On the absorption of light in the Orinoco River plume
Ana Lucia Odriozola1, Ramon Varela2, Chuanmin Hu1, Yrene Astor2, Laura
Lorenzoni1, Frank E. Müller-Karger1
1Institute
for Marine Remote Sensing (IMaRS), College of Marine Science,
University of South Florida, 140 7th Ave. South, St Petersburg, FL 33701
2Fundacion
La Salle de Ciencias Naturales, Estación de Investigaciones Marinas de
Margarita, Apartado 144 Porlamar, Isla de Margarita, Venezuela
Corresponding author:
Ana Lucia Odriozola
Institute for Marine Remote Sensing/IMaRS, College of Marine Science, University
of South Florida, 140 7th Ave. South, St Petersburg, FL 33701
727-553-1186 (Office), 727-553-1103 (FAX), luchi@marine.usf.edu
i
On the absorption of light in the Orinoco River plume
________________________________________________________________________
Abstract. The spectral absorption coefficients of particles (phytoplankton and detritus)
and colored dissolved organic matter (CDOM) were measured in the Orinoco River
plume in the Gulf of Paria (GOP) and southeastern Caribbean Sea (SEC) in the wet (June,
October) and dry (February) seasons of 1998, 1999, and 2000. During both seasons and
over the three years, there was substantial patchiness in water color off the Orinoco Delta,
and CDOM accounted for 61-98% of the total light absorption coefficient at 440 nm in
the GOP and SEC at most stations ( x  89  7.6%; N=44). Detritus dominated
absorption due to particles ( x  70  20%; N= 27) near the Orinoco Delta, while
phytoplankton dominated particle absorption in the northern GOP and in the SEC ( x 
6517%; N=42). Absorption coefficients of CDOM, phytoplankton, and detritus at 440
nm ranged 0.23 m-1 to 2.59 m-1, 0.016 m-1 to 0.55 m-1, and 0.002 m-1 to 0.545 m-1 during
the dry seasons, and 0.38 m-1 to 3.21 m-1, 0.013 m-1 to 0.113 m-1, and 0.003 m-1 to 0.754
m-1 during the wet seasons, respectively. The ratio of CDOM to phytoplankton absorption
in the Orinoco plume [aCDOM(440)/aph(440)] ranged from 3.3 to 139 ( x  30  24;
N=44), which are extremely high compared to other coastal regions. These values are
explained by the unique characteristics of the Orinoco River (e.g. low phytoplankton
biomass and high discharge of sediments and CDOM which inhibit phytoplankton
growth). Our results demonstrate that it is fundamentally difficult to estimate
phytoplankton absorption or chlorophyll-a concentrations from space using wavelengths
in the blue portion of the light spectrum in coastal and estuarine waters affected by large
rivers like the Orinoco. New chlorophyll algorithm development efforts need to focus on
the red wavelengths (e.g. fluorescence peak) where CDOM influence is minimal.
________________________________________________________________________
Keywords: Light absorption, CDOM, Gelbstoff, chlorophyll-a, ocean-color, river plume,
phytoplankton, South Eastern Caribbean, Venezuela, Orinoco River, Gulf of Paria
ii
1
1. Introduction
2
The color of natural waters is determined by the preferential absorption and
3
scattering at specific wavelengths by water molecules and suspended and dissolved
4
substances. The total absorption coefficient at a certain wavelength (at()) is defined as
5
the sum of the absorption by water molecules (aw()), phytoplankton (aph()), detritus
6
(ad()), and colored dissolved organic matter (CDOM; aCDOM()). Changes in the
7
concentration of these substances thus affect the color of the water.
8
Studies of the sea spectral reflectance (SSR, i.e., ocean color) over the past few
9
decades have developed methods to assess the biomass of marine phytoplankton using
10
remote sensing techniques (Carder et al., 1999; O’Reilly et al., 2000). These studies are
11
increasingly focused on the need to understand the role of phytoplankton and dissolved
12
organic matter (DOM) in the carbon budget (Muller-Karger et al., 2005a; Siegel et al.,
13
2005; Hu et al., 2006), the spatial and temporal variability of productivity over large and
14
regional scales (Behrenfeld et al., 2001), and the quality of coastal waters (Hu et al.,
15
2004a; Muller-Karger et al., 2005b). Regional and global chlorophyll and primary
16
production estimates are affected by river plumes, as is the interpretation of other
17
regional processes when using remotely sensed data from SSR satellites. However, we
18
still know very little about the optical characteristics of river plumes. Indeed, large rivers
19
such as the Amazon and Orinoco affect the color of the open ocean hundreds to
20
thousands of kilometers from the river delta (Muller-Karger et al., 1988, 1989; Hu et al.,
21
2004b; Del Vecchio and Subramaniam, 2004).
22
23
Coastal waters are optically complex (Sathyendranath, 2000), where, in contrast
to Case 1 waters (Morel et al., 1977), phytoplankton pigments do not dominate the color
1
1
of water. Rather, other particulate and dissolved substances mask or dominate the bio-
2
optical signal of phytoplankton pigments (Case 2 waters). Among these substances are
3
CDOM, detritus, and suspended sediments. CDOM consists of yellow-brown colored
4
organic compounds such as humic and fulvic acids, which originate from local (e.g. local
5
phytoplankton degradation) or land sources. CDOM absorbs strongly in the ultraviolet
6
and has an absorption spectrum that decreases exponentially with increasing wavelength
7
(Bricaud et al., 1981). High CDOM concentrations therefore decrease the amount and
8
quality of radiation available for phytoplankton photosynthesis. CDOM absorption is
9
commonly used as a proxy for CDOM concentrations.
10
The dispersal of the Orinoco River plume over the Southeastern Caribbean (SEC)
11
has been documented previously using SSR satellite images (Müller-Karger et al., 1989;
12
Hochman et al., 1994; Del Castillo et al., 1999; Hu et al., 2004b). However, the
13
interpretation of the optical signature (color) detected by satellite sensors over the
14
Orinoco River plume has been a challenge. Hochman et al. (1994) tried to deconvolve the
15
signatures of CDOM and phytoplankton pigments on CZCS images from the Orinoco
16
River plume, concluding that as much as 50% of the chlorophyll derived from the CZCS
17
images within the plume was an artifact due to the presence of CDOM. Blough et al.
18
(1993) and Del Castillo et al. (1999) studied the absorption properties of the Orinoco
19
plume, including the Gulf of Paria (GOP) and SEC. Both studies described the absorption
20
properties of CDOM but did not evaluate its contribution to total absorption relative to
21
that of particles.
2
1
In this study we examine the relative importance of phytoplankton, detritus, and
2
CDOM in defining the color of the Orinoco River plume. We collected in situ
3
observations to address:
4
5
6
7
1. Seasonal and spatial patterns of particle and CDOM absorption in the GOP
and SEC;
2. Spectral characteristics of aph(), ad(), aCDOM(), and of the chlorophyllspecific absorption of phytoplankton (aph*());
8
3. Contributions of aph(), ad(), and aCDOM() to at().
9
The results of this study provide information that is necessary to develop future
10
SSR algorithms for the estimation of chlorophyll and other constituents.
11
12
13
2. Study Region
The Orinoco River originates in the southern part of Venezuela (Figure1), and
14
discharges waters from about 31 major and 2,000 minor tributaries into the western
15
tropical Atlantic. These waters are transported into the southeastern Caribbean Sea
16
largely through the Gulf of Paria, but during the rainy season a larger but unquantified
17
fraction of the plume also flows east around Trinidad and Tobago into the Caribbean. The
18
Orinoco is considered to be the third largest river in the world in terms of volumetric
19
discharge (after the Amazon and the Congo), discharging an average of ~ 3.6 x104 m3 s-1
20
(Meade et al., 1983; Lewis, 1988; Muller-Karger et al., 1989; Bonilla et al., 1993;
21
Vörösmarty et al., 1998). Figure 2 shows the Orinoco River hydrograph based on data
22
collected from 1923 to 1989. Low discharge occurs during the dry season (January –
23
May) and high discharge during the rainy season (July – October) as a result of the
3
1
meridional migration of the Intertropical Convergence Zone (ITCZ). Maximum discharge
2
occurs around August, with a mean of 7x104 m3 s-1. Minimum flow occurs around March
3
with a mean of 1x104 m3 s-1.
4
The Orinoco receives waters containing high amounts of dissolved matter and
5
suspended solids from the Andes Mountains and Venezuelan plains (the "Llanos"). It also
6
receives waters containing low concentrations of suspended solids (Monente and
7
Colonnello, 1997) but high concentrations of CDOM (Lewis and Saunders, 1990) coming
8
from the Guayana Shield (locally referred to as “black waters”). The Caroní River is a
9
major contributor of such black waters. Waters derived from upstream of the Caroní are
10
locally referred to as "white" because of their milky color. The Orinoco is one of few
11
large rivers for which the hydrologic regime has not been severely impacted by human
12
activities (Lewis, 1988).
13
The Gulf of Paria (GOP) is a semi-enclosed basin adjacent to the northern half of
14
the Orinoco Delta (Figure 1). The exchange of water and sediment with the Atlantic
15
Ocean and the Caribbean Sea are controlled by two narrow channels to the Gulf, one
16
located to the south (Serpent’s Mouth) and one to the north (Dragon’s Mouth).
17
Immediately to the west of the Dragon's Mouth, along the northern coast of the Paria
18
Peninsula, strong coastal upwelling occurs year-round, but is more pronounced during the
19
dry season when Trade Winds are stronger.
20
The GOP receives and retains a significant portion of the sediments discharged
21
from the Orinoco's Mánamo and Boca Grande channels (Warne et al., 2002). Waters and
22
sediments discharged through Boca Grande may mix with waters and sediments from the
4
1
Amazon River before entering the Gulf (van Andel and Postma, 1954; Milliman et al.,
2
1982).
3
4
3. Methods and data
5
3.1 Sample collection:
6
Samples were collected during 6 research cruises (Table 1) to the GOP and SEC
7
onboard of the R/V Hno. Ginés (Fundación La Salle de Ciencias Naturales, Venezuela)
8
between 1998 and 2000. These cruises were part of NASA's SIMBIOS (Sensor
9
Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies)
10
program. A total of 85 stations were sampled within the Orinoco River Plume (ORP)
11
during the study (Figure 3). Table 2 shows the location and sampling date for each
12
station. Near-surface water samples were collected at each station at 1 m depth using a
13
rosette ensemble outfitted with 8 L Niskin bottles. Vertical profiles of temperature and
14
salinity were performed at each station using a Seabird CTD sensor. Water samples for
15
pigment analyses were filtered through GF/F filters. Pigments were extracted using hot
16
methanol (99.8%) and measured fluorometrically (Holm-Hansen et al., 1965) using a
17
Turner Designs Fluorometer model 10-AV at the Estación de Investigaciones Marinas de
18
Margarita (EDIMAR) of Fundación La Salle in Margarita Island, Venezuela.
19
20
3.2 Absorption measurements:
21
Water samples for particle absorption (ap) observations were filtered using 25 mm
22
Whatman GF/F filters. Enough water was filtered to exceed an optical density of 0.04 at
23
675 nm (Bissett et al., 1997). The volumes filtered ranged from 0.05 to 2.0 L. Absorption
5
1
coefficients were measured following the filter pad method described by Kishino et al.
2
(1985), as modified by Bricaud and Stramski (1990). A PHOTORESEARCH PR-650
3
spectroradiometer (Spectrascan) with a 4 nm spectral resolution and a band range of 380
4
nm to 780 nm was used to measure the optical density of the filters. After the first
5
measurement, phytoplankton pigments were extracted by soaking the filters with hot
6
methanol (99.8%), and the optical density of the filters was measured again for
7
absorbance due to de-pigmented particles (detritus). Particle and detritus absorption
8
coefficients (ap and ad, respectively) were then obtained (Mitchell and Kiefer, 1988, as
9
modified by Bricaud and Stramski, 1990). The absorption coefficient of phytoplankton
10
11
(aph), was calculated by difference between ap(λ) and ad(λ).
Estimates of aCDOM(λ) were obtained by filtering samples into acid-washed glass
12
bottles using silicon tubing connected directly to the Niskin bottles and attached pre-
13
combusted stainless-steel filter holders with pre-combusted glass-fiber filters (Whatman
14
GF/F 0.7 µm pore size). The absorbance of the filtrate was measured using an Ocean
15
Optics spectrophotometer equipped with 10 cm long cuvettes, with a spectral resolution
16
of 0.23 nm and a spectral range of 185 nm to 475 nm.
17
18
The absorption coefficient (a) was obtained from the absorbance (D) by:
a = ln(10)  D/r
(Hu et al., 2002)
(1)
19
where r is the path length (0.1 m).
20
An exponential function was used to fit CDOM absorption spectra (Bricaud et al.,
21
1981), and a nonlinear least squares fitting routine was used to calculate the absorption
22
spectral slope between 270 nm and 450 nm:
23
aCDOM() = aCDOM() e-S( - o) + offset
(2)
6
1
where  is a reference wavelength and S (nm-1) is the spectral slope. The offset accounts
2
for residual scattering effects and is discarded after the fitting.
3
4
3.3 Surface and subsurface radiometric reflectance measurements
5
Radiometric measurements of spectral downwelling irradiance Ed(z,λ), upwelling
6
irradiance Eu(z,λ), and upwelling radiance Lu(z,λ) were collected underwater using a
7
PRR-600 radiometer from BIOSPHERICAL INSTRUMENTS. Above water
8
measurements of Ed(λ, 0+), total surface upwelling radiance Lt(λ), and downwelling sky
9
radiance Lsky(λ), were collected using a PR-650 (spectrascan) from PHOTORESEARCH.
10
The data was processed using IDL (Research Systems Inc.) software routines created at
11
the Institute for Marine Remote Sensing (IMaRS/USF). Measurements and processing of
12
the radiometric data were carried out following the Ocean Optics Protocols for Satellite
13
Ocean Color Sensor Validation (Muller, 2002).
14
15
16
17
18
The diffuse attenuation coefficient, Kd(λ), was derived from Ed(λ,z) using:
E d (, z)  E d (, 0 ) e  k d ( ) z
(3)
The depth (zmax) at which light is reduced to 1% of the subsurface (0-) irradiance
was estimated as:
z(max) = ln100/Kd(λ)
(Kirk, 1994)
(4)
19
20
21
22
Remote sensing reflectance, Rrs(λ), was derived as:
Rrs(λ) = Lw(λ )/Ed(λ, 0+)
= [Lt(λ ) - (Lsky(λ ) * 0.02)]/Ed(λ, 0+)
7
(5)
1
where Lw(λ) is the water leaving radiance, and 0.02 is the Fresnel reflectance. Lt(λ) was
2
measured above water with a nadir angle of ~ 30° and azimuth  ~ 90° from the solar
3
plane. Lsky(λ) was measured in the same plane at a zenith angle of ~30o.
4
5
3.4 Bio-optical Algorithms
6
The performance of various bio-optical algorithms was examined to evaluate the
7
effect of the absorption conditions that characterize this region. In situ chlorophyll-a
8
concentration observations were compared with chlorophyll-a estimates derived with
9
SeaWiFS satellite images and in situ Rrs() measurements. Both the ocean color (OC)
10
version four algorithm (OC4v4; O’Reilly et al., 2000) and the MODIS chlorophyll-a
11
semi-analytical algorithm (Carder et al., 1999) were tested. The in situ Rrs()
12
measurements allowed testing of the algorithm performance without considering the
13
implications of complex atmospheric correction required for satellite images of turbid
14
coastal waters (Hu et al., 2000).
15
16
4. Results and Discussion
17
4.1 CDOM absorption (aCDOM)
18
CDOM absorption spectra showed the expected exponential decrease with
19
increasing wavelengths (Figure 4). Most spectra featured a small shoulder near 265 nm.
20
This has been attributed to the presence of organic rings of purine and pyrimidine
21
(Yentsch and Reichert, 1962). The magnitude of aCDOM() is a proxy for the
22
concentration of CDOM. Minimum values were found in the SEC outside the river plume
23
during the dry season (SIM5), and maximum values occurred near the delta during the
8
1
wet season (SIM4). Within the body of the Orinoco River plume, a large number of
2
spectra were similar, indistinctively of season and place. As reported previously in the
3
GOP and in other coastal regions, CDOM generally presented a conservative behavior
4
with salinity (Figure 5), indicating that it is mainly of riverine origin (Vodacek et al.,
5
1997; Del Castillo et al., 1999; Keith et al., 2002; Hu et al., 2003). However, there was
6
some indication of non-conservative CDOM additions at salinities near 15-20 during the
7
wet season (Fig. 5a, > 3 m-1). Similar phenomena have been reported in Blough et al.
8
(1993) and Del Castillo (1999) at salinities below 30, which suggest local inputs by
9
phytoplankton and/or other non-point CDOM sources.
10
Values of S, the aCDOM spectral slope, during the wet season ranged from 0.013 to
11
0.018 nm-1 ( x = 0.014 nm-1; N=7) in the GOP and between 0.014-0.017 nm-1 ( x = 0.015
12
nm-1; N=20) in the SEC. During the dry season, S varied between 0.010-0.017 nm-1 ( x =
13
0.014 nm-1; N=6) in the GOP and 0.013-0.020 nm-1 ( x = 0.016 nm-1; N=12) in the SEC
14
(Table 2). Most S values fell within the range reported by Blough and Del Vecchio
15
(2002) for coastal waters influenced by river input (0.013-0.018 nm-1).
16
An increase in the range of S was observed at salinities above 30 (Figure 5
17
bottom) during SIM5 (March 2000), which suggested that different processes affected the
18
composition of CDOM as the plume mixed with Caribbean Sea waters. Variations in S
19
result from changes in the proportion of humic to fulvic acids (Carder et al., 1989), by
20
chemical modifications of CDOM such as bleaching due to exposure to sunlight (Del
21
Castillo et al., 1999), or by an increased abundance of locally generated CDOM (Blough
22
and Del Vecchio, 2002). Because surface turbidity during SIM5 was lower than during
23
any other cruises (Odriozola, 2004), it is reasonable to assume that photodegradation was
9
1
stronger (due to exposure to more sunlight) and therefore responsible for the changes in S
2
during this cruise. Blough et al. (1993) and Del Castillo et al. (1999) attributed the weak
3
relationship of S and salinities below 30 to the fact that there are no significant changes in
4
the optical properties of CDOM in the river plume closer to shore, indicating insignificant
5
changes of CDOM chemical composition.
6
Phytoplankton absorption due to chlorophyll-a peaks around 440 nm.
7
Measurements of the absorption of light by CDOM at this wavelength help understand
8
possible biases in bio-optical algorithms used to estimate chlorophyll-a. Values of
9
aCDOM(440) are presented in Table 2. During the dry season, aCDOM(440) ranged from
10
0.415 to 2.59 m-1 ( x = 1.64 m-1; N=6) in the GOP, and 0.231-1.672 m-1 ( x = 0.94 m-1;
11
N=12) in the SEC. During the wet season, aCDOM(440) values varied from 0.403 to 3.21
12
m-1 ( x = 1.58 m-1; N=7) in the GOP, and 0.455-1.543 m-1 ( x = 0.86 m-1; N=20) in the
13
SEC. Around 60% of aCDOM(440) values were between 0.5 and 1.5 m-1. Values of aCDOM
14
in the GOP and SEC have been previously reported at 300nm (Blough et al., 1993; Del
15
Castillo et al., 1999), and they fall within the range of values measured in this study
16
(Figure 4). In general, aCDOM(440) values observed in the Orinoco River plume during
17
this study (Table 2) were higher than those found in other coastal waters influenced by
18
river plumes, such as the West Florida shelf (aCDOM(440) = 0.72 m-1 and 0.17 m-1 for
19
salinities of 27.9 and 30.46, respectively; Del Castillo, 1998), the Northern Gulf of
20
Mexico (aCDOM(443) = 0.45 m-1 at salinity ~ 20; D’Sa and Miller, 2003), the Amazon
21
River estuary (aCDOM(440) ~ 0.78 at salinities of ~15; Green and Blough, 1994) and the
22
western tropical Atlantic Ocean under the influence of the Amazon river plume
23
(aCDOM(440) ~ 0.2 m-1 at salinity ~ 30; Del Vecchio and Subramanian, 2004).
10
1
2
4.2 Particle Absorption (ap)
3
The absorption coefficient due to particulates, ap(λ), is defined as the sum of the
4
absorption coefficients due to phytoplankton, aph(λ), and detritus, ad(λ). Figure 6 provides
5
a visual interpretation of the relative contribution of aph(440) and ad(440) to ap(440).
6
During the wet and dry seasons, ad (λ) dominated ap(λ) in the southern GOP and around
7
Serpent’s Mouth near the Orinoco Delta. ad(λ) decreased toward Dragon’s Mouth as
8
phytoplankton contributions to ap(λ) increased and dominated in the northern GOP and
9
SEC, particularly during the dry season. At a few SEC stations located immediately north
10
of Dragon’s Mouth, ad(λ) was as high as aph(λ) or higher. In the coastal upwelling region
11
immediately to the west of Dragon’s Mouth along the coast of the Paria Peninsula,
12
phytoplankton dominated ap(λ) during both seasons. Table 3 shows the percentage values
13
for the contributions of aph(λ) and ad(λ) to ap(λ) at each station.
14
During the dry season aph(440) ranged from 0.016 m-1 (SIM5_12) to 0.549 m-1
15
(SIM3_11), with minimum values in the SEC. During the wet season aph(440) ranged
16
from 0.013 m-1 (SIM6_10) to 0.113 m-1 (SIM4_3). This time the minimum values were
17
found in the GOP. The maximum, however, did not show any pattern with season except
18
for the coastal upwelling station west of Dragon’s Mouth. This station showed a
19
maximum during the dry season (Table 2). An extreme value of aph(440) (0.549 m-1) was
20
observed during SIM3 at a station in the GOP (SIM3_11), coinciding with a maximum in
21
surface chlorophyll-a concentration (8.11 mg m-3) related to a red tide event observed at
22
that location. Beside this exceptional event, mean values of surface aph(440) showed no
23
apparent spatial or seasonal variability.
11
1
The specific absorption coefficient of phytoplankton (aph*) is an indicator of the
2
phytoplankton ability to absorb light, and is broadly related to changes in light intensity
3
(photoadaptation), nutrient availability, pigment composition, and/or size and geometry
4
of the cells (change in population, package effect) (Sathyendranath et al., 1987; Carder et
5
al., 1999; Kirk, 1994; Bricaud et al., 1995). Changes in aph*() were largest between 400
6
and 550 nm (Figure 7). During the dry season aph*(440) varied from 0.019 m2 mg-1
7
(SIM3_1) to 0.095 m2 mg-1 (SIM5_11) in the GOP and 0.020 m2 mg-1 (SIM1_8) to 0.16
8
m2 mg-1 (SIM5_7) in the SEC. During the wet season aph*(440) showed a range of 0.021
9
m2 mg-1 (SIM4_4) to 0.072 m2 mg-1 (SIM6_20) in the GOP and of 0.017 m2 mg-1
10
(SIM6_20) to 0.109 m2 mg-1 (SIM6_7) in the SEC (Table 2). Most of the values were
11
within the aph*(440) range estimated by Prieur and Sathyendranath (1981) for marine
12
waters (0.013 m2 mg-1 to 0.077 m2 mg-1).
13
Variations in aph*(440) were usually accompanied by small variations in
14
aph*(675). According to Fujiki and Taguchi (2002), variations in aph*(675) can be
15
attributed to the package effect of chlorophyll. Variations in aph*(440), however, may
16
result from combined influences of package effect and changes in pigment composition
17
of the cell.
18
Changes in pigment composition result from changes in community structure or
19
phytoplankton adaptations to light. Phytoplankton cells increase the content of
20
photoprotective pigments under high light conditions, while they increase the content of
21
accessory photosynthetic pigments under dark conditions. In other words, the ratio of
22
photosynthetic to photoprotective pigments present in a cell is a function of the irradiance
23
intensity and history. Photosynthetic pigments are normally less variable, thus
12
1
photoprotective pigments are considered to drive most changes in aph() (Lohrenz et al.,
2
2003; Culver and Perry, 1999). With exception of SIM5, values of maximum depth
3
penetration of light indicate that the blue light (at 412 and 443 nm) was attenuated to 1%
4
of the subsurface irradiance in the first 5 and 10 m of the water column in the GOP and
5
SEC, respectively, during both seasons. Values of diffuse attenuation coefficient, Kd(),
6
at the same wavelengths, were 2 to 3 times higher in the GOP than in the SEC, especially
7
during the cruises in 1999 (SIM3 and SIM4).
8
9
Keith et al. (2002) indicate that in waters with high CDOM absorption and small
spectral slope values (S  0.020 nm-1), phytoplankton must utilize accessory
10
photosynthetic pigments at wavelengths longer than 440 nm to collect sufficient levels of
11
light energy to assure survival. Similar to what was observed by Bricaud et al. (1995), we
12
observed a tendency of aph* in the blue to increase with decreasing chlorophyll
13
concentration (Figure 7). This relationship has been explained in the past as “package
14
effect” but it could also be related to a relative increase in concentration of accessory
15
pigments (Bricaud et al., 1995; Ciotti et al., 1999).
16
17
4.3 CDOM and particle contributions to total absorption
18
The multi-year set of CDOM, phytoplankton pigment, and detritus absorption
19
coefficient observations clearly demonstrates that CDOM dominated the absorption of
20
blue light in the Orinoco River plume (Table 4; Figure 8). While substantial patchiness in
21
water color is observed off the Orinoco Delta, at most stations, CDOM absorbed close to
22
90% of the light at 440 nm in the GOP and SEC during both seasons. During the dry
23
season, the remaining 10% of the total blue light absorption coefficient was partitioned,
13
1
more or less equally, between detritus and phytoplankton. During the wet season, the
2
contribution due to detritus increased in the GOP to about 8%, while in the SEC the
3
detritus contribution decreased to < 5%. Within patches in the GOP, we saw detritus
4
absorption coefficients that contributed as much as 34% to absorption at 440 nm during
5
the wet season. Similarly, occasional aph(440) as high as 20% of the total absorption was
6
seen in the GOP during the dry season.
7
Average ag(440) to aph(440) ratios ranged from 3.33 to 139.4 in the GOP and
8
from 9.2 to 80.63 in the SEC, with higher ratios in the GOP than in the SEC. The SIM6
9
cruise (October 2000) was an exception in that the ratios were about the same in the GOP
10
and SEC (Table 5). The reason for this was not entirely clear. In the GOP, the highest
11
mean ratio was observed during SIM4 in October 1999, which was a year with very high
12
precipitation over northern South America. The lowest ratio was observed during SIM5
13
in March 2000. Spatial changes observed in the ratio were dominated by spatial changes
14
in ag(440). This persistently high ratio is a concise indicator that the traditional bio-
15
optical band ratio algorithms are not adequate to estimate biomass in the Orinoco plume,
16
and it is also and indicator of the uniqueness bio-optical characteristics of this region.
17
Del Vecchio and Subramaniam (2004) investigated the contributions of
18
particulate and dissolved materials to total light absorption in the Amazon River plume
19
during low and high discharge. They found that, during high river flow, >70% of the light
20
at 440nm was absorbed by CDOM close to the river mouth, but in the plume offshore
21
(~1000 km from the river mouth, with surface salinity values close to 32) CDOM
22
absorption decreased to < 20% while phytoplankton absorbed ~40%. D’Sa and Miller
23
(2003) reported that during low Mississippi River flow, phytoplankton and detritus
14
1
dominate absorption in the Mississippi's plume, with CDOM contributing to <25% of
2
absorption in areas near the coast, where salinity values were ~20 and chlorophyll
3
concentrations were high (~17 mg m-3). In offshore stations (salinity >33), they found
4
that CDOM absorption contributions increased to >50% while chlorophyll concentrations
5
substantially decreased to <0.2 mg m-3. Most chlorophyll-a values (~90%) observed in
6
the GOP and SEC were <3 mg m-3 with no significant spatial variability or nearshore-
7
offshore gradient within the portion of the plume studied in the GOP and SEC.
8
9
Chlorophyll-a concentrations and primary productivity within the stem of
Orinoco River are below values seen in other large rivers. Lewis (1988) concluded that
10
this low production is due to several reasons which include light limitation, a small
11
biomass that requires a lengthy period of growth and high velocities of flow that reduce
12
the potential for biomass accumulation. Productivity is likely to increase as sediments
13
settle out of surface waters immediately off the delta, but biomass is limited by the high
14
secondary production of these waters, evidenced by the extremely active shrimp and
15
coastal groundfish fishery of the region (WECAFC, 1997).
16
During the period of our cruises to the Orinoco River plume (1998-2000), the
17
Pacific Ocean experienced a “La Niña” episode. Above-normal precipitation occurred
18
over the Caribbean Sea (Bell et al., 1999 and 2000). This likely led to higher runoff and
19
terrestrial CDOM delivery to the GOP and SEC. Unfortunately, we were unable to obtain
20
discharge measurements of the Orinoco River for these years and we understand that,
21
regrettably, the river may not be gauged at this time.
22
23
4.4. Bio-optical algorithms
15
1
Application of the OC4v4 algorithm in the SEC using in situ Rrs(λ) observations
2
leads to overestimation of chlorophyll-a concentrations (Figure 9), with higher errors at
3
lower concentrations. Percentage errors (%E) ranged from about 20% (SIM3_7) to over
4
1000% (SIM4_8), with an average overestimation of over 200%. The lowest errors were
5
calculated in the upwelling zone along the northern coast of the Paria Peninsula (SIM3_7,
6
and SIM4_7).
7
Regressions between in situ chlorophyll-a concentration and Rrs(λ) band ratios
8
show that changes in chlorophyll-a concentration do not produce noticeable changes in
9
the band ratios. Yet, small variations in Rrs(λ) result in larger errors in the estimation of
10
chlorophyll-a. The bio-optical band ratios are dominated by aCDOM(λ) rather than by
11
aph(λ) in the plume. Therefore, the OC4v4 algorithm fails.
12
Carder et al. (1999) developed a semi-analytical algorithm to explicitly separate
13
chlorophyll-a from CDOM. This algorithm is based on an inversion model, in which
14
absorption coefficients are derived from Rrs(λ) measurements. However, we obtained
15
percentage errors >100% in chlorophyll estimates for the Orinoco plume using the
16
inversion method. This is partially due to the fact that the semi-analytical algorithm
17
switches to the traditional band ratio method if Rrs(412)/Rrs(443) is below a predefined
18
threshold.
19
An alternative to derive chlorophyll-a concentrations from satellite sensors (e.g.
20
MODIS) in this region is to use the Fluorescence Line Height algorithm, which is based
21
on solar-stimulated chlorophyll fluorescence (~683 nm), where CDOM interference is
22
minimal. This approach has proven to be of great value over the west Florida shelf, where
23
traditional band ratio and semi-analytical bio-optical algorithms fail due to the presence
16
1
of large quantities of riverine CDOM (Hu et al., 2005). This MODIS product is still
2
experimental, requires careful atmospheric correction which has not yet been tested, and
3
in general remains uncalibrated. Similar approaches should be explored further in the
4
future for other coastal regions affected by rivers.
5
6
7
5. Conclusion
CDOM dominated the total absorption coefficient in the blue wavelengths in the
8
Orinoco River plume, Gulf of Paria (GOP) and southeastern Caribbean Sea (SEC), during
9
both the wet (June, October) and dry (February) seasons of 1998, 1999, and 2000.
10
CDOM contributions to total absorption coefficient at 440 nm were as high as 98%; such
11
high values were observed in both seasons. Near the Orinoco Delta, detritus dominated
12
the absorption coefficient by particles, whereas in the Gulf of Paria and southeastern
13
Caribbean Sea phytoplankton dominated. The ratio of CDOM to phytoplankton
14
absorption in the Orinoco plume was higher than in other coastal regions, due to the
15
unique characteristics of the Orinoco River plume. Some of these high values could also
16
be attributed to the 1998-2000 La Niña event, which caused extreme rainfall over the
17
southeastern Caribbean. These high values of CDOM to phytoplankton absorption limit
18
the applicability of traditional band-ratio and semi-analytical bio-optical algorithms that
19
use blue light to estimate aquatic chlorophyll-a concentration in this region. For this
20
reason, the use of the chlorophyll-a Fluorescence Line Height algorithms (~ 680 nm)
21
deserves further research in coastal areas affected by riverine inputs.
17
6. Acknowledgements
This work was supported by NASA grants NAS5-31716 and NAG5-10738, and by
NASA’s Earth Science Fellowship, grant # NGT5-30354. We thank the personnel of the
Fundación La Salle, Estación de Investigaciones Marinas de Margarita
(FLASA/EDIMAR) for their professional support. In particualr we thank the crew of the
R/V Hno. Ginés (FLASA), and Anadiuska Rondon, John Akl, and Glenda Arias who
provided essential field and laboratory support.
1
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10
Figure Captions
Figure1. Study region showing the extent of the Orinoco River and the Orinoco River
Delta (inset).
Figure 2. Climatological average hydrograph showing the discharge of the Orinoco River
at Puente Angostura, showing maxima, minima, and mean monthly values, using data
from 1923 to 1989 (Source: Vörösmarty et al., 1998). Arrows show months when cruises
were conducted.
Figure 3. Location of the sampling stations for each cruise conducted between 1998 and
2000. The imagery was collected using the SeaWiFS sensor (images courtesy of
OrbImage Corp.). The images represent the standard chlorophyll-a product generated
using the standard NASA bio-optical algorithms which confound the optical effects of
CDOM and chlorophyll and therefore overestimate chlorophyll in an undetermined
manner within river plumes of the region.
Figure 4. CDOM absorption spectra. Blue-SEC stations, Black-GOP stations.
Figure 5. Relationship between CDOM absorption coefficient at 440 nm, aCDOM(440),
and salinity (A); between CDOM spectral slope, S, and salinity (B); and between
aCDOM(440) and chlorophyll-a (C).
Figure 6. Percentage contributions of phytoplankton and detritus to particle absorption
coefficient at 440 nm .
Figure 7. Phytoplankton specific absorption (aph*()) spectra in the Orinoco River plume
for dry (A) and wet (B) seasons. Panel C shows the relationship between aph* at 440 nm
and Chlorophyll_a concentrations (log scale).
11
Figure 8. Percentage contributions of CDOM, phytoplankton and detritus to total
absorption coefficient at 440 nm (dots indicate position of the stations).
Figure 9. Chlorophyll-a concentration derived from the OC4v4 algorithm, [Chl-a]OC4v4
versus chlorophyll-a concentrations measured from in situ water samples [Chl-a]mea
during the dry (A) and wet (B) seasons.
12
Tables
Table 1. Orinoco-SIMBIOS cruises
CRUISE ID
DATES
SIM1 (9)
Jun. 24 – Jun. 28, 1998
SIM2 (16)
Oct. 27 – Oct. 30, 1998
SIM3 (15)
Feb. 23 – Feb. 28, 1999
SIM4 (14)
Oct. 26 – Oct. 30, 1999
SIM5 (14)
Mar. 27 – Mar. 31, 2000
SIM6 (17)
Oct. 21 – Oct. 26, 2000
( ) = number of stations sampled
SEASON
Dry-wet
Wet
Dry
Wet
Dry
Wet
13
Table 2. Location, date, salinity, chlorophyll-a concentration, phytoplankton specific
absorption coefficient at 440 nm, phytoplankton, detritus, and CDOM absorption
coefficients at 440 nm, and CDOM spectral slope for each station
Latitude Longitude
(N)
(W)
Station #
SIM1_7
10.55
-61.89
SIM1_6
10.67
-61.83
(SIM1_4) 10.78
-62.00
SIM1_5
10.79
-61.85
SIM1_11 11.02
-61.81
SIM1_8
11.01
-61.87
SIM1_12 11.10
-61.89
SIM1_13 11.16
-61.95
SIM1_9
11.22
-62.00
SIM2_16 10.00
-62.02
SIM2_15 10.01
-62.02
SIM2_14 10.03
-62.01
SIM2_2
10.11
-62.11
SIM2_3
10.43
-61.96
SIM2_4
10.55
-61.89
SIM2_5
10.68
-61.83
SIM2_5b 10.68
-61.83
(SIM2_7) 10.78
-62.00
SIM2_6b 10.79
-61.83
SIM2_6
10.81
-61.83
SIM2_18 10.87
-61.94
SIM2_17 10.95
-61.86
SIM2_8
11.02
-61.78
SIM2_9
11.11
-61.80
SIM2_10 11.21
-61.79
SIM3_1
9.98
-61.80
SIM3_2
10.00
-61.92
SIM3_3
10.03
-62.06
SIM3_11 10.17
-62.10
SIM3_4
10.55
-61.89
SIM3_5
10.73
-61.83
SIM3_6
10.80
-61.81
(SIM3_7) 10.82
-61.96
SIM3_8
10.93
-61.78
SIM3_9
11.11
-61.81
SIM3_10 11.28
-61.82
SIM4_1_1 9.98
-61.80
SIM4_1_2 10.00
-61.87
SIM4_2
10.00
-61.92
SIM4_3
10.03
-62.06
SIM4_11 10.17
-62.10
SIM4_4
10.55
-61.89
SIM4_5
10.73
-61.83
(upwelling focus station)
SEC stations
Date
26-Jun-98
26-Jun-98
25-Jun-98
25-Jun-98
27-Jun-98
26-Jun-98
27-Jun-98
27-Jun-98
26-Jun-98
27-Oct-98
27-Oct-98
27-Oct-98
27-Oct-98
28-Oct-98
28-Oct-98
28-Oct-98
30-Oct-98
28-Oct-98
30-Oct-98
28-Oct-98
30-Oct-98
30-Oct-98
29-Oct-98
29-Oct-98
29-Oct-98
24-Feb-99
24-Feb-99
24-Feb-99
24-Feb-99
25-Feb-99
25-Feb-99
25-Feb-99
25-Feb-99
26-Feb-99
26-Feb-99
26-Feb-99
28-Oct-99
28-Oct-99
28-Oct-99
28-Oct-99
28-Oct-99
29-Oct-99
29-Oct-99
a ph*
(440) a ph (440) a d (440) a CDOM (440)
S
Salinity Chl-a
(PSU) (mg m-3) (mg m-2)
(m-1)
(m-1)
(m-1)
(nm-1)
24.67
24.33
36.42
29.45
27.59
27.36
31.54
31.18
29.94
19.00
15.36
18.97
18.18
20.00
20.79
21.65
21.32
34.60
31.75
22.15
34.15
30.38
25.40
28.87
29.19
21.27
26.05
27.19
27.06
24.23
25.11
28.33
33.54
27.09
29.17
34.94
20.32
22.92
19.54
15.32
20.50
19.23
20.04
2.54
2.31
0.15
1.94
1.23
1.88
2.04
2.41
2.42
1.00
1.02
0.77
1.30
1.54
0.62
0.78
2.12
0.63
1.64
1.63
0.68
1.80
1.00
0.79
0.92
1.87
1.78
1.66
8.11
1.60
1.15
0.64
3.52
1.10
1.70
0.17
0.97
0.39
0.40
2.38
1.44
1.30
1.88
14
0.0154
0.0168
0.0728
0.0203
0.0225
0.0135
0.0188
0.0184
0.0173
0.0226
0.0200
0.0316
0.0211
0.0252
0.0342
0.0241
0.0135
0.0283
0.0162
0.0188
0.0340
0.0351
0.0428
0.0285
0.0113
0.0281
0.0334
0.0155
0.0301
0.0179
0.0498
0.0229
0.0262
0.0861
0.0524
0.0640
0.0331
0.0286
0.0138
0.0151
0.0162
0.055
0.054
0.038
0.037
0.053
0.065
0.057
0.033
0.031
0.046
0.039
0.057
0.034
0.029
0.046
0.030
0.045
0.047
0.034
0.053
0.049
0.039
0.035
0.077
0.091
0.550
0.038
0.050
0.021
0.273
0.042
0.070
0.024
0.073
0.040
0.023
0.113
0.034
0.027
0.046
0.036
0.034
0.025
0.024
0.029
0.025
0.029
0.307
0.227
0.169
0.160
0.064
0.018
0.018
0.050
0.005
0.049
0.039
0.007
0.030
0.020
0.019
0.545
0.186
0.143
0.206
0.009
0.023
0.051
0.053
0.009
0.014
0.002
0.576
0.087
0.074
0.754
0.069
0.026
0.044
1.144
0.014
2.384
0.010
0.706
0.014
1.823
0.013
1.432
0.014
1.410
0.014
1.522
0.014
1.000
0.015
1.253
0.015
0.403
0.018
1.130
0.015
0.773
0.016
0.659
0.016
0.455
0.017
0.465
0.016
2.217
0.013
1.620
0.014
1.236
0.014
1.829
0.013
2.485
0.013
2.135
0.013
1.672
0.013
1.628
0.014
1.169
0.015
1.024
0.015
1.501
0.014
3.208
0.013
3.185
0.013
1.053
0.015
1.163
0.015
1.070
0.015
(Continues )
Table 2. (Continued)
Latitude Longitude
(N)
(W)
Station #
SIM4_6
10.80
-61.81
(SIM4_7) 10.82
-61.96
SIM4_8
10.93
-61.78
SIM4_9
11.11
-61.81
SIM4_10 11.28
-61.82
SIM5_1
9.98
-61.80
SIM5_2
10.00
-61.93
SIM5_3
10.03
-62.06
SIM5_11 10.17
-62.08
SIM5_4
10.55
-61.89
SIM5_5
10.67
-61.83
(SIM5_7) 10.78
-62.00
SIM5_6
10.78
-61.83
SIM5_8
10.94
-61.78
SIM5_9
11.10
-61.78
SIM5_10 11.27
-61.78
SIM5_12 11.43
-61.78
SIM6_1
9.98
-61.80
SIM6_2
10.00
-61.93
SIM6_3
10.03
-62.06
SIM6_11 10.17
-62.08
SIM6_20 10.42
-61.93
SIM6_4
10.55
-61.89
SIM6_5
10.67
-61.83
SIM6_6
10.78
-61.83
(SIM6_7) 10.78
-62.00
SIM6_8
10.94
-61.78
SIM6_9
11.10
-61.79
SIM6_10 11.27
-61.78
SIM6_12 11.43
-61.78
(upwelling focus station)
SEC stations
Date
29-Oct-99
29-Oct-99
30-Oct-99
30-Oct-99
30-Oct-99
29-Mar-00
29-Mar-00
29-Mar-00
29-Mar-00
30-Mar-00
30-Mar-00
30-Mar-00
30-Mar-00
31-Mar-00
31-Mar-00
31-Mar-00
31-Mar-00
24-Oct-00
24-Oct-00
24-Oct-00
24-Oct-00
25-Oct-00
25-Oct-00
25-Oct-00
25-Oct-00
25-Oct-00
26-Oct-00
26-Oct-00
26-Oct-00
26-Oct-00
a ph*
a ph (440) a d (440) a CDOM (440)
Chl-a
(440)
S
Salinity
(PSU) (mg m-3) (mg m-2)
(m-1)
(m-1)
(m-1)
(nm-1)
22.24
35.61
22.75
23.78
32.25
30.34
31.21
31.24
32.55
31.79
31.77
36.23
31.71
32.61
33.13
33.22
35.46
15.79
11.01
16.28
17.72
19.95
15.61
16.36
26.41
34.64
17.49
24.31
29.28
32.45
1.06
3.00
0.79
1.12
0.28
1.27
1.14
1.08
0.97
0.51
0.55
1.47
0.62
0.56
0.66
0.54
0.18
1.05
1.46
1.39
1.52
0.67
1.09
0.62
0.71
0.18
1.53
1.13
0.17
0.20
15
0.0207
0.0206
0.0306
0.0334
0.0533
0.0359
0.0386
0.0370
0.0679
0.0397
0.0356
0.0515
0.0387
0.0345
0.0428
0.0538
0.0652
0.02958
0.03539
0.03477
0.02509
0.03433
0.02511
0.03674
0.03174
0.07036
0.03011
0.01158
0.05059
0.04625
0.032
0.082
0.035
0.052
0.023
0.067
0.063
0.057
0.092
0.028
0.026
0.099
0.033
0.027
0.037
0.022
0.016
0.046
0.070
0.067
0.055
0.048
0.040
0.035
0.034
0.020
0.070
0.019
0.013
0.015
0.089
0.023
0.033
0.012
0.010
0.073
0.061
0.260
0.036
0.010
0.003
0.007
0.041
0.037
0.031
0.005
0.015
0.407
0.405
0.241
0.039
0.023
0.026
0.017
0.020
0.003
0.055
0.023
0.004
0.003
1.110
2.590
1.104
0.415
0.562
0.245
0.231
2.696
2.121
1.431
1.683
1.441
1.543
1.002
-
0.015
0.012
0.015
0.017
0.015
0.019
0.020
0.013
0.013
0.014
0.014
0.014
0.014
0.014
-
Table 3. Detritus and phytoplankton contributions to particle absorption
Station
SIM1_7
SIM1_6
SIM1_5
SIM1_8
SIM1_11
SIM1_12
SIM1_13
SIM1_9
SIM2_16
SIM2_15
SIM2_14
SIM2_2
SIM2_3
SIM2_4
SIM2_5
SIM2_5B
SIM2_6
SIM2_6B
SIM2_8
SIM2_9
SIM2_10
SIM2_7
SIM2_18
SIM3_1
SIM3_2
SIM3_3
SIM3_11
SIM3_4
SIM3_5
SIM3_6
SIM3_8
SIM3_9
SIM3_10
SIM3_7
SIM4_1_1
SIM4_1_2
a d (440)
%
a ph (440)
%
39.56
38.64
76.72
39.34
39.68
35.37
27.78
33.72
90.29
87.98
78.60
80.40
52.89
34.62
38.30
52.08
45.35
52.13
36.14
28.99
32.76
14.29
17.07
93.97
70.72
61.11
27.25
19.15
31.51
70.83
17.65
16.67
7.69
16.26
88.75
68.50
60.44
61.36
23.28
60.66
60.32
64.63
72.22
66.28
9.71
12.02
21.40
19.60
47.11
65.38
61.70
47.92
54.65
47.87
63.86
71.01
67.24
85.71
82.93
6.03
29.28
38.89
72.75
80.85
68.49
29.17
82.35
83.33
92.31
83.74
11.25
31.50
Station
SIM4_2
SIM4_3
SIM4_11
SIM4_4
SIM4_5
SIM4_6
SIM4_8
SIM4_9
SIM4_10
SIM4_7
SIM5_1
SIM5_2
SIM5_3
SIM5_11
SIM5_4
SIM5_5
SIM5_6
SIM5_8
SIM5_9
SIM5_10
SIM5_12
SIM5_7
SIM6_1
SIM6_2
SIM6_3
SIM6_11
SIM6_20
SIM6_4
SIM6_5
SIM6_6
SIM6_8
SIM6_9
SIM6_10
SIM6_12
SIM6_7
16
a d (440)
%
a ph (440)
%
76.29
86.97
66.99
49.06
48.89
73.55
48.53
18.75
30.30
21.90
52.14
49.19
82.02
28.13
26.32
10.34
55.41
57.81
45.59
18.52
48.39
6.60
89.85
85.26
78.25
41.49
32.39
39.39
32.69
37.04
44.00
54.76
23.53
16.67
13.04
23.71
13.03
33.01
50.94
51.11
26.45
51.47
81.25
69.70
78.10
47.86
50.81
17.98
71.88
73.68
89.66
44.59
42.19
54.41
81.48
51.61
93.40
10.15
14.74
21.75
58.51
67.61
60.61
67.31
62.96
56.00
45.24
76.47
83.33
86.96
Table 4. CDOM, detritus and phytoplankton contributions to total absorption
Station
SIM1_7
SIM1_6
SIM1_5
SIM2_16
SIM2_15
SIM2_14
SIM2_2
SIM2_3
SIM2_4
SIM2_5B
SIM2_5
SIM2_6
SIM2_8
SIM2_9
SIM2_10
SIM3_1
SIM3_2
SIM3_3
SIM3_11
SIM3_4
SIM3_5
SIM3_6
SIM3_8
SIM3_9
a CDOM (440)
%
a d (440)
%
a ph (440)
%
92.17
96.17
74.79
84.02
84.42
86.42
88.13
88.69
95.53
91.71
88.42
89.29
88.03
85.66
87.87
79.09
85.76
83.73
70.59
97.89
96.38
95.56
96.59
92.80
2.89
1.38
18.82
14.16
13.41
10.37
9.24
5.67
1.41
4.07
3.85
4.50
3.99
3.85
3.54
19.44
9.85
9.68
7.95
0.37
1.06
2.89
0.53
1.14
4.43
2.20
5.72
1.53
1.80
2.82
2.26
5.08
2.58
3.71
6.33
5.48
7.13
9.30
7.39
1.24
4.05
6.15
21.21
1.50
2.28
1.19
2.50
5.56
Station
SIM4_1_1
SIM4_1_2
SIM4_2
SIM4_3
SIM4_11
SIM4_4
SIM4_5
SIM4_8
SIM5_2
SIM5_11D
SIM5_4
SIM5_5
SIM5_8
SIM5_10
SIM6_2
SIM6_3
SIM6_11
SIM6_20
SIM6_4
SIM6_6
SIM6_10
17
a CDOM (440)
%
a d (440)
%
a ph (440)
%
60.95
91.88
96.88
78.49
90.57
95.15
91.68
93.71
95.20
89.20
90.26
90.26
94.13
87.28
84.86
87.08
93.44
95.58
95.24
96.22
97.76
34.30
5.30
2.23
18.58
5.92
2.15
3.80
2.81
2.26
2.88
2.22
2.22
0.52
2.06
12.74
9.90
2.58
1.30
1.71
1.28
0.37
4.37
2.43
0.70
2.77
2.96
2.18
3.98
2.95
2.30
7.41
6.13
6.13
4.29
8.26
2.20
2.76
3.57
2.75
2.63
2.11
1.25
Table 5. CDOM absorption to phytoplankton absorption ratios at 440 nm
Station
SIM1_7
SIM1_6
SIM1_5
SIM2_16
SIM2_15
SIM2_14
SIM2_2
SIM2_3
SIM2_4
SIM2_5B
SIM2_5
SIM2_6
SIM2_8
SIM2_9
SIM2_10
SIM3_1
SIM3_2
SIM3_3
SIM3_11
SIM3_4
SIM3_5
SIM3_6
SIM3_8
a g (440)/a ph (440)
20.81
43.76
13.08
54.85
46.90
30.67
38.95
17.46
37.01
24.72
13.96
16.28
12.35
9.21
11.89
63.66
21.16
13.61
3.33
65.45
42.30
80.63
38.59
Station
SIM3_9
SIM4_1_1
SIM4_1_2
SIM4_2
SIM4_3
SIM4_11
SIM4_4
SIM4_5
SIM4_8
SIM5_2
SIM5_11D
SIM5_4
SIM5_5
SIM5_8
SIM5_10
SIM6_2
SIM6_3
SIM6_11
SIM6_20
SIM6_4
SIM6_6
SIM6_10
18
a g (440)/a ph (440)
16.69
13.95
37.80
139.39
28.31
30.60
43.59
23.04
31.81
41.35
12.04
14.71
14.71
21.97
10.57
38.54
31.59
26.16
34.73
36.22
45.66
77.92