SEDIMENT AND CHLOROPHYLL CONCENTRATIONS IN MAJOR CHINESE RIVERS USING MERIS IMAGERY

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SEDIMENT AND CHLOROPHYLL CONCENTRATIONS IN MAJOR CHINESE RIVERS USING MERIS IMAGERY P.J. Mulhearn (1) and Ian S. F. Jones (2) (1) Ocean Technology Group J05, University of Sydney, NSW 2006 Australia; phil.mulhearn@otg.usyd.edu.au (2) Ocean Technology Group J05, University of Sydney, NSW 2006 Australia; otg@otg.usyd.edu.au ABSTRACT In the course of an attempt to investigate sediment and chlorophyll levels in outflows of three major Chinese rivers, it has been found to be nearly impossible to obtain any valid data from MERIS imagery in the coastal zone. The problems were found to be due to either aerosol levels which were too high or to the presence of aerosols whose properties could not be matched to any of the aerosol models currently held in the MERIS database. These aerosols most likely arise from the large increases in aerosol loads which are occurring over China as it increasingly develops economically. 1. INTRODUCTION The growing affluence of the Chinese people and the resulting expansion of industrial activity has increased the amount of pollution produced. This pollution ends up in the rivers and in the atmosphere. Simultaneously dam building changes the river flow patterns. Will changes in sediment transport, such as induced by the Three Gorges dam, impact on the coastal ocean and its fishery? The primary production, as depicted by the phytoplankton abundance is expected to respond.. This project attempted to investigate the turbidity and chlorophyll levels in the outflows of three major Chinese rivers, using MERIS imagery. Earlier studies in the Great Barrier Reef lagoon found good correlation between MERIS results and ground truth, although MERIS tended to underestimate Total Suspended Solids (TSS) [1]. The three rivers were the Huanghe (Yellow River), the Changjiang (Yangtze River) and the Zhujiang (Pearl River). The satellite images have the potential to show large scale patterns of ocean parameters, as against in-situ measurements, which may be more accurate but which can not be used to obtain overall synoptic views. It was hoped to examine seasonal and interannual variations in turbidity and chlorophyll levels and the occurrences of algal blooms. Unfortunately no reliable images were obtained, despite examination of many images from a range of years and seasons. All water areas were flagged as Case 2 sediment dominated. The algorithm for Case 2, sediment dominated, bright pixel atmospheric correction [2] often failed to give valid results and in some cases provided negative normalized water leaving reflectances. Problems flagged were invalid aerosol alpha and aerosol thickness, ice or high aerosol load pixel, or aerosol model is out of aerosol model database. PCD_19 (uncertain aerosol type and optical thickness) was flagged over wide areas. (PCD = Product Confidence Data). Reference [3] found that aerosol optical depth increased dramatically over China from 1961 to 1990, particularly over the middle and lower reaches of the Changjiang and the eastern part of southwest China. No images were found in this study in which the majority of pixels gave valid results according to the MERIS algorithms in VISAT. The problems encountered are examined below for a number of very typical cases. Proc. Envisat Symposium 2007, Montreux, Switzerland 23 27 April 2007 (ESA SP-636, July 2007)

Mouth Figure 1. MERIS image, from 5 March 2005, of TSS in area near the Huanghe outflow, and TSS histogram showing the distribution in gm/m 3. 2. TYPICAL CASE STUDIES 2.1 Huanghe Outflow Region 5 March 2005 The Huanghe is one of China s largest rivers and meets the sea at Bohai Bay, south of Tianjin. The area of Bohai Bay north of the river s mouth is shown in Fig. 1, in which total suspended sediment (TSS) concentrations, computed from the MERIS data, of 5 March 2005, are shown. Strange features are the relatively low values (in blue) around the river mouth, and the higher TSS band (in yellow) off shore. This yellow colour corresponds to a TSS of 50 gm/m 3, which is the upper limit for calculating TSS from the MERIS sensor [4]. However the area flagged as having invalid reflectances extends offshore approximately twice as far as the yellow area. The low values very close to shore (in blue and white) are probably due to adjacency effects [5]. Fig. 2(a) shows, in black, the areas flagged as having invalid reflectances, while Fig. 2(b) shows, in black, the areas flagged as having invalid aerosol alpha and aerosol thickness. The background image in Figs. 2 (a) and (b) is the MERIS band 1 (wavelength of 412.691 nm) image of 5 March 2005, which is shown in Fig. 3 (a). In this last white areas are those with zero or near zero reflectance in band 1. The white areas close to the black in Fig. 2(b) are also areas of near zero reflectance in this band. In Fig. 3 (b) the pastel green areas within the white area are flagged as aerosol model is out of aerosol model database, i.e. the atmospheric aerosol in this area could not be matched with the aerosol models within the MERIS database. The invalid reflectances within this image appear to be due then to there being no model within the MERIS database able to match the aerosol type present in the scene. This is a common problem within the area of Figs. 1 to 3.

(a) (b) Figure 2. Invalid pixels, shown in black, near the Huanghe outflow on a MERIS band 1 image: (a) invalid reflectances; (b) invalid aerosol alpha and aerosol thickness. (a) (b) Figure 3. MERIS image near the Huanghe outflow on 5 March 2005(a) Band 1, (b) Band 1 image with pastel green overlay within white area indicating aerosol model is out of aerosol model database.

Changjiang mouth Hangzhou Bay Figure 4. MERIS image of TSS at the mouth of the Chanjiang and in Hangzhou Bay, and TSS histogram showing the distribution in gm/m 3, 17 October 2004. 2.2 Changjiang Outflow, 17 October 2004 The Changjiang is China s longest river and the one with the greatest volume flow and one of the greatest sediment fluxes [6]. In Fig. 4 is shown TSS calculated from MERIS data for 17 October 2004. As one moves inshore TSS can be seen to increase to approximately 50 gm/m 3 and then start to decrease. This is clearly an artifact due to the system s inability to handle TSS concentrations above 50 gm/m 3. (a) (b) Figure 5 MERIS image of band 1, 17 October 2004 with (a) invalid reflectances, flagged in black and (b) Areas of invalid aerosol alpha and aerosol thickness flagged in black. Fig. 5 shows the areas flagged as having pixels with (a) invalid reflectances and (b) invalid aerosol alpha and aerosol thickness. As these two areas are the same it seems that the former is determined by the latter. Reflectances are valid within the light blue area. However TSS values higher than 50 gm/m 3 were very likely landward

of the light blue area, so the MERIS algorithms may here be confusing strange aerosols with high TSS values. The area covered by this image was found to have the same problems on many occasions. Figure 6. MERIS image of TSS in the Zhujiang estuary, 14 February 2004, and TSS histogram showing the distribution in gm/m 3.. 2.3 Zhujiang Estuary, 14 February 2004 The Zhujiang is the major river in southern China. Ghuangzhou and its industrial area are situated on its banks and its estuary is just to the west of Hong Kong. This estuary and the waters around Hong Kong have been the subjects of many studies e.g. [7] and [8]. Fig. 6 shows the TSS values, calculated from MERIS data, in the Zhujiang estuary on 14 February 2004. The values in this image appear to be quite sensible, with maximum TSS values less than 50 gm/m 3. However over-water reflectances in the whole image are flagged as invalid. The over-water pixels are also flagged as invalid aerosol alpha and aerosol thickness and ice or high aerosol load. It seems, once again that the MERIS algorithms cannot handle the aerosols, a common problem over the Zhujiang estuary. 3. SOURCES OF AEROSOLS The levels of air pollution in China are notoriously high, and this could be a major contributor to the problems with aerosols found in this study. The major sources of pollution are coal combustion and vehicle exhausts [9] to [14]. In the winter months fine dust transported from north-west China is also a major source of airborne particles in Beijing, coastal China and over the Yellow Sea, east of Bohai Bay [9], [12] and [15]. Near the mouths of the Changjiang and Zhujiang both the pollution and wind-driven soil are major sources of aerosols in the winter months. The aerosol optical depths over China have also been dramatically increasing [3]. In Hong Kong, close to the mouth of the Zhujiang, the summer monsoon brings clean marine air over that region [10].Although this is very high in humidity, its aerosol model should be in the MERIS database. It may just be that the aerosol levels are just too high. The inability of the MERIS algorithms to resolve the TSS and chlorophyll seems to persist along the whole China coastline. This would suggest the problem lies with the aerosol resolution and not with the very high values of TSS in the river plumes near the river mouth. In order to meet our original goals it may be necessary to develop a bigger range of aerosol models for use with the MERIS algorithms. 4. REFERENCES 1. Kosmicki, K., L. Ametistova,, I.S.F Jones (2005) From SeaWifs to MERIS: Great Barrier Reef Lagoon Case Study, ESA SP- 572. 2. Aiken, J. and Moore, G. (2000) Algorithm Technical Basis Document ATBD 2.6 Case 2 (S) Bright Pixel Atmospheric Correction, Plymouth Marine Laboratory PO-TN- MEL- GS-0005.

3. Yunfeng, L., Lu, D., Zhou, X., Li, W. And He, Q. (2001) Characteristics of the spatial distribution and yearly variation of aerosol optical depth over China in the last 30 years. Journal of Geophysical Research, 106, 14501-14514. 4. European Space Agency (2002) EnviSat MERIS Product Handbook, 2002. 5. MERIS Quality Working Group (2006), MERIS Product Quality Status Report MEGS7.4 and IPF 5, version 1, ENVISAT 6. Wu, J., H. Shen, Y. Chen, (2001), Sediment classification and estimation of suspended sediment fluxes in the ChangJiang Estuary, China, Water Resources Research, 37, 1969-1979. 7. Yin, K., 2002, Monsoonal influence on seasonal variations in nutrients and phytoplankton biomass in coastal waters of Hong Kong in the vicinity of the Pearl River estuary, Marine Ecology Progress Series, 245, 111-122. 8. Cai, W-J., Dai, M., Wang, Y., Zhai, W., Huang, T., Chen, S., Zhang, F., Chen, Z and Wang, Z. (2004) The biogeochemistry of inorganic carbon and nutrients in the Pearl River estuary and the adjacent Northern South China Sea, Continental Shelf Research, 24, 1301-1319. 12. Sun, Y., Zhuang, G., Wang, Y., Han, L., Guo, J., Dan, M., Zhang, W, Wang, Z. and Hao, Z. (2004) The air-borne particle pollution in Beijing concentration, composition, distribution and sources, Atmospheric Environment, 38, 5991-6004. 13. Ye,B., Ji, X., Yang, H., Yao, X., Chan, C.K., Cadle, S.H., Chan, T. and Mulawa, P.A. (2003) Concentration and chemical composition of PM 2.5 in Shanghai for a 1- year period, Atmospheric Environment, 37, 499-510. 14. Zhang, J., Wu, Y., Liu, C.L., Shen, Z.B., Yu, Z.G. and Zhang, Y. (2001) Aerosol characters from the desert region of Northwest China and the Yellow Sea in spring: observations at Minqin, Qingdao and Qianliyan in 1995-1996. Atmospheric Environment, 35, 5007-5018. 15. Kim, B-G., Han, J-S and Park, S-U (2001) Transport of SO 2 and aerosol over the Yellow Sea, Atmospheric Environment, 35, 727-737. 9. Cao, L., Tian, W., Ni, B., Zhang, Y. and Wang, P. (2002) Preliminary study of airborne particulate matter in a Beijing sampling station by instrumental neutron activation analysis, Atmospheric Environment, 36, 1951-1956. 10. Cheng, Z.L., Lam, K.S., Chan, L.Y. Wang, T. and Cheng, K.K. (2000) Chemical characteristics of aerosols at coastal station in Hong Kong. I. Seasonal variation of major ions, halogens and mineral dusts between 1995 and 1996, Atmospheric Environment, 34, 2771-2783. 11. Shu, J., Dearing, J.A., Morse, A.P., Yu, L. and Yuan, N. (2001) Determining the sources of atmospheric particles in Shanghai, China, from magnetic and geochemical properties, Atmospheric Environment, 35, 2615-2625.