Chlorophyll a (Chl-a) Concentration Measurement and Prediction in Taihu Lake Based on MODIS Image Data

Comparing with the chlorophyll-a (Chl-a) concentration measurement in ocean, the measurement of the inland water body based on MODIS image data is far from mature. The inland lake meets a series of more harsh pollution problems yet lack of any efficient methods in fast measurement and prediction. Therefore, the measurement and prediction upon the in-land water body pollution and eutrophication became critical. Taihu Lake is one of the largest freshwater inland lakes in China, which is also the most important water source. The eutrophication in Taihu Lake is becoming more serious while the economy of Taihu lake drainage basin developing. In summer 2007, the algae bloom brake out widespread in Taihu lake. A method of Chl-a concentration measurement and prediction, base on the MODIS image data, is presented in this paper. Two components were included in the method. The first component is estimation of Chl-a concentration based on MODIS image. The DN values were derived from MODIS image data, and translated into normalized reflectance. An image-based atmosphere correction method was applied in preprocess of MODIS image data to reduce the atmospheric effect, including calculating and removing Rayleigh scattering, and removing aerosol contribution at desired wavelength, etc. Based on studying the spectral characteristic of Chl-a, the suitable MODIS bands and band combinations were correlated with Chl-a measurement. The Chl-a concentration were based on Chlorophyll Empirical Algorithm and remote sensing reflectance (Rrs). Field data were used to correct the rough Chl-a concentration data. Secondly, the eco-dynamic model in Taihu Lake was developed. Two sub-modules were included in the eco-dynamic model: the hydrodynamic model and the ecological model in lake. The eco-dynamic model had been calibrated and tested by field measured data. The hydrodynamic model was used to simulate the flow field drove by wind. The distribution of Chl-a concentration in the future could be predicted by the ecological model. Two dates of MODIS data of May 8 and May 19, 2007 in Taihu Lake, China, were used in this study. The results show that, the most serious eutrophication state occurs in the north of Taihu Lake, and the eutrophication state in the east part of the lake is better than other region, which agree well with the local measured data. The result of numerical simulations provided satisfactory result in comparison with the distribution of Chl-a concentration based on MODIS. This approach could be applied to other coastal or inland regions for the measurement and prediction of Chl-a concentration, but the specific relationship between MODIS reflectance and Chl-a may vary as a consequence of different water body. The presence of other constituents can also be investigated in the further research.