Page updated: March 8, 2021
Author: Emmanuel Boss
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Classification Schemes

Taxonomies of Water Types

Classification of natural waters into optical water types, as with many other taxonomies, is done in order to generalize and systematize the science of ocean color. Arnone et al. (2004), in a review paper on water mass classification, credits the Secchi disk (invented around 1865) as the first quantitative optical instrument that has been used to measure water transparency and hence provided the ability to differentiate water mass based on their optical properties. Classification schemes that are based on water color are primarily based on absorption (as scattering contributes to intensity but less to color).

Classification Schemes of water types are based on

  • The human eye: visually compare the water color to the color of a standard color sample (Forel-Ule color scale)
  • Analysis of AOP spectra (Jerlov water types)
  • The relative importance of Chlorophyll in determining the optical properties of the water (Case 1 vs. Case 2)
  • Analysis of inherent optical properties (ternery diagrams)

Human-eye-based Classifications: The Forel-Ule Color Classification

The Forel-Ule Scale is a method to approximately determine the color of bodies of water. Different inorganic compounds with standard formulas are used to produce a color palette with twenty one fluid vials covering blue to green to brown. The analysis consists of finding the vial whose color best matches the color of the water body; the result is an index from 1 to 21. The method is often used in conjunction with the Secchi disk and is included in data bases such as (NOAA’s World Ocean Database. The method was developed in the 1890s by Francois-Alphonse Forel and William Ule. Although now replaced by instruments for quantitative work, the Forel-Ule color measurements are still of interest because of the ease of making measurements and the large database of historical observations, which has value for studies of long-term changes in ocean ecosystems (e.g., Wernand (2011)). There is now even a smart-phone app for making Forel-Ule measurements. Figure 1 shows the use of a Forel-Ule color scale to determine the color of the ocean by visually determining the closest match of the water color to one of the 21 Forel-Ule colors.


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Figure 1: Using a Forel-Ule color scale to determine the color of the ocean. Photo from ICBM Uni. Oldenburg.

Figure 2 shows the locations of the 21 Forel-Ule colors on a CIE chromaticity diagram. The open circle is the white point. The open diamond is the CIE color of the remote-sensing reflectance Rrs as calculated by HydroLight using the “new Case 1” IOP model with a chlorophyll concentration of 5mgm3. The closest Forel-Ule value is 6.


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Figure 2: The locations of the 21 Forel-Ule colors on a CIE chromaticity diagram (black squares). The open diamond is the color of Rrs as calculated by HydroLight for a chlorophyll concentration of 5mgm3.

Another comparative scale is the Hazen Platin-Cobalt-Scale adopted as the American Public Health Association (APHA) color scale (described in ASTM D1209,“Standard Test Method for Color of Clear Liquids (Platinum Cobalt Scale)”). It is based on diluting a standard stock solution (500ppm of PtCo) and finding the dilution whose color best matches the fluid compared.

Analysis of AOP Spectra: The Jerlov Classification

Jerlov (1968) introduced a classification of water bodies based on their spectral optical attenuation depth zk 1Kd. Since ocean color is proportional to 1a 1Kd these spectra are linked to the color observed. Jerlov discretized his observations into a set of five typical oceanic spectra and nine typical coastal spectra (e.g. Table XX in Jerlov (1968) which is linked here).


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Figure 3: Jerlov’s water mass clasification based on transmittance along 1 m of sea water. Based on data from Table XX in Jerlov (1968)

Solonenko and Mobley (2015) give tables relating the Jerlov water types to a consistent set of absorption and scattering coefficients (consistent in the sense that the IOPs, when used in HydroLight, generate Kd spectra that correspond to the different Jerlov water types).

Importance of Chlorophyll versus Other Components: Case 1 versus Case 2 Water Types

Morel and Prieur (1977) described the spectral shape of R = EuEd and its changes as separating two types of waters.

They found that “two extreme cases can be identified and separated. Case 1 is that of a concentration of phytoplankton high compared to other particles. In contrast, the inorganic particles are dominant in case 2. In both cases dissolved yellow substance is present in variable amounts. An ideal case 1 would be a pure culture of phytoplankton and an ideal case 2 a suspension of nonliving material with a zero concentration of pigments.”

Morel and Prieur emphasized that these ideal cases are not encountered in nature, and they suggested the use of high or low values of the ratio of pigment concentration to scattering coefficient as a basis for discriminating between Case 1 and Case 2 waters.

The definitions of Case1 and Case 2 have evolved over the years into the ones commonly used today (Gordon and Morel (1983), Morel (1988)):

  • Case 1 waters are those waters whose optical properties are determined primarily by phytoplankton and co-varying colored dissolved organic matter (CDOM) and detritus degradation products.
  • Case 2 waters are everything else, namely waters whose optical properties are significantly influenced by other constituents such as mineral particles, CDOM, or microbubbles, whose concentrations do not covary with the phytoplankton concentration.

In Case 1 waters, several changes occur as the pigment concentration increases:

1.
The R values in the blue-violet region decrease progressively and a minimum is formed around 440 nm, which corresponds to the maximum absorption of chlorophyll. The maximum shifts toward 565-570 nm, which is the wavelength where simultaneously the absorption due to pigments is at its minimum and the absorption due to the water itself rapidly increases.
2.
The second maximum of absorption by chlorophyll a in vivo creates an R minimum near 665 nm. This minimum is only slightly marked because the increase in absorption due to the presence of chlorophyll remains weak compared with the absorption due to water itself.
3.
At 685nm a second reflectance maximum appears due to fluorescence by chlorophyll superimposed on absorption/scattering interaction near the 676nm absorption band.
4.
A hinge point in R values in the 560-640-nm band is observed with relatively little change as chlorophyll varies.

In Case 2 waters inorganic particles are relatively more dominant than phytoplankton. As the turbidity increases the following modifications appear:

1.
The reflectance values are generally higher than for case 1 throughout the spectrum and of a different shape. There is no longer, as in Case 1, a minimum at 440 nm. On the contrary, the curves become convex between 400 and 560 nm (inverted ’U’ shape rather than inverted ’V’). The maximum is flatter than in case 1, but located at the same wavelength, 560 nm.
2.
R values become higher as turbidity increases. This is opposite of what was observed in Case 1, particularly for wavelengths above 550 nm.
3.
As a result of the flat shape of the R curves, the dominant wavelength does not shift beyond 510 nm. These waters are blue-green or green with a bright and milky appearance due to the combined effects of high irradiance values and of low purity values.

Although the Case 1 versus Case 2 distinction has proven very useful, it can also be misleading. It must be understood that natural waters are not simply either Case 1 or Case 2; there is a continuous gradation of water optical properties (whether IOPs or AOPs) and their dependence of chlorophyll and other water constituents. It must also be remembered that “Case 1” and “Case 2” are not synonyms for “open ocean” and “coastal” waters.

Mobley et al. (2004) have even suggested that it is perhaps time to drop this type of binary classification as it sometimes obfuscates more than it helps. For example, the same water can be Case 1 for absorption but Case 2 for scattering (e.g., if the water contains non-absorbing but highly scattering mineral particles), or it can be Case 2 for absorption and Case 1 for scattering (e.g., if the water contains a high concentration of highly absorbing terrigenous CDOM, which does not covary with the chlorophyll, and which does not affect the scattering). Of course, water in the same area may be Case 1 during some time of the year and Case 2 in other times. Waters with similar chlorophyll concentrations may have large variations in ocean color in open ocean environment (e.g. Eastern Mediterranean vs. South Pacific gyre).

Ternery Diagrams

Ternary diagrams are used to differentiate water masses optically by designating a point in a triangle based on the relative contribution of absorption by phytoplankton, non-algal particles, and CDOM to the total absorption (minus that of the salt water itself) at a specific wavelength. A point at the center of the triangle designate equal contribution by all, while each points at the apex designate water where all the contribution is from a single component. An example of a ternary diagram applied to absorption is given in Figure 16 of Babin et al. (2003b) at various wavelengths for European coastal waters. The diagram shows well how at different wavelengths different constituents (dissolved material, algae and non-algal particles) dominate absorption.

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