: https://doi.org/10.1111/j.1365-2427.2005.01490.x
Staehr PA, Sand-Jensen K, 2007. Temporal dynamics and regulation of lake metabolism. Limnol. Oceanogr. 52:108-120. DOI: https://doi.org/10.4319/lo.2007.52.1.0108
Steinman AD, Lamberti GA, Leavitt PR, 2006. Biomass and pigments of benthic algae, p. 357-379. In: FR Hauer and GE Lamberti (eds.), Methods in stream ecology. Burlington, Academic Press. DOI: https://doi.org/10.1016/B978-012332908-0.50024-3
Stendera S, Adrian R, Bonada N, Cañedo-Argüelles M, Hugueny B, Januschke K, et al., 2012. Drivers and stressors of freshwater biodiversity patterns across different ecosystems and scales: a review. Hydrobiologia 696:1-28. DOI: https://doi.org/10.1007/s10750-012-1183-0
Stewart WDP, May E, Tuckwell SB, 1976. Nitrogen and phosphorus from agricultural land and urbanization and their fate in shallow freshwater lochs, p. 276-305. In: W. Dermott and J.R. Gasser (eds.) Agriculture and water quality, Technical Bulletin 32. London, HMSO.
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. DOI: https://doi.org/10.3390/rs8080640
Topp SN, Pavelsky TM, Jensen D, Simard M, Ross MR, 2020. Research trends in the use of remote sensing for inland water quality science: Moving towards multidisciplinary applications. Water 12:169. DOI: https://doi.org/10.3390/w12010169
Tyler AN, Hunter PD, Spyrakos E, Groom S, Constantinescu AM, Kitchen J, 2016. Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters. Sci. Total Environ. 572:1307-1321. DOI: https://doi.org/10.1016/j.scitotenv.2016.01.020
Vargas-Lopez IA, Rivera-Monroy VH, Day JW, Whitbeck J, Maiti K, Madden CJ, Trasviña-Castro A, 2021. Assessing chlorophyll a spatiotemporal patterns combining in situ continuous fluorometry measurements and Landsat 8/OLI data across the Barataria Basin (Louisiana, USA). Water 13:512. DOI: https://doi.org/10.3390/w13040512
Vermote EFTD, Tanré D, Deuzé JL, Herman M, Morcrette JJ, Kotchenova SY, 2006. Second simulation of a satellite signal in the solar spectrum-vector (6SV). 6S User Guide Version 3.
Villa P, Pinardi M, Tóth VR, Hunter PD, Bolpagni R, 2017. Remote sensing of macrophyte morphological traits: implications for the management of shallow lakes. J. Limnol. 76:1629. DOI: https://doi.org/10.4081/jlimnol.2017.1629
Voulvoulis N, Arpon KD, Giakoumis T, 2017. The EU Water Framework Directive: From great expectations to problems with implementation. Sci. Total Environ. 575:358–366. DOI: https://doi.org/10.1016/j.scitotenv.2016.09.228
Wang M, Shi W, Tang J, 2011. Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements. Remote Sens. Environ. 115:841-854. DOI: https://doi.org/10.1016/j.rse.2010.11.012
Wantzen KM, Junk WJ, Rothhaupt KO, 2008. An extension of the floodpulse concept (FPC) for lakes, p. 151-170. In: K.M. Wantzen, K.O. Rothhaupt, M. Mörtl, M. Cantonati, L.G. Tóth and P. Fischer (eds.), Ecological effects of water-level fluctuations in lakes. Dordrecht, Springer. DOI: https://doi.org/10.1007/978-1-4020-9192-6_15
Weyhenmeyer GA, Willén E, Sonesten L, 2004. Effects of an extreme precipitation event on water chemistry and phytoplankton in the Swedish Lake Mälaren. Boreal Environ. Res. 9:409-420.
Woods T, Kaz A, Giam X, 2021. Phenology in freshwaters: a review and recommendations for future research. Ecography. Online ahead of Print. DOI: https://doi.org/10.1111/ecog.05564
Zhang M, Duan H, Shi X, Yu Y, Kong F, 2012. Contributions of meteorology to the phenology of cyanobacterial blooms: implications for future climate change. Water Res. 46:442-452. DOI: https://doi.org/10.1016/j.watres.2011.11.013
Marco Bartoli, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma

Marine Science and Technology Center of Klaipeda University, 92294 Klaipeda, Lithuania

How to Cite

Pinardi, Monica, Gary Free, Beatrice Lotto, Nicola Ghirardi, Marco Bartoli, and Mariano Bresciani. 2021. “Exploiting High Frequency Monitoring and Satellite Imagery for Assessing Chlorophyll-a Dynamics in a Shallow Eutrophic Lake”. Journal of Limnology 80 (3). https://doi.org/10.4081/jlimnol.2021.2033.

Similar Articles

<< < 1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.

List of Cited By :

Crossref logo