ADVANCED ALGORITHMS FOR REMOTE ESTIMATION OF WATER QUALITY

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ADVANCED ALGORITHMS FOR REMOTE ESTIMATION OF
WATER QUALITY

• Giorgio DallOlmo
• Center for Advanced Land Management Information
  Technologies,
• School of Natural Resource Sciences,
• UNL

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Objective

• To devise a technique for QUANTITATIVE REMOTE
  estimation of water quality

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Color of a water body

• Relates to the types and amounts of substances
  present in the water column that interact with
  light absorbing or scattering it.

We call them OPTICALLY ACTIVE CONSTITUENTS
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Absorption Spectral Properties of Optically
Active Constituents
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Examples of water colors
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Spectral Reflectance (1)

• The percentage of light reflected by a target

• Allows quantitatively measuring the color of
  water, minimizing the effect of different
  illumination conditions

Lup
Ed
Water body
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Spectral Reflectance (2)
Spectral reflectance is a quantitative measure of
absorption and scattering by optically active
constituents
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Examples of reflectance spectra
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Spectral Indices

• Transforms of reflectance values at different
  wavelengths that
• 1) maximally relate to the concentration of the
  constituent of interest, and
• 2) minimize the effects of other optically active
  constituents and survey conditions

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Proposed Chl-a Spectral Index
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Results Chl-a model development
Year 2001
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Results Chl-a model validation Year 2002
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Potentials

• Remote estimation by means of airborne (AISA) and
  satellite systems
• Smart Sampling (example)
• Early warning systems for toxic algal blooms
  (cyanobacteria, red tides)
• Data with high temporal and spatial resolution to
  study aquatic ecosystems

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Limitations

• Calibration
• Only surface layer (depending on water
  transparency)
• Weather conditions (for airborne or space borne
  sensors)

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On-going work

• Study the sensitivity of algorithms for
  chlorophyll-a estimation to dissolved organic
  matter and suspended matter concentration
• Development of algorithms for estimation of
• Secchi disk depth/Turbidity
• Dissolved Organic Matter
• Tripton
• Detection/quantification of different pigments
  (algal groups)
• Chlorophyll-b
• Phycocyanin
• Phycoerythrin
• Carotenoids

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Acknowledgements

• My supervisor
• Dr. A. Gitelson
• CALMIT team
• Dr. D. Rundquist
• R. Perk
• B. Leavitt
• J. Moon
• A. Viña

• WATER CENTER team
• Dr. K. Hoagland
• Dr. J. Holz
• T. Barrow
• Other collaborators

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Cat Fish Ponds, MS. August 2002
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