Towards a hydrodynamic and optical modeling system with remote sensing feedback
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Towards a Hydrodynamic and Optical Modeling System with Remote Sensing Feedback. Yan Li Dr. Anthony Vodacek Digital Imaging and Remote Sensing Laboratory Center for Imaging Science Rochester Institute of Technology April 5, 2006. Objective Methods Modeling (ALGE and Hydrolight 4.1)

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Towards a hydrodynamic and optical modeling system with remote sensing feedback

Towards a Hydrodynamic and Optical Modeling System with Remote Sensing Feedback

Yan Li

Dr. Anthony Vodacek

Digital Imaging and Remote Sensing Laboratory

Center for Imaging Science

Rochester Institute of Technology

April 5, 2006


Outline

Objective Remote Sensing Feedback

Methods

Modeling (ALGE and Hydrolight 4.1)

Remote sensing feedback

Experimental Design & Data

Results

Summary

Outline


Objective
Objective Remote Sensing Feedback

  • High resolution plume simulations at the mouth of Niagara River and Genesee River to study the transport and the 3D distribution of CDOM and suspended sediments

  • Spectral remote-sensing reflectance at various locations in the mouth of Genesee River was calculated

  • Simulated remote-sensing reflectance compared to remote imagery to provide a feedback mechanism to the hydrodynamic model


ALGE Remote Sensing Feedback

ALGE

  • 3D finite differencing hydrodynamic model solving momentum, mass and energy conservation equations

  • Realistic predictions of movement and dissipation of plumes, sediments, and passive tracers discharged into lakes

  • High resolution simulations for node-to-node matching with satellite thermal imagery or airborne imagery

Model output

Spatial data

Satellite image

  • Geo-referenced site specific

    • Bathymetry

    • Weather data

    • Inflow and outflow


Basic Hydrolight World Remote Sensing Feedback

solar and

atmospheric

radiance

air/water interface

CHL

TSS

CDOM

bottom reflectance


Hydrolight Remote Sensing Feedback

  • Radiative transfer numerical model

  • Input

    • IOPs (absorption and scattering coefficients, scattering phase function)

    • state of the wind-blown air/water interface (wind speed)

    • sky spectral radiance distribution (built-in model/MODTRAN)

    • nature of the bottom boundary

  • AOPs (remote sensing reflectance Rrs)

Lw: water leaving radiance

Ed: evaluated just above the water surface


Physical Forcing Remote Sensing Feedback

Inputs

ALGE

3D Distribution of

CDOM and TSS

Remote Imagery

(Plume)

Algal Growth

Model

Hydrolight 4.1

IOPs (a, b, bb)

Spectral Rrs

or Radiance

Remote Imagery

or Lab Analysis


Study Area – Niagara River and Genesee River Remote Sensing Feedback

Genesee River

Niagara River


Plume simulation forcing factors
Plume Simulation Forcing Factors Remote Sensing Feedback

  • Meteorological data was from Buffalo weather station

  • Discharge flow rate was from US Army Corp. of Eng. Detroit District

  • The high resolution, limited area simulations of the plume were nudged from large scale whole lake simulation

  • TSS modeled as particles and CDOM modeled as passive tracers


a(760 nm) = 2.55 (where water absorbs maximally) Remote Sensing Feedback

a(430 nm) = 0.0144 (where water absorbs minimally)

Absorption of red light is 177 times stronger than absorption of blue light

Absorption coefficients: Pope and Fry (1997)

Scattering coefficients: Smith and Baker (1981)


DIRS capabilities Remote Sensing Feedback

for field sampling

and in-water

measurements

(Dr. Tony Vodacek)

HydroRad-4 spectroradiometer

HydroScat-2 backscatter meter

normalized to a(350)=1.0

CDOM no scattering


Assuming chlorophyll scattering goes to zero soon after 700 nm

Chlorophyll has maximal absorption coefficients at 430 and 670 nm


Maximal absorption occurs at the lowest wavelengths (~ 350 nm)

Absorption falls off rapidly as wavelength increasing

Absorption is negligible beyond 500 nm

Specific absorption and scattering coefficients are determined by Dr. Vodacek from the May 20, 1999 Lake Ontario water samples


Genesee River Plume nm)

LANDSAT-7 visible image showing the Genesee River plume on June, 14 2004 (spatial resolution 30 m)


Genesee River Plume nm)

MODIS calibrated and geo-located radiance (L1B) image showing the Genesee River plume on June, 15 2004 (spatial resolution 250 m)

Blue circle: plume water

Green circle: lake water


visible nm)

thermal

Modular Imaging Spectrometer Instrument

(MISI)

Lake Ontario

plume

  • Airborne line scanner

  • 70 VNIR channels

  • 5 thermal channels

  • nominal 2 milliradian FOV (20ft GSD at 10,000ft)

  • sharpening bands in VIS and LWIR

  • LWIR thermal band detecting the upwelling track caused by boat traffic

  • Plume traveling northward because of calm wind conditions on June 7, 2004

  • Westward track of the plume shown in MODIS image due to prevailing wind from the east


Niagara River Plume shown by simulated surface flow currents and passive tracer

Murthy, C.R., and K.C. Miners. 1989. Mixing characteristics of the Niagara River plume in Lake Ontario. Water Pollution Research Journal of Canada 24(1):143-162.


Simulated Genesee River Plume and passive tracer

Suspended sediment concentration profile from ALGE (g/m^3)

plume water


CHL profile (Chl0 = 4.2, Zmax = 100, h = 7.5, = 3.0) and passive tracer

CDOM absorption as an exponential function of both wavelength and depth

Genesee River Plume


Water Quality Conditions and passive tracer

  • Concentrations (Hydrolight variables)

  • estimated from laboratory analysis on water samples


Lake Ontario and passive tracer

Optical Identification of the Plume

compare Rrs

Genesee River Plume

The shaded bars at the bottom show the nominal

SeaWiFs sensor bands


Summary
Summary and passive tracer

  • High resolution hydrodynamic simulations showing the spread of plumes

  • Simulated vertical profile of suspended sediment from ALGE

  • Spectral Rrs simulated from lab analysis showing the optical identification of plume

  • Study of remote satellite/airborne imagery (LANDSAT-7, MODIS, MISI)

Future work

  • Modify ALGE to be spectral on shortwave range (CDOM)

  • More optical property data for Niagara River Plume

  • Retrieve more spectral information from remote satellite/airborne imagery (LANDSAT-7, MODIS, MISI)


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