1. Monitoring Water Chlorophyll-a Concentration (Chl-a) in Lake Dianchi,China from 2003 ~ 2009 by MERIS Data

2. Lake Dianchi Location: 24°50΄N, 102°41΄E Surface Area : 300 km2
Depth: mean depth- 4.3 m
maximum depth m
Type: Fresh
State: the lake close to the urban area of Kunming City, the capital of Yunnan Province, suffering from increasing eutrophication due to the large amount of industrial wastewater and municipal sewage discharges. This leads to the frequent occurrence of algal blooms from April to November each year.
Lake Dianchi is located in a plateau area of southwestern.
Because it is close to the urban area of Kunming City, the capital of Yunnan Province, the lake is suffering from increasing eutrophication due to the large amount of industrial wastewater and municipal sewage discharges.
Fig. Lake Dianchi basin
(Jin Xiangcan et al)

3. Objectives
To evaluate the performance of popular Chl-a concentrations retrieval models using the datasets collected from Lake Dianchi (China)
To uncover the recent spatial/temporal change trends of Chl-a concentrations in Lake Dianchi using the optimized model and MERIS data from 2003~ 2009

4. Atmospheric correction
Methodology
Atmospheric correction
Geometric correction
Field survey
Reflectance
Chl-a
In situ data
Model calibration
MERIS images
Reflectance images
Model validation
Lake Dianchi
Chl-a maps

5. MERIS Data Description
57 scenes of MERIS 1-b products：
Top Of Atmosphere (TOA) radiance
auxiliary data :
Location: longitude, latitude
Sun-zenith/azimuth (View)
DEM、Wind、Ozone、Humidity…
2003~2009:
2003/11~2004/03、2004/11~2005/05
2005/11~2006/04、2007/01~2008/05
2008/11~2009/03
2007 each month
Other years : 11\12\01\02\03 month

6. Model description (1) Fluorescence Line Height (FLH ) Model:
Where FHL is height at nm above the base line between and nm. The corresponding MERIS waveband number are 8 (681 nm), 9 (708 nm), and 10 (753 nm).
(2)Two_band Model :
where is the above-water remote sensing reflectance at the waveband centered at x nm, the corresponding MERIS waveband numbers are 7 (665 nm), 9 (708 nm).

7. Model description (3)Three_band Model:
where is the above-water remote sensing reflectance, at the waveband centered at x nm, the corresponding MERIS waveband numbers are 7 (665 nm), 9 (708 nm) and 10(753nm), and , are the absorption coefficients for phytoplankton and pure water, respectively.
The first band λ1 should be maximally sensitive to phytoplankton absorption (a_Chla), the second band λ2 minimizes the effect of suspended solids absorption (a_d(λ)), dissolved matter absorption (a_CDOM(λ)) and pure water absorption (a_w(λ)). The
effect of backscattering (bb) by all particulate matter is minimized by the third band λ3. This semi-analytical algorithm involves three assumptions: 1) the absorption by suspended solids and CDOM at λ2 is close to that at λ1; 2) reflectance at λ3 is minimally affected by the absorption of water constituents and can only account for the variability in scattering between samples; and 3) the total backscattering coefficient of the three bands is approximately equal.

8. Methodology: Model calibration
RMSE= mg m-3 b
Fig. Calibration of (a) the FLH , (b) the two-band and (c) the three_band models

9. Model calibration
The three_band model was more accurate performance than other two models.
The three_band model can be described as:

10. Model validation
The accuracy of the Chl_a prediction was assessed by RMSE, MNB and NRMS.
Where N is the number of samples is the predicted Chl-a value and is the analytically measured Chl-a value, and

11. Model validation
1:1 line
RMSE= mg m-3
MNB=-24.12%
NRMS=22.46%
Fig. Validation of the MERIS three_band model: Relationships between the chl-a concentrations measured in situ and estimated

12. Results
Comparison of Chl-a measured in situ and estimated by MERIS data:
(2006/04/03) (Lu et al, 2009)
(2006/04)
RMSE= mg · m-3
MNB= 10.79%
NRMS= %

13. Results- Chl-a monthly variation
2007/01, 02, 03, 04, 06, 09, 10, 11, 12
average
Month average Chl-a is in the range of 13.7 to mg ·m-3;
Chl-a monthly variation: lowest---rising----rising----declining
02~03 ( lowest, averaging mg ·m-3);
04~06 (increasing, averaging mg ·m-3);
09~11 (highest, averaging mg ·m-3 );
12~01 (decreasing, averaging mg ·m-3 ).

14. Results- Chl-a annual variation
11 (November), 2003~2009
November Chl-a is in the range of 30.0 to mg ·m-3;
Chl-a annual variation: declining—lowest----rising
2005 (lowest, averaging 30.0 mg ·m-3) ;
2007 (highest, averaging mg ·m-3 ).

15. Results- Chl-a annual variation
12 (December), 2003~2009
December Chl-a is in the range of 20.0 to 80.3 mg ·m-3;
Chl-a annual variation: declining—lowest----rising
2004 (lowest, averaging 20.0 mg ·m-3);
2007 (highest, averaging 80.0 mg ·m-3 ). .

16. Results- Chl-a annual variation
01 (January), 2003~2009
January Chl-a is in the range of 14.9 to 74.3 mg ·m-3;
Chl-a annual variation: rising slowly
2004 (averaging mg ·m-3);
2007 (highest, averaging 80.0 mg ·m-3 ).

17. Results- Chl-a annual variation
02 (February), 2003~2009
February Chl-a is in the range of 9.56 to mg ·m-3;
Chl-a annual variation: stabilized
2006 (slightly higher);
others (stable around 20.0 mg ·m-3 ).

18. Results- Chl-a annual variation
03 (March), 2003~2009
March Chl-a is in the range of to mg ·m-3;
Chl-a annual variation: stabilized
2005 (slightly higher);
others (stable around 20.1 mg ·m-3 ).

19. Results- Chl-a annual variation
04 (April), 2003~2009
April Chl-a is in the range of to mg ·m-3;
Chl-a annual variation: declining slowly
2006 (highest);
others (fluctuating around 38.0 mg ·m-3 ).

20. Results- Chl-a annual variation
Chl-a concentrations is increasing slowly from 2003~2009 (2007: highest);
Chl-a concentrations is stabilized when its value < 35mg ·m-3 (February , March, April);
Chl-a concentrations annual variation is very obvious when its value is higher than 35mg ·m-3 (November, December, January).

21. Results- Chl-a spatial variation
Chl-a concentrations is increasing from the south to the north of Lake Dianchi;
Chl-a concentrations is higher in the edge of Lake Dianchi, especially that closing to the cities and towns;
Chl-a concentrations spatial variation is more obvious when Chl-a concentrations is higher (from April to November).

22. Conclusion
1. The three-band model based on MERIS band 7,9,10 was proposed to estimate Chl-a concentrations in Lake Dianchi. The results showed that the accuracy was improved compared with the FLH model and two-band model.
2. Chl-a concentrations temporal and spatial variations can be mapped out by a time-series of MERIS products. The case of Lake Dianchi showed that it is entirely possible to use the MERIS products to estimate Chl-a concentrations change trends in turbid productive waters.
3. In Lake Dianchi, Chl-a concentrations showed a uptrend from 2003~2009. It also implied obvious monthly variations. Each year from April to November, Chl-a concentrations rised quickly , which illustrated the algal blooms in that period. In the spatial distribution, Chl-a concentrations is higher at the edge and the north of lake, which are close to the cities and towns.
4. Further research is required to explore better atmospheric correction methods and algorithms for the retrieval of Chl-a concentrations from MERIS imagery.