Abstract. The standard quasi-analytical algorithm (Lee et al., 2002) was tuned as QAA-V
using a suite of synthetic data and in situ measurements to improve its
performance in optically complex and shallow estuarine waters. Two
modifications were applied to the standard QAA: (1) the semi-analytical
relationship for obtaining remote sensing reflectance just below the
water surface as a function of absorption and backscattering coefficients was
updated using Hydrolight® simulations, and
(2) an empirical model of the total non-water absorption coefficient was
proposed using a ratio of green to red bands of an ocean color sensor, which
is known to work well in various inland and estuarine environments. The QAA-V-derived total absorption and backscattering coefficients, which were
evaluated in a variety of waters ranging from highly absorbing and turbid
to relatively clear shelf waters, showed satisfactory performance on
a Hydrolight-simulated synthetic dataset
(R2 > 0.87, MRE < 17 %), an in situ estuarine and nearshore
dataset (R2 > 0.70, MRE < 35 %), and the NOMAD
(R2 > 0.90, MRE < 30 %). When compared to the
standard QAA (QAA-v6), the QAA-V showed an obvious improvement with
∼ 30–40 % reduction in absolute mean relative error for
the Hydrolight-simulated synthetic and in situ
estuarine and nearshore datasets, respectively. The methodology of tuning
QAA was applied to the VIIRS ocean color sensor and validation results
suggest that the proposed methodology can also be applied to other ocean
color and land-observing sensors. The QAA-V was also assessed on VIIRS
imagery using a regional relationship between suspended particulate matter
(SPM) and particulate backscattering coefficient at 532 nm
(bbtnw532; R2 = 0.89, N = 33). As a case study,
the QAA-V processing chain and VIIRS imagery were used to generate a sequence
of SPM maps of Galveston Bay, Texas following the unprecedented flooding of
Houston and the surrounding regions due to Hurricane Harvey in August 2017. The
record discharge of floodwaters through two major rivers into the bay
resulted in very high SPM concentrations over several days throughout the
bay, with wind forcing additionally influencing its distribution into the
coastal waters of the northern Gulf of Mexico. The promising results of this
study suggest that the application of QAA-V to various ocean color and
land-observing satellite imagery could be used to assess the bio-optical
state and water quality dynamics in a variety of coastal systems around the
world.
Adjustment of ocean color sensor calibration through multi-band statistics
