Estuarine, Coastal and Shelf Science (1990) 31, l-9 The Radiometric Determination of Total Pigment and Seston and its Potential Use in Shelf Seas J. Brown and J. H. Simpson Marine Science Laboratories, University College of North Wales, Menai Bridge, Gwynedd, LL59 5EY, U.K. Received 29January 1990 and in revisedform 13June 1990 Keywords: irradiance meters; chlorophyll measurements; seston; spectral analysis; remote sensing; continental shelf A total of 293 radiometric observations of subsurface reflectance and simul- taneous measurements of pigment and seston provide the basis for improved algorithms relating surface properties to spectral reflectance R(1). Without allowance for the effects of seston, total pigment concentration C (chlorophyll a + phaeopigment) for our entire data set fits an algorithm of the form C = a)‘-*; y = R(440 nm)/R(550 nm) with constants a = - 0.06 and b = 1.60. The effect of inorganic seston concen- tration, Z,, over the range 0 <Z, < 6 mg l-‘, is to modify the exponent b such that it increases significantly according to b = 1.80 + O-38 Z,. This result confirms the trend apparent in discrete values of b for case 1 and case 2 waters, but also implies that there may be advantages in a (physically more realistic) continuous representation. C, is found to be related to the intensity of reflectance at 550 nm, but with a slope m which is controlled by the concentration of organic seston Z0 through the relation m = 0.094 - 1.046 ZO. Owing to the highly variable nature of the organic component, La cannot at present be reliably determined from the radiometric data. Hence, the general problem of determining C, C, and Z, from radiometer data in remote sensing and in situ applications cannot generally be solved without additional estimates of Z;. Introduction Phytoplankton pigments and suspended sediments are key factors in controlling the bio- logical and chemical processes of the shelf seas. Chlorophyll concentrations in the surface waters are closely linked to the levels of primary productivity by phytoplankton which correspond to overall variations of biomass (Floodgate et al., 1981) and the distribution and activity of fish and sea birds (Brown, 1980). Suspended sediment particles regulate the light energy available for photosynthesis and their surfaces are increasingly recognized as sites for microbiological activity (Hoppe, 1984). In addition, they play a significant role in the transport of elements and compounds by chemical adsorption and desorption. 0272-7714/90/070001+09 $03.00/O @ 1990 Academic Press Limited
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Estuarine, Coastal and Shelf Science (1990) 31, l-9
The Radiometric Determination of Total Pigment and Seston and its Potential Use in Shelf Seas
J. Brown and J. H. Simpson Marine Science Laboratories, University College of North Wales, Menai Bridge,
Gwynedd, LL59 5EY, U.K.
Received 29January 1990 and in revisedform 13June 1990
A total of 293 radiometric observations of subsurface reflectance and simul- taneous measurements of pigment and seston provide the basis for improved algorithms relating surface properties to spectral reflectance R(1). Without allowance for the effects of seston, total pigment concentration C (chlorophyll a + phaeopigment) for our entire data set fits an algorithm of the form
C = a)‘-*; y = R(440 nm)/R(550 nm)
with constants a = - 0.06 and b = 1.60. The effect of inorganic seston concen- tration, Z,, over the range 0 <Z, < 6 mg l-‘, is to modify the exponent b such that it increases significantly according to b = 1.80 + O-38 Z,. This result confirms the trend apparent in discrete values of b for case 1 and case 2 waters, but also implies that there may be advantages in a (physically more realistic) continuous representation.
C, is found to be related to the intensity of reflectance at 550 nm, but with a slope m which is controlled by the concentration of organic seston Z0 through the relation m = 0.094 - 1.046 ZO. Owing to the highly variable nature of the organic component, La cannot at present be reliably determined from the radiometric data. Hence, the general problem of determining C, C, and Z, from radiometer data in remote sensing and in situ applications cannot generally be solved without additional estimates of Z;.
Introduction
Phytoplankton pigments and suspended sediments are key factors in controlling the bio- logical and chemical processes of the shelf seas. Chlorophyll concentrations in the surface waters are closely linked to the levels of primary productivity by phytoplankton which correspond to overall variations of biomass (Floodgate et al., 1981) and the distribution and activity of fish and sea birds (Brown, 1980). Suspended sediment particles regulate the light energy available for photosynthesis and their surfaces are increasingly recognized as sites for microbiological activity (Hoppe, 1984). In addition, they play a significant role in the transport of elements and compounds by chemical adsorption and desorption.
Distributions of phytoplankton pigments and suspended sediments are both subject to considerable variability on spatial scales down to 10m or less. These parameters also undergo substantial changes with time, in part due to the high energy tidal regime of the shelf. To successfully assess the concentration patterns of these variables, we might hope to use the synoptic view provided by visible band imagery from aircraft and satellite mounted scanners, whose coverage cannot be matched by conventional surface measurements.
Where levels of suspended sediment are low and the biomass determines the optical properties of the surface waters, a degree of success has been achieved in determining pigmentdistributions,e.g. theGulfStream(Gordonetal., 1980)andMiddleAtlanticBight (Gordon et al., 1983). At the other extreme, Topliss (1986) summarizes work in which the suspended sediment concentrations dominate pigments and for which algorithms based on the spectral signature of the water leaving signal can be derived. When both pigments and sediment jointly influence the spectral signature of the water leaving radiance the situation becomes less certain. Attempting to resolve this uncertainty Mitchelson et al. (1986) examined data from the Irish Sea and Scottish coastal waters using the classification of case 1 (pigment dominated) and case 2 (sediment and/or yellow substance dominated) waters, detailed by Morel and Prieur (1977), Morel (1980) and Gordon and Morel (1983). It was concluded that total pigment concentrations could be determined to a log accuracy of approximately + 0.2 based on a log-log relationship with the colour ratio of upwelling radiances at 440 and 550 nm.
In this paper we have examined an extensive data set collected in the Irish Sea and Menai Strait and augmented by data from around the Island of Aldabra in the Indian Ocean and the Iberian upwelling region. Supplementing this we have also considered the data of Mitchelson et al. (1986), which included data from the Scottish Shelf. Consequently we are able to present a number of algorithms which determine total pig- ment (C) concentrations on the basis of the spectral signature of the sea surface, for different ranges of inorganic seston (C,) concentrations. We also consider further the interpretation of radiometric data used to interpret reflectance data quantitatively in terms of total seston (C) concentrations.
Data collection
Results presented here are based principally on the analysis of data collected from the west coast shelf waters of the U.K. (see Figure l), compiled during March-September 1982-86 inclusive. Further profiles were also obtained from the Iberian upwelling region (Haynes & Barton, 1990), in September 1986, and around the Indian Ocean atoll of Aldabra (9”3O’S, 46”20’E) during May and June 1987. Sampling included discrete near- surface measurements of C (chlorophyll a and phaeopigment), yellow substance fluorescence in shelf waters and inorganic (Zi) and organic seston (,X0), using the tech- niques detailed in Mitchelson et al. (1986). For the shelf data, conditions varied from the relatively clear waters of the west Scottish shelf and Western Irish Sea, where C and Z concentrations were frequently as low as 0.5 mg m-3 and 0.3 mg l-l, respectively, to the turbid waters of Liverpool Bay and the Menai Strait, where values were as high as 20.0mgmP3 and 40.0mg l-‘, respectively. The oligotrophic conditions of the Indian Ocean and the Iberian upwelling region had negligible levels of C and values of C<0.6mgm-3.
Radiometric determination of pigment and seston 3
58”
56’
54”
52”
500
kMJ3w
\
North Sea
\ _ 4?‘/F,rlh of
.,
60” N
58”
56”
54”
52”
50”
Lo ..9”w-~--- L--...- 1- -I 6” 3” 0”
Figure 1. Sampling areas (shaded) for which shelf data were collected during March- September 1982-86 inclusive.
Spectral measurements of the subsurface reflectance
where Ei,(i) and Ed(A) are upwelling and downwelling irradiance, respectively, were made with a multi-channel irradiance meter (see Mitchelson et al., 1986), including the bands 440, 520,550 and 670 nm (bandwidth Ai, - 10 nm), which were chosen to coincide with the CZCS bands. The ratio R(J), where E,(I) and E,(A) are normalized by coincident surface light intensity readings is also independent of sensor calibration, since the same sensor is used for up- and downwelling measurements. Here we concentrate on the ratio ;~=I?(440 nm)/R(550 nm), representing the maximum (1” = 440 nm) and minimum (jL = 550 nm) levels of visible light absorption due to chlorophyll, and its relationship with C concentration. Measurements were made within 3 m of the surface, where y has been taken as independent of depth.
Pigment algorithms
The full data set is displayed in Figure 2 in the form of a log-log plot of C VS. 1’. Almost all the shelf data has I’> 1 while deep water data extends to 7 - 6.
4 3. Brown & 3. H. Simpson
+ UK Shelf
A lndlan ocean
o lberian coast
ho y
t i
-0.6 ~0.6 O-8
l
-0.6
UK Shelf All data
Figure 2. Full data set of log,,C us. log,,y [y= 83440 nm)/R(550 nm)] regression lines for U.K. shelf data and the total data set.
indicating the
Initially restricting the analysis to the shelf data, we find for the best estimate of C
log& = - 251( * 0.34)log,,y - 0.12( -t 0.07) (1)
with a coefficient of determination r’ = 0.45, n = 271 and a root mean square (r.m.s.) scatter of C about the regression of 0.29, in close accord with the earlier estimate from Mitchelson et al. (1986).
When the deep water data are added the fit is somewhat improved giving
log& = - 1.60( k O.l6)log,,y - O-06( + 0.04)
with r2 = 0.55, n = 293 and an r.m.s. deviation of 0.30.
(2)
These equations imply uncertainty by a factor of c. 2 in estimates of C. The algorithm of equation (2) is in reasonable agreement with previous work by Morel (1980), who found a gradient of - 1.40 and an intercept of 0.21 (y = R(440 nm)/R(560 nm)), for a mixture of case 1 and case 2 waters.
The slope(b) of equation (2) is significantly different from the shelf-only case suggesting a progressive change as y decreases. This change in b is likely to be associated with the large differences in Zi already noted and we have examined the possibility of a systematic dependence of this kind by analysing the data for different ranges of L’,. For each range of Lt concentration we have determined the constants a (intercept) and b which are shown in Table 1. For each of the first four ranges b can be determined with a high degree of confidence. Above Xi= 6 mg l-i, where our data set is relatively sparse and the spread of log,,C(O.O - 0.7) limited, b is not adequately determined.
Radiometric determination of pigment and seston 5
TABLE 1.
\ range
@xl 7
F SD SE of Significance b a t-2 n ratio ofb regression (“Cl)
x \ G -3 //Yy-l / 3 b--(0.382 tl.80) B r2= 0.95, ” = 4
-2
i
-I
Figure 3. Values oflog,,C/log,,y ZJS. Z, presented in Table 1, the regression line indicating the decrease in sensitivity of the colour ratio (y) to changes in C with increasing levels of inorganic seston (2,). Zt levels are presented as the median in each range (I) with the error bars denoting the standard errors.
Figure 3 presents graphically the values of b for the relationships listed in Table 1; the z‘! classification was chosen to give an adequate number of points in each category. Individ- ual fits within each range are comparable to those of equation (1). In the four ranges up to 6.0 mg 1-i there is a clear indication of a systematic increase of slope with increasing C2 content, such that the sensitivity of colour ratio to changes in C decreases significantly. For example, taking the 57 points for which Ci< 1.0 mg l-‘, we find b= - 1.97 which is close to the range of slopes ( - 1.7 1 to - 1.82) for case 1 waters given by Gordon and Morel (1983). As Z, increases, b becomes more negative, at least up to the range 3.0 < 1, < 60 mg l- ’ where b = - 3.40 and is significantly different at levels of 0.1 ‘IO, 5”,, and 25”,, to b in the ranges C, < 1.0, 1.0 <C, < 2.0 and 2.0 < L“l < 3.0, respectively. In the range Z, < 6.0 mg 1-i the change in relationship between log,,(C)/log,,y and Cj can be characterized by the equation
log,,(C) - = - [0.38( + 0.05) Z, + 1.80( * 0.14)]
log,,1 (3)
6 J. Brown &J. H. Simpson
with r2 = 0.95 and n = 4 and significant at the lOa o level. Using this variable form of 6 yields some improvement in the standard error of the regression for Z, < 2.0 mg 1-l (Table 1) when compared to the entire data set.
The decrease in sensitivity of 7 to C changes as X1 increases is in agreement with previously reported differences between algorithms for case 1 and case 2 waters (Mitchelson et al., 1986). Present results though, suggest the physically more reasonable notion of a continuous algorithm with an exponent which is a function of Z-,.
In all our regressions for C on y we find residual standard deviations of c. 0.26 + 0.06 in log,,C. When determining subsurface reflectance an attempt was made to minimize exper- imental errors by restricting measurements to sea states of 5 or less, so reducing variability in irradiance signals from surface waves, and avoiding times within 2 h of dawn and dusk when light levels are low and the upwelling irradiance may be close to noise level which leads to noisy reflectance signals. With these precautions it seems likely that the combined uncertainties account for only a small percentage of the observed residual scatter.
A probable explanation of some of the scatter is provided by Tett and Grantham (1980) who took a series of samples of C at the same station and found a standard deviation in log& of up to 0.2 which would account for a good proportion of our observed variance. This is in accord with the variations about the mean values of triplicate samples collected for each of our measurements of C.
Gordon and Morel (1983) collated work from a number of authors who indicated that the ratio R(520 nm)/R(550 nm) is correlated with C, also noted by Mitchelson (1986). In general the dependence is weaker than that given in equation (1) and a markedly greater slope suggests lower sensitivity to varying C concentrations. A similar regression for the data compiled in this study fails to provide a significant relationship, with r3 = 0.15 (n = 206). Further, we were unable to identify subsets of the data by location, season or L, concentration which could yield significant relationships.
Seston algorithm
While pigments, which act primarily as light absorbers, are the principal control on the spectral distribution of upwelling light, its intensity is related to the concentration of inorganic particles which are the principal scatterers. In a previous study we have looked for a relationship between R(550 nm) and the concentration and shown that the slope of the relationship is strongly influenced by C0 levels (Simpson &Brown, 1987). The data set has been extended and the analysis is presented in Figure 4 to illustrate this effect. Each plotted point represents the results of a regression analysis of the form, total seston ,Z = mR(550 nm), for a range of C, values, in which the regression line is constrained to pass through the origin. This is justified by the low inherent reflectance of pure seawater, which on the basis of the data given by Morel and Prieur (1977) is less than 0.5”,, .
There is an almost linear increase in m with increasing C,, which means that the efficiency of reflection is reduced by increased absorption associated with organic seston. For 2; > 1 .O mg 1-l the change in m can be described by
m = - 1.046Z:, + 0.094 (r2 = 0.93, n = 5) (4)
but there is an appreciable curvature in the relationship as Z tends to zero. This region, where L’, has little influence on the reflection, can be accounted for by the curve
m = - (c; + I)“505 -t 0.7 (r’ = 0.98, n = 10). ‘5)
Radiometric determination of pigment and seston 7
Figure 4. Variation of m = dL/dR(550 nm)“, with organic seston (L:,), the latter as median values in each range (I) over 1-O < Z0 < IO.0 mg l- I. Changes in m are best described by the linear regression when ZO> I.0 mg 1 I, but to account for the region where the efficiency of reflection varies little with 2, (see insert) the relationship is best described by the more complicated polynomial. Vertical error bars represent standard errors, with the number of points and coefficient of determination (r’) given by the upper and lower bracketed numbers, respectively.
Discussion
Our results point to the possibility of improving the prediction of total pigment from spectral reflectance data by allowing the algorithm exponent to vary continuously with seston content
where a, and b, are the intercept and slope, respectively, for each Xi range. Such an approach is perhaps preferable from a fundamental standpoint to the artificial dis- continuity implied in the separation of case 1 and case 2 waters. On the other hand the practical application of a continuous algorithm to remote sensing data would require good estimates of seston content.
In order to obtain Zi from reflectance data, our seston algorithm results indicate that it is necessary to know at least the approximate level of organic seston, EO, which appears to control the efficiency of reflection by the inorganic suspensions, independently of in situ characteristics.
As far as we can determine, C, exhibits no consistent correlation with surface reflec- tances. Nor is it possible to obtain a relationship between C and X, as the latter comprises greatly varying quantities of organic waste derived from land runoff and decaying and resuspended biota. Even in the areas of the Scottish Shelf and Western Irish Sea, where C, levels are typically < 1.0 mg 1-l (case l), a regression of C against .ZO yields r2=0.072 (n = 18) and 0.004 (n = 27), respectively. Levels of yellow substance, with values of the order 4-10 milli-fluorescence units (mFl), had no effect on algorithms.
Further, it is not always feasible to use past experience to estimate specific C, or .& values in particular areas. This is particularly so on the U.K. shelf where the concentration
8 J. Brown &J. H. Simpson
sEP :“._a,;,‘,,~~
0 20 0 IO 20 0 IO 20
C, (mg km’) Z. (mg r’i C(mg rnm3)
Figure 5. Monthly distributions of Za, X,, and C for the data collected in the areas indicated in Figure 1. Evidently 1 month cannot be characterized by a unique concentration in any parameter.
of resuspended material is dependent in shallow water on wind and more generally the phase of the tide and is not wholly seasonal (Weeks & Simpson, 1990). Examination of distributions of Ci, C, and C concentrations on a monthly basis (Figure 5) reveals that Ci and C, tend to be greatest in March and September, but comparable conditions may occur in other months with no period when levels of either parameter can be regarded as negligible. Similarly it is not usually valid to assume that any one month can be character- ized by consistently high or low levels of C. Levels of C may be significantly lower in winter, but considerable detrital organic material would still be present.
In spite of the clear limitations inherent in the seston dependence of the pigment algorithm, our results do confirm that the pigment algorithm (ignoring seston effects) provides estimates of C with a standard deviation of N 0.3 in log,,C. It should be remem- bered, however, that we are dealing with sea-level irradiance data, and that when we come to the interpretation of satellite and aircraft scanner data further uncertainties result from the inexactitude of the atmospheric correction. This complication would be avoided in algorithm applications to data from subsurface radiometers attached to moorings. Measurements with such systems could offer a useful technique for monitoring pigment variability on time scales from a day to years, information which is much needed and complements the spatial distributions obtained from remote sensing.
- Radiometric determination of pigment and seston 9
Acknowledgements
The authors thank all those who participated in the many cruises required to enable us to acquire such a considerable data set, particularly Dr E. G. Mitchelson who was respon- sible for much of the initial work. This study was funded under a N.E.R.C. special topic grant GST/02/122.
References
Brown, R. G. B. 1980 Sea birds as marine animals. In Behaviour of Marine Animals, Vol4., Marine Birds (Burger, J., Olla, B. L. &Wit-m, H. E., eds). Plenum Press, New York. pp. l-39.
Floodgate, G. D., Fogg, E., Jones, D. A., Lochte, K. & Turley, C. M. 1981 Microbiological and zooplankton activity at a front in Liverpool Bay. Nature, London 290, 130-136.
Gordon, H. G., Clark, D. K., Brown, J. W., Brown, 0. B., Evans, R. H. & Broenkow, W. W. 1983 Phyto- plankton pigment concentrations in the Middle Atlantic Bight: comparison of ship determinations and CZCS estimates. Applied Optics 22,20-36.
Gordon, H. G., Clark, D. K., Mueller, J. L. & Hovis, W. A. 1980 Phytoplankton pigments from the Nimbus- 7 Coastal Zone Colour Scanner: comparisons with surface measurements. Science 210,63-66.
Gordon, H. G. & Morel, A. Y. 1983 Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. Lecture Notes on Estuarine Studies. Springer-Verlag, Berlin. 114 pp.
Haynes, R. & Barton, E. D. 1990 A poleward flow along the Atlantic coast of the Iberian Peninsula.Journaloj Geophysical Research 95,11425-l 1442.
Hoppe, H. G. 1984 Attachment of bacteria: advantages or disadvantage for survival in the aquatic environ- ment. In Microbial Adhesiott and Aggregation (Marshall, K. C., ed.). Springer-Verlag, New York. pp. 283-303.
Mitchelson, E. G. 1986 Etudes des proprietes optiques de l’eau de mer. Rapport de Laboratoire de Physique et Chimie Marines. Villefranche-sur-mer (unpublished data report).
Mitchelson, E. G., Jacob, N. J. & Simpson, J. H. 1986 Ocean colour algorithms from the case 2 waters of the Irish Sea in comparison to algorithms from case 1 waters. Continental Shelf Research 5,403-415.
Morel, A. Y. 1980 In-water and remote measurements of ocean colour. Boundary Layer Meteorology 18, 177-201.
Morel, A. Y. & Prieur, L. 1977 Analysis of variations in ocean colour. Limnology and Oceanography 22, 709-722.
Simpson, J. H. & Brown, J. 1987 The interpretation of visible band imagery of turbid shallow seas in terms of the distribution of suspended particulates. Continental Shelf Research 7,1301-1305.
Tett, P. B. & Grantham, B. 1980 Variability in sea-loch phytoplankton. In Fjord Oceanography (Freeland, H. J., Farmer, D. M. & Levings, C. D., eds). Plenum Press, New York. pp. 435-438.
Topliss, B. J, 1986 Spectral variations in upwelling radiant intensity in turbid coastal waters. Estuarine, Coastal and Shelf Science 22,395-414.
Weeks, A. & Simpson, J. H. 1990 The measurement of suspended particulate concentrations from remotely sensed data. InternationalJournal of Remote Sensing (in press).
