Abstract
High-frequency sensor measurements provide new opportunities to better understand and manage water resources. Recent advances in sensor and information technologies have enabled autonomous measurement and analysis of the aquatic environment at ever-increasing spatial and temporal resolution. Here, we describe the fundamentals of automated high-frequency lake monitoring, including hardware and telemetry design, sensor types and measurement principles, maintenance requirements, and quality assurance/quality control of datasets. These aspects require careful consideration to collect data that are suitably robust for monitoring and research needs. Examples are provided of the value of high-frequency measurements and derived data products for analysing short- and long-term lake processes. When applied with rigor, automated sensor measurements can improve programmes of management, monitoring, and research by providing baseline data, enabling rapid response to disturbance events, reducing some long-term costs, and opening new windows of opportunity to better understand the present era of declining water quality and environmental change.
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References
Bastien C, Cardin R, Veilleux É, Deblois C, Warren A, Laurion I (2011) Performance evaluation of phycocyanin probes for the monitoring of cyanobacteria. J Environ Monit 13:110–118
Burger DF, Hamilton DP, Pilditch CA, Gibbs MM (2007) Benthic nutrient fluxes in a eutrophic, polymictic lake. Hydrobiologia 584:13–25
Earp A, Hanson CE, Ralph PJ et al (2011) Review of fluorescent standards for calibration of in situ fluorometers: recommendations applied in coastal and ocean observing programs. Opt Express 19:26768–26782
Gregor J, Maršálek B (2005) A simple in vivo fluorescence method for the selective detection and quantification of freshwater cyanobacteria and eukaryotic algae. Acta Hydrochim Hydrobiol 33:142–148
Hodges C (2016) A validation study of phycocyanin sensors for monitoring cyanobacteria in cultures and field samples. Unpublished M.Sc. Thesis. The University of Waikato, Hamilton, New Zealand
Lee TY, Tsuzuki M, Takeuchi T, Yokoyama K, Karube I (1995) Quantitative determination of cyanobacteria in mixed phytoplankton assemblages by an in vivo fluorimetric method. Anal Chim Acta 302:81–87
Marcé R, George G, Buscarinu P, Deidda M, Dunalska J, de Eyto E, Flaim G, Grossart HP, Istvanovics V, Lenhardt M, Moreno-Ostos E, Obrador B, Ostrovsky I, Pierson DC, Potužák J, Poikane S, Rinke K, RodrÃguez-Mozaz S, Staehr PA, Å umberová K, Waajen G, Weyhenmeyer GA, Weathers KC, Zion M, Ibelings BW, Jennings E (2016) Automatic high frequency monitoring for improved lake and reservoir management. Environ Sci Technol 50:10780–10794
Meinson P, Idrizaj A, Nõges P, Nõges T, Laas A (2015) Continuous and high-frequency measurements in limnology: history, applications, and future challenges. Environ Rev 24:52–62
Read JS, Hamilton DP, Jones ID, Muraoka K, Winslow LA, Kroiss R, Wu CH, Gaiser E (2011) Derivation of lake mixing and stratification indices from high-resolution lake buoy data. Environ Model Softw 26:1325–1336
Taiz L, Zeiger E (2010) Plant physiology, 5th edn. Sinauer Associates, Sunderland, MA
Taylor JR, Loescher HL (2013) Automated quality control methods for sensor data: a novel observatory approach. Biogeosciences 10:4957–4971
Weathers K, Hanson PC, Arzberger P, Brentrup J, Brookes J, Carey CC, Istvanovics V (2013) The Global Lake Ecological Observatory Network (GLEON): the evolution of grassroots network science. Limnol Oceanogr Bull 22:71–73
Winslow LA, Zwart JA, Batt RD, Dugan HA, Woolway RI, Corman JR, Hanson PC, Read JS (2016) LakeMetabolizer: an R package for estimating lake metabolism from free-water oxygen using diverse statistical models. Inland Waters 6:622–636
Woolway RI, Jones ID, Hamilton DP, Maberly SC, Muraoka K, Read JS, Smyth RL, Winslow LA (2015) Automated calculation of surface energy fluxes with high-frequency lake buoy data. Environ Model Softw 70:191–198
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McBride, C.G., Rose, K.C. (2018). Automated High-frequency Monitoring and Research. In: Hamilton, D., Collier, K., Quinn, J., Howard-Williams, C. (eds) Lake Restoration Handbook. Springer, Cham. https://doi.org/10.1007/978-3-319-93043-5_13
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DOI: https://doi.org/10.1007/978-3-319-93043-5_13
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