The distinctiveness of this dominant wavelength is termed “color purity” and
is defined in Fig. 17.1 as the ratio of the line Q-S to the line A-S. Thus, spectral purity
is a measure of the magnitude of the contribution of the dominant monochromatic
spectrum at the dominant wavelength l dom , while a spectral purity p of 0 indicates a
“white” spectrum. Together, the dominant wavelength l dom , and its associated spectral purity p are considered herein as defining aquatic color.
Since the upwelling radiance L u (þ0,l) is controlled by the CPA optical influence
(transduced through R(À0,l), see Practice 15), any changes in chlorophyll,
suspended minerals and dissolved organic carbon are bound to result in changes
of the water column color. In the case of significant horizontal heterogeneity of the
hydro-optical field structure of the target water body, the color must also display a
distinct patchy pattern. Such a phenomenon is characteristic of many lakes and
water storage reservoirs, as well as marine coastal zones. It can be easily detected
on space imageries in the visible spectrum.
Focused on studying the formation of radiometric characteristics of natural
water, this teaching lab is confined to a simplified numerical modeling experiment
when chlorophyll and dissolved organic carbon fluorescence impacts are neglected.
A complete solution of this problem can be found elsewhere.
17.2 Practice 16
17.2.1 Objective
To investigate the dependence of the dominant wavelength and color purity on the
CPA (chlorophyll, suspended minerals and dissolved organic carbon) concentration
vector given the incident radiation spectral distribution.
17.2.2 Software and Set of Input Parameters
1. Code “color” in “Paskalv.7.0” (TP7) and files with the input data stored in the
folder « c:\Dis_liq ».
2. Text editor « Word», packages Exel», «Surfer » and « TableCurve ».
3. A set of input parameters provided by the Practice chief/supervisor. (Table 17.1)
17.2.3 Sequential Steps of the Exercise Implementation
1. Read attentively the section devoted to the physical/theoretical background of
this exercise. If necessary, consult the referenced literature.
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17 Simulations and Analyses of Variations in Colorimetric Properties
is defined in Fig. 17.1 as the ratio of the line Q-S to the line A-S. Thus, spectral purity
is a measure of the magnitude of the contribution of the dominant monochromatic
spectrum at the dominant wavelength l dom , while a spectral purity p of 0 indicates a
“white” spectrum. Together, the dominant wavelength l dom , and its associated spectral purity p are considered herein as defining aquatic color.
Since the upwelling radiance L u (þ0,l) is controlled by the CPA optical influence
(transduced through R(À0,l), see Practice 15), any changes in chlorophyll,
suspended minerals and dissolved organic carbon are bound to result in changes
of the water column color. In the case of significant horizontal heterogeneity of the
hydro-optical field structure of the target water body, the color must also display a
distinct patchy pattern. Such a phenomenon is characteristic of many lakes and
water storage reservoirs, as well as marine coastal zones. It can be easily detected
on space imageries in the visible spectrum.
Focused on studying the formation of radiometric characteristics of natural
water, this teaching lab is confined to a simplified numerical modeling experiment
when chlorophyll and dissolved organic carbon fluorescence impacts are neglected.
A complete solution of this problem can be found elsewhere.
17.2 Practice 16
17.2.1 Objective
To investigate the dependence of the dominant wavelength and color purity on the
CPA (chlorophyll, suspended minerals and dissolved organic carbon) concentration
vector given the incident radiation spectral distribution.
17.2.2 Software and Set of Input Parameters
1. Code “color” in “Paskalv.7.0” (TP7) and files with the input data stored in the
folder « c:\Dis_liq ».
2. Text editor « Word», packages Exel», «Surfer » and « TableCurve ».
3. A set of input parameters provided by the Practice chief/supervisor. (Table 17.1)
17.2.3 Sequential Steps of the Exercise Implementation
1. Read attentively the section devoted to the physical/theoretical background of
this exercise. If necessary, consult the referenced literature.
172
17 Simulations and Analyses of Variations in Colorimetric Properties