water quality and optical property characterizations for china’s lake taihu

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010

Image:

MODIS Land Group,

NASA GSFC

March 2000

Presented byMenghua Wang

Water Quality and Optical Property Characterizations for China’s Lake

Taihu

2 Center for Satellite Applications and Research (STAR) Review

09 – 11 March 2010

Requirement, Science, and BenefitRequirement/Objective• Weather and Water

– Serve society’s needs for weather and water information• Better, quicker, and more valuable weather and water information to support improved decisions• Increase lead time and accuracy for weather and water warnings and forecasts• Improve predictability of the onset, duration, and impact of hazardous and high-impact severe

weather and water events• Increase coordination of weather and water information and services with integration of local,

regional, and global observation systems

• Ecosystems– Protect, restore and manage the use of coastal and ocean resources through ecosystem-

based management• Healthy and productive coastal and marine ecosystems that benefit society• A well informed public that acts as a steward of coastal and marine ecosystems

Science• How to provide accurate water optical, biological, and biogeochemical property data in

coastal and inland regions from satellite measurements?

Benefit• Improve water resources forecasting capabilities• Protect and monitor water resources• Understand the effect of environmental factors on human health and well-being


09 – 11 March 2010

Challenges and Path Forward• Science Challenges

– Accurate remote sensing of the water properties is still challenges for: (a) complex coastal and inland waters and (b) for absorbing aerosols.

• Next Steps– Continue efforts for improving the remote sensing data

products for coastal and inland waters.– Demonstrate various applications for using the improve data

products.• Transition Path

– We will implement research results into NOAA operational data processing, e.g., the NOAA SWIR project, which will be operation in this year.


09 – 11 March 2010

Improved Water Optical Property Data in Coastal and Inland Regions

SWIR-based Atmospheric Correction Algorithm: the shortwave infrared (SWIR) atmospheric correction algorithm has been developed and demonstrated to provide improved ocean color products in coastal and inland waters.

Inland Lake Taihu: contains consistently highly turbid waters, and the derivation of MODIS lake property data requires using the SWIR method, due to significant water-leaving radiance contributions at the near-infrared (NIR) bands.

Standard Satellite Ocean Color Data Processing: often fails to produce any valid products in very turbid waters, e.g., in Lake Taihu, due to an incorrect assumption and/or computation of the NIR water contributions.

Quantitative Characterization of Aquatic Optical and Biological Property: for Lake Taihu is demonstrated using the SWIR-based algorithm from MODIS-Aqua measurements.

Research Results Demonstrate: an application of satellite-derived imagery for inland water quality monitoring, assessment, and management.


09 – 11 March 2010

SWIR-based Ocean Color Products for Various Applications

Coastal Phytoplankton Bloom Study: Observations of Hurricane Katrina-induced phytoplankton bloom in the Gulf of Mexico (Shi and Wang, 2007; Liu et al., 2009).

Ecosystem Responses to Major Weather Event: Three-dimension observations from MODIS and CALIPSO for ocean responses to Cyclone Nargis in the Gulf of Martaban (Shi and Wang, 2008).

River Estuary, River Dynamics and River Plume: Satellite observations of flood-driven Mississippi River plume in the spring 2008 (Shi and Wang, 2009).

Stormwater Plume Detection: Stormwater plume detection in the southern California coastal ocean (Nezline et al., 2008).

Coastal and Inland-water Hazard Monitoring: Satellite-observed blue-green algae blooms in China’s Lake Taihu (Wang and Shi, 2008).

Environmental Responses to a Land Reclamation Project: Satellite-observed drastic changes in marine environment in response to the Saemangeum Reclamation Project in South Korea (Son and Wang, 2009).

Monitoring Green Macroalgae Blooms in Yellow Sea: Satellite observation and monitoring of green macroalgae blooms in the Yellow Sea during the spring and summer of 2008 (Shi and Wang, 2009).


09 – 11 March 2010

Blue-Green Algae Bloom Crisis in Lake Taihu (Spring 2007)


09 – 11 March 2010

0.1

1

March 21 April 10 April 30 May 20 June 9

Chl

orop

hyll-

a (m

g m

-3)

nLw() (m

W/cm

2 m sr)

50

8

3

10

Normalized Water-leaving Radiance at 443 nm

Chlorophyll-a

Date (2007)

Bloom Location

Central Lake

The work was featured in the NASA 2008 Sensing Our Planet (http://nasadaacs.eos.nasa.gov/articles/2008/2008_algae.html)

Satellite (MODIS) Observed Blue-Green Algae (Microcystis) Bloom

MODIS Images: True Color, Chlorophyll-a,

and Radiance

Quantitative Measurements


09 – 11 March 2010

Diffuse Attenuation Coefficient Kd(490):Water Turbidity and Water Quality


09 – 11 March 2010

Radiance nLw(443): Algae Absorption


09 – 11 March 2010

Radiance nLw(645): Sediment Amount


09 – 11 March 2010

Significant NIR radiance nLw(859) contributions in Lake Taihu


09 – 11 March 2010

Validation Results for MODIS-derived Water-leaving Radiance Spectra

10-1

100

101

400 500 600 700 800 900

In Situ DataMODIS-Aqua

nLw

() (

mW

cm

-2

m-1

sr-1

)

Wavelength (nm)

Lake Taihu in China, June 10, 2007 (a)

Location: (120.20oE, 31.43oN)

10-1

100

101

400 500 600 700 800 900


nLw

() (

mW

cm

-2

m-1

sr-1

)

Wavelength (nm)

Lake Taihu in China, June 12, 2007


(b)

10-1

100

101

400 500 600 700 800 900


nLw

() (

mW

cm

-2

m-1

sr-1

)

Wavelength (nm)



(c)

10-1

100

101

400 500 600 700 800 900


nLw

() (

mW

cm

-2

m-1

sr-1

)

Wavelength (nm)



(d)


09 – 11 March 2010

Challenges and Path Forward• Science Challenges

– Accurate remote sensing of the water properties is still challenges for: (a) complex coastal and inland waters and (b) for absorbing aerosols.

• Next Steps– Continue efforts for improving the remote sensing data

products for coastal and inland waters.– Demonstrate various applications for using the improve data

products.• Transition Path

– We will implement research results into NOAA operational data processing, e.g., the NOAA SWIR project, which will be operation in this year.

water quality and optical property characterizations for china’s lake taihu

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