TY - JOUR

T1 - Assessing ESA Climate Change Initiative data for the monitoring of phytoplankton abundance and phenology in deep lakes: Investigation on Lake Geneva

AU - Bonnier, Mona

AU - Anneville, Orlane

AU - Iestyn Woolway, R.

AU - Thackeray, Stephen J.

AU - Morin, Guillaume P.

AU - Reynaud, Nathalie

AU - Soulignac, Frédéric

AU - Tormos, Thierry

AU - Harmel, Tristan

PY - 2024/8/1

Y1 - 2024/8/1

N2 - Lake water quality assessment requires quantification of phytoplankton abundance. Optical satellite imagery allows us to map this information within the entire lake area. The ESA Climate Change Initiative (ESA-CCI) estimates Chl-a concentrations, based on medium resolution satellite data, on a global scale. Chl-a concentrations provided by the ESA-CCI consortium were analyzed to assess their representativeness for water quality monitoring and subsequent phenology studies in Lake Geneva. Based on vertically resolved in-situ data, those datasets were evaluated through match-up comparisons. Because the underlying algorithms do not take into account the vertical distribution of phytoplankton, a specific analysis was performed to evaluate any potential biases in remote sensing estimation, and consequences for observed phenological trends. Different approaches to data averaging were performed to reconstruct Chl-a estimates provided by the remote sensing algorithms. Strong correlation (R-value > 0.89) and acceptable discrepancies (rmse ∼ 1.4 mg.m−3) were observed for the ESA-CCI data. This approach permitted recalibration of the ESA CCI data for Lake Geneva. Finally, merging satellite and in-situ data provided a consistent time series for long term analysis of phytoplankton phenology and its interannual variability since 2002. This combination of in-situ and satellite data improved the temporal resolution of the time series, enabling a more accurate identification of the timing of specific spring events characterising phytoplankton phenology.

AB - Lake water quality assessment requires quantification of phytoplankton abundance. Optical satellite imagery allows us to map this information within the entire lake area. The ESA Climate Change Initiative (ESA-CCI) estimates Chl-a concentrations, based on medium resolution satellite data, on a global scale. Chl-a concentrations provided by the ESA-CCI consortium were analyzed to assess their representativeness for water quality monitoring and subsequent phenology studies in Lake Geneva. Based on vertically resolved in-situ data, those datasets were evaluated through match-up comparisons. Because the underlying algorithms do not take into account the vertical distribution of phytoplankton, a specific analysis was performed to evaluate any potential biases in remote sensing estimation, and consequences for observed phenological trends. Different approaches to data averaging were performed to reconstruct Chl-a estimates provided by the remote sensing algorithms. Strong correlation (R-value > 0.89) and acceptable discrepancies (rmse ∼ 1.4 mg.m−3) were observed for the ESA-CCI data. This approach permitted recalibration of the ESA CCI data for Lake Geneva. Finally, merging satellite and in-situ data provided a consistent time series for long term analysis of phytoplankton phenology and its interannual variability since 2002. This combination of in-situ and satellite data improved the temporal resolution of the time series, enabling a more accurate identification of the timing of specific spring events characterising phytoplankton phenology.

KW - Water quality

KW - Earth observation

KW - Peri-alpine Lake

KW - Long-term trends

KW - Remote sensing

KW - Chlorophyll

U2 - 10.1016/j.jglr.2024.102372

DO - 10.1016/j.jglr.2024.102372

M3 - Article

VL - 50

JO - Journal of Great Lakes Research

JF - Journal of Great Lakes Research

SN - 0380-1330

IS - 4

M1 - 102372

ER -