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Paper title Deriving DOC concentrations in tropical black waters from remote sensing data - the case study of Petit-Saut reservoir.
Authors
  1. Arthur Coqué INRAE Speaker
  2. Guillaume Morin INRAE - PACA
  3. Thierry Tormos
  4. Jean Michel Martinez CNRS
  5. Étienne Dambrine Pôle R&D « ECLA », Aix-en-Provence, France; INRAE, USMB, CARRTEL, Le Bourget du Lac, France
Form of presentation Poster
Topics
  • A7. Hydrology and Water Cycle
    • A7.06 EO for monitoring water quality and ecological status in inland waters
Abstract text Freshwaters play a significant role in the global carbon cycle by degassing large carbon fluxes. It is established that most of this carbon emitted to the atmosphere comes from organic matter degradation during transport and storage in rivers and lakes. This is particularly true for freshwaters in tropical context such as Petit-Saut reservoir (365 km²) in French Guiana, with huge inputs of terrestrial organic matter (litter and drowned forest), high temperatures and humidity (both being aggravating factors of the degradation).
Knowledge about spatial distribution and temporal evolution of dissolved (and particulate) organic carbon (resp. DOC and POC) in this reservoir and its tributaries is fundamental for a better understanding of degassing mechanisms and estimation of GHG emissions. Hence, we tested the potentialities of high spatial resolution multispectral satellite imagery (Sentinel-2 and Landsat 8) for monitoring DOC concentrations in these absorbing tropical waters, using the absorption coefficient of the coloured dissolved organic matter (aCDOM) as a proxy.
Optical properties (aCDOM and above water remote sensing reflectance (Rrs)) as well as water quality measurements (DOC, POC, total suspended matter, chlorophyll-a, etc) were carried out at 25 stations evenly distributed over the entire lake. CDOM absorption was the highest at the mouth of the main tributary (Sinnamary river) and the lowest in the pelagic area, near the dam.
Simulated satellite spectra were computed by convoluting in situ hyperspectral data with the spectral response function of the given satellite sensor (Sentinel-2/MSI or Landsat 8/OLI), and have been compared to atmospherically corrected satellite data. We used several atmospheric correction algorithms (ACOLITE, C2RCC, C2X, C2X-COMPLEX, GRS, iCOR, LaSRC, Sen2Cor) and resulted spectra were highly heterogeneous (depending on the method used), and poorly correlated with in situ spectra. We explain these limited performances by environmental factors, such as the presence of absorbing aerosols (e.g., N2O) or strong adjacency effects (IOCCG, 2018) that are sill hardly resolved by atmospheric correction methods. According to the ACIX-AQUA exercise (Pahlevan et al., 2021), it is indeed not uncommon that atmospheric correction processors failed to retrieve realistic water reflectance in very absorbing waters surrounded by dense vegetation – typically the case of Petit-Saut reservoir, located within the Amazon rainforest.
We tested several semi-empirical and semi-analytical algorithms from the literature to estimate aCDOM at 440 nm ( aCDOM(440) ) from multispectral data. We also designed an empirical algorithm based on Sentinel-2 bands B3 to B5, performances of atmospheric correction processors being reasonable on this part of the spectrum. Even though the retrieval of aCDOM in the absorbing black waters of Petit-Saut remains challenging, most of these recalibrated algorithms seem to be robust enough to variable concentrations of total suspended matter, and provide satisfactory results over the entire range of aCDOM observed during our campaign.
In order to retrieve DOC concentration from remote sensing data, a linear relationship between aCDOM(440) and DOC has been defined and suggest that aCDOM(440) can be used as an efficient tracer to estimate DOC in most of Petit-Saut waters. However, points located in main tributaries or their transition zones do not follow the same relationship, which is known to be water body or river specific (Valerio et al., 2018).
To summarise, we were able to estimate DOC in these tropical black waters from simulated satellite spectra, but there are still several challenging issues to overcome before being able to do it from space – atmospheric correction being the first order source of uncertainty associated with aCDOM estimation in such highly absorbing environments. New measurement campaigns will be conducted i) to enrich our dataset and precise the optical properties of tributaries and transition zones, ii) to study possible seasonal or inter-annual variation of the aCDOM(440)–DOC relationship (Del Castillo, 2005) and iii) to better constrain atmospheric corrections by having in situ AOT measurements.
When the above-mentioned limitations will be overcome, our next objective will be to produce time series of DOC concentrations from Sentinel-2 and Landsat 8 archives. It will help to characterize the spatial and temporal distribution of organic carbon in the area, which is useful to better comprehend organic matter degradation processes and dynamics. Ultimately, this will benefit both public authorities and Électricité de France (the dam manager) in their management of the dam and its reservoir.


References

Del Castillo, C.E., 2005. Remote Sensing of Organic Matter in Coastal Waters, in: Miller, R.L., Del Castillo, C.E., Mckee, B.A. (Eds.), Remote Sensing of Coastal Aquatic Environments: Technologies, Techniques and Applications, Remote Sensing and Digital Image Processing. Springer Netherlands, Dordrecht, pp. 157–180. https://doi.org/10.1007/978-1-4020-3100-7_7

IOCCG (2018). Earth Observations in Support of Global Water Quality Monitoring. Greb, S., Dekker, A. and Binding, C. (eds.), IOCCG Report Series, No. 17, International Ocean Colour Coordinating Group, Dartmouth, Canada.

Pahlevan, N., Mangin, A., Balasubramanian, S.V., Smith, B., Alikas, K., Arai, K., Barbosa, C., Bélanger, S., Binding, C., Bresciani, M., Giardino, C., Gurlin, D., Fan, Y., Harmel, T., Hunter, P., Ishikaza, J., Kratzer, S., Lehmann, M.K., Ligi, M., Ma, R., Martin-Lauzer, F.-R., Olmanson, L., Oppelt, N., Pan, Y., Peters, S., Reynaud, N., Sander de Carvalho, L.A., Simis, S., Spyrakos, E., Steinmetz, F., Stelzer, K., Sterckx, S., Tormos, T., Tyler, A., Vanhellemont, Q., Warren, M., 2021. ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters. Remote Sensing of Environment 258, 112366. https://doi.org/10.1016/j.rse.2021.112366

Valerio, A. de M., Kampel, M., Vantrepotte, V., Ward, N.D., Sawakuchi, H.O., Less, D.F.D.S., Neu, V., Cunha, A., Richey, J., 2018. Using CDOM optical properties for estimating DOC concentrations and pCO 2 in the Lower Amazon River. Optics Express 26, A657. https://doi.org/10/gd8zmb