Abstract
Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.
Highlights
The flow of the water, starting with rainfall and headwater streams, carries particulate and dissolved materials from land to ocean, driving the transport and cycling of a vast suite of biogeochemical components
We considered ap as representative of non-algal particles (NAP) because aphy contribution was very low for the Amazon and relatively low for CW rivers (
The Amazon River’s aCDOM (443) values (2.12 ± 0.53 m−1 ; see Table 2) are in the same range of values presented by Martinez et al [13] (aCDOM (440) = 3.3 ± 1.0 m−1 ), and relatively lower when compared to values presented by Jorge et al [67]
Summary
The flow of the water, starting with rainfall and headwater streams, carries particulate and dissolved materials from land to ocean, driving the transport and cycling of a vast suite of biogeochemical components. The physical-biogeochemical properties of the water carried by rivers are in constant change while traveling downstream to the coastal ocean due to interactions among the landscape, wetlands, weather and climate forcing, and in situ processes [1,2,3]. In situ sampling captures the properties at a specific point location and time. It represents a considerable challenge for an effective and representative monitoring at regional scales, considering the large distance between sampling stations and the usually inconstant nature of field sampling, in remote regions [4,5]. The intrinsic transience of river properties is more evident when using remotely sensed satellite observations, which have the advantage of capturing the dynamic and heterogenous nature of surface waters [6]. In situ sampling obviously remains crucial since it is a required step for validation and robust analysis of remote sensing observations
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