Seasonal–spatial variation and remote sensing of phytoplankton absorption in Lake Taihu, a large eutrophic and shallow lake in China

Shallow water, strong sediment resuspension, complex river inputs and frequent cyanobacterial blooms characterize the waters of Lake Taihu. In such shallow, eutrophic lakes, the remote sensing of phycocyanin (PC), a characteristic pigment of cyanobacteria, is dependent on the estimation precision of phytoplankton absorption. For Lake Taihu, we monitored the seasonal–spatial variation of phytoplankton absorption, and a three-band model was calibrated and validated to estimate phytoplankton absorption (aph(665)) from a dataset of the spatial and temporal patterns of the bio-optical properties collected, during five cruises in January (winter), April (spring), July (summer), and October (autumn) in 2006 to 2007. Two distinct situations prevailed; in winter tripton strongly predominated over particulate matter, and in spring-summer-autumn phytoplankton made an important contribution. In winter, meteorology mainly determined the bio-optical properties of the water column, whereas in the spring-summer-autumn the biological activity was an additional active factor. The three-band remote sensing model 1⁄2R 1 rs ð673Þ R 1 rs ð698Þ Rrsð731ÞðRrs: remote sensing reflectance) of aph(665) was calibrated and validated, and its performance was compared and assessed with the published band-ratio method. With the three-band model, the root mean square error and mean relative error were 0.150 m (50.5% accounting for the mean value) and 45.7% respectively; with the published band-ratio method, the values were 0.290 m (97.3% accounting for the mean value) and 213.0% respectively, based on an independent validation dataset. Furthermore, the three-band and band-ratio models worked well in estimating phytoplankton absorption with simulated MERIS bands data with higher precision for the three-band model in Lake Taihu. The result showed that the three-band model was superior to the published band-ratio method, and thus the former can be used to improve the estimation precision of remote sensing of PC.

[1]  Vittorio E. Brando,et al.  Assessment of water quality in Lake Garda (Italy) using Hyperion , 2007 .

[2]  Machteld Rijkeboer,et al.  Effect of a Waveband Shift on Chlorophyll Retrieval from MERIS Imagery of Inland and Coastal Waters , 2004 .

[3]  Guangwei Zhu,et al.  Measured and numerically partitioned phytoplankton spectral absorption coefficients in inland waters , 2008 .

[4]  A. Gitelson,et al.  A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation , 2008 .

[5]  Annick Bricaud,et al.  Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water‐leaving radiances at SeaWiFS channels in a continental shelf region off Brazil , 2006 .

[6]  Nicolas Hoepffner,et al.  Determination of the major groups of phytoplankton pigments from the absorption spectra of total particulate matter , 1993 .

[7]  Anatoly A. Gitelson,et al.  Satellite Estimation of Chlorophyll-$a$ Concentration Using the Red and NIR Bands of MERIS—The Azov Sea Case Study , 2009, IEEE Geoscience and Remote Sensing Letters.

[8]  Annick Bricaud,et al.  Spatial variations in the chlorophyll‐specific absorption coefficients of phytoplankton and photosynthetically active pigments in the equatorial Pacific , 1997 .

[9]  S. Sathyendranath,et al.  Absorption coefficient of phytoplankton: regional variations in the North Atlantic , 1996 .

[10]  H. Gons,et al.  MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes , 2008 .

[11]  Anatoly A. Gitelson,et al.  Remote chlorophyll-a retrieval in turbid, productive estuaries : Chesapeake Bay case study , 2007 .

[12]  Anatoly A. Gitelson,et al.  The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration , 1992 .

[13]  H. Gordon,et al.  Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean. , 1975, Applied optics.

[14]  Tang Jun.  The Methods of Water Spectra Measurement and Analysis I:Above-Water Method , 2004 .

[15]  Antonio Ruiz-Verdú,et al.  An evaluation of algorithms for the remote sensing of cyanobacterial biomass , 2008 .

[16]  Mark A. Moline,et al.  Deriving in situ phytoplankton absorption for bio‐optical productivity models in turbid waters , 2004 .

[17]  B. Osborne,et al.  Light and Photosynthesis in Aquatic Ecosystems. , 1985 .

[18]  William G. Booty,et al.  Spectral absorption properties of dissolved and particulate matter in Lake Erie , 2008 .

[19]  Bai Zhang,et al.  Estimation of chlorophyll-a concentration using field spectral data: a case study in inland Case-II waters, North China , 2009, Environmental monitoring and assessment.

[20]  H. Claustre,et al.  Variability in the chlorophyll‐specific absorption coefficients of natural phytoplankton: Analysis and parameterization , 1995 .

[21]  Richard G. Derwent,et al.  Radiative forcing in the 21st century due to ozone changes in the troposphere and the lower stratosphere , 2003 .

[22]  L. Prieur,et al.  An optical classification of coastal and oceanic waters based on the specific spectral absorption curves of phytoplankton pigments, dissolved organic matter, and other particulate materials1 , 1981 .

[23]  Giorgio Dall'Olmo,et al.  Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results. , 2006, Applied optics.

[24]  H. Gons,et al.  Optical teledetection of chlorophyll a in turbid inland waters , 1999 .

[25]  Jim Aiken,et al.  An absorption model to determine phytoplankton size classes from satellite ocean colour , 2008 .

[26]  C. Stedmon,et al.  Optical properties and signatures of chromophoric dissolved organic matter (CDOM) in Danish coastal waters , 2000 .

[27]  T. Platt,et al.  Bio-optical characteristics of diatom and prymnesiophyte populations in the Labrador Sea , 2000 .

[28]  Michael E. Sieracki,et al.  Specific absorption coefficient and phytoplankton biomass in the southern region of the California Current , 2004 .

[29]  Motoaki Kishino,et al.  Chlorophyll-specific absorption coefficients and pigments of phytoplankton off Sanriku, northwestern North Pacific , 1998 .

[30]  Junsheng Li,et al.  Modeling Remote-Sensing Reflectance and Retrieving Chlorophyll-a Concentration in Extremely Turbid Case-2 Waters (Lake Taihu, China) , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Stefan G. H. Simis,et al.  Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water , 2005 .

[32]  John J. Cullen,et al.  Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient , 2002 .

[33]  Giorgio Dall'Olmo,et al.  Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results. , 2005, Applied optics.

[34]  Bing Zhang,et al.  A study of absorption characteristics of chromophoric dissolved organic matter and particles in Lake Taihu, China , 2007, Hydrobiologia.

[35]  H. Sosik,et al.  Light absorption by phytoplankton, photosynthetic pigments and detritus in the California Current System , 1995 .

[36]  Antonio Ruiz-Verdú,et al.  Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass , 2007 .

[37]  Dariusz Stramski,et al.  Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe , 2003 .

[38]  Tiit Kutser,et al.  Monitoring cyanobacterial blooms by satellite remote sensing , 2006 .

[39]  Lin Li,et al.  Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin , 2008 .

[40]  Marcel Babin,et al.  Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: Analysis and implications for bio-optical models , 1998 .

[41]  J. Catalán,et al.  Attenuation of ultraviolet radiation in mountain lakes: Factors controlling the among‐ and within‐lake variability , 2000 .

[42]  Bio-Optical Properties of Seawater in the Western Subarctic Gyre and Alaskan Gyre in the Subarctic North Pacific and the Southern Bering Sea during the Summer of 1997 , 2001 .

[43]  Anatoly A. Gitelson,et al.  Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: Model tuning and accuracy optimization , 2006 .

[44]  H. Paerl,et al.  Light absorption by phytoplankton and chromophoric dissolved organic matter in the drainage basin and estuary of the Neuse River, North Carolina (U.S.A.) , 2005 .

[45]  CaoWenxi,et al.  Regional patterns of particulate spectral absorption in the Pearl River estuary , 2003 .

[46]  Junsheng Li,et al.  [Comparison of chlorophyll a concentration estimation in Taihu Lake using different methods]. , 2009, Huan jing ke xue= Huanjing kexue.