Abstract
Generally, river plume waters can be distinguished from seawater by differences in salinity, temperature, turbidity, suspended matter and dissolved organics. Optically active water constituents interact with light, and their reflectance can be measured using Satellite Earth Observation (SEO) (Lombardi et al., 2022).
When getting close to coastal zones, the effects of anthropogenic and natural activities on the sea require a finer observation scale than ready-to-use SEO-derived products. To get mapping products time series at high spatial resolution from SEO, local calibration of retrieval algorithms with in situ data is required to accurately estimate concentrations of near-surface parameters, although the collection of dedicated in-situ data is not easily available.
In this study, we calibrated regional algorithms based on Copernicus Sentinel-2 MultiSpectral Instrument (MSI) data with the value domain typical of the coastal area of central Adriatic Sea to build accurate estimates of turbidity and chlorophyll-a parameters.
The algorithm 'C2RCC' (C2X-Nets) (Brockmann et al., 2016) available in the Water Color Data Analysis System (WC-DAS) (Filipponi et al., 2021) was regionally (Abruzzo coast) calibrated with ad hoc collected data during 12 boat campaigns (years 2019-2020), in 20 sampling points distributed between Pescara river mouth and a mussel farm. We estimated and analysed mapping products time series at 10 m spatial resolution, related to turbidity (in FNU) and chlorophyll-a concentration (in mg/m3), from all available Sentinel-2 MSI satellite acquisitions in the period 01 July 2016 - 31 December 2021 (total of 589 observations).
On average, in situ data turbidity decreases and salinity increases when moving away from the coast. This general trend, expected when the softer and colder waters of the river mix with the saltier and warmer marine waters, is well captured by SEO imagery: turbidity values in the coastal waters (0-3 nautical miles NM) of Abruzzo region has mean value 4.48 FNU ± 1.58 standard deviation.
Chlorophyll-a mean value is 0.20 ± 0.04 standard deviation in 0-3 NM coastal waters of Abruzzo region, indicating oligotrophic waters.
There are many potential benefits of using SEO to support sea and public health as well as economic activities. For aquaculture purposes, SEO data provides (i) mapping of parameters at high spatio-temporal resolution to (ii) more accurately monitor environmental and sanitary conditions. Spatial analysis of SEO data helps in (iii) assessing the most suitable areas for aquaculture farming and can underlie Marine Spatial Planning. Furthermore, in combination with weather forecast, SEO data facilitates (iv) modelling in active forecasting systems and alert to timely intervene to safe production and mollusc quality.
References
Lombardi, A., Manzi, M. P., Giacinto, F. D., Colaiuda, V., Tomassetti, B., Papa, M., Ippoliti, C., Giansante, C., Ferri, N. & Marzano, F. S. (2022) Coastal Water Quality: Hydrometeorological Impact of River Overflow and High-resolution Mapping from Sentinel-2 Satellite. In: Tsuzuki, M. S. G., Rahman, R. O. A., editors. Engineering Problems - Uncertainties, Constraints and Optimization Techniques . London: IntechOpen; 2022. (https://www.intechopen.com/online-first/82160 doi: 10.5772/intechopen.104524)
Brockmann, C., Doerffer, R., Peters, M., Kerstin, S., Embacher, S. & Ruescas, A. (2016) Evolution of the C2RCC neural network for Sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters. In Proc. Living Planet Symposium (ed. Ouwehand, L.), ESA-SP, Vol. 740.
Filipponi, F., Ippoliti, C., Tora S., Giansante, C., Scamosci, E., Petrini, M., Di Deo, N. & Conte A. (2021) Water color data analysis system for coastal zone monitoring. In: Proceeding of X International Conference AIT “Planet Care from Space”, Trends in Earth Observation, 2 vol. September 2021. DOI: 10.978.88944687/00