Remote Sensing Inversion Of Chlorophyll A In Typical Polluted Rivers Of Taihu Based On High Spatial Resolution Data

Chlorophyll a is one of the important water quality parameters and its concentration is the main indicator of water eutrophication. In this paper, we take western Taihu Lake and its typical polluted rivers as our study area. The in-situ measured data combined with RapidEye and ALOS data were firstly used to analyse apparent optical properties and inherent optical properties of water, and then a variety of remote sensing inversion models of chlorophyll a aimed at measured highperspectral data, RapidEye and ALOS data were developed and the accuracy, stability and applicability of different models were evaluated. On this basis, according to the pre-processing result of high spatial resolution data, the optimal inversion models of chlorophyll a were selected and applied to derive the distribution of chlorophyll a in western Taihu Lake and its typical polluted rivers. Thereas, the temporal and spatial variation of chlorophyll a was analyzed. The main conclusions of this study are as follows:(1) Remote sensing inversion models of chlorophyll aFor measured highperspectral data, the single-band model, the first derivative model, the band ratio model, the three-band model and the four-band model are all suitable for inversion of chlorophyll a in western Taihu Lake and its typical polluted rivers. In contrast, the band ratio model which takes Rrs(727)/Rrs(678) as independed variable, the three-band model and the four-band model have higher accuracy and stability.For simulated RapidEye data, the linear function of single-band model has poor accuracy and stability while the quadratic function of single-band model, the multi-band combination model and the three-band model have higher accuracy and stability and they are effective for the inversion of chlorophyll a in western Taihu Lake and its typical polluted rivers. In contrast, the quadratic function of three-band model has the highest accuracy and stability with the model’s R2is0.97, the average relative error is12.53%and the root mean square error is4.44μg/LFor simulated ALOS data, the linear functions of single-band model and the multi-band combination model have poor accuracy and stability while the quadratic function of all models are all effective for the inversion of chlorophyll a in western Taihu Lake and its typical polluted rivers. In contrast, the quadratic function which takes (B1+B3)/(B1+B2+B4) as independed variable has the highest accuracy and stability with the model’s R2is0.95, the average relative error is14.27%and the root mean square error is5.20μg/L.(2) The temporal and spatial variation of chlorophyll aFrom the view of temporal variation, the trend of chlorophyll a in western Taihu Lake and its typical polluted rivers in the whole year is as follows:summer> autumn> winter> spring. In summer, the temperature is higher and it is suitable for the growth of algal, so the concentration of chlorophyll a reaches the maximum of the whole year and there are large areas of cyanobacteria blooms. In autumn, the concentration of chlorophyll a decreases with the temperature falls while there still exists some cyanobacteria blooms. In winter and spring, the temperature is not suitable for the growth of algal, and there are no cyanobacteria blooms basically. And the concentration of chlorophyll a reaches the minimum of the whole year in spring because lots of algal dies after cold winter.From the view of spatial variation, the concentration of chlorophyll a in typical polluted rivers which flow into Taihu Lake is significantly higher than that in its surrounding lakes especially in winter and spring and the change scope of chlorophyll a in rivers is obviously less than that in its surrounding lakes. The concentration of chlorophyll a in waters which near the estuary is significantly lower than that in the center of rivers while the concentration of chlorophyll a in waters near the bank of rivers is higher than that in the center of rivers. And its trend is roughly as follows: water near the bank of rives>water in the center of rivers>water near the estuary.