Validation and Calibration of QAA Algorithm for CDOM Absorption Retrieval in the Changjiang (Yangtze) Estuarine and Coastal Waters

Distribution, migration and transformation of chromophoric dissolved organic matter (CDOM) in coastal waters are closely related to marine biogeochemical cycle. Ocean color remote sensing retrieval of CDOM absorption coefficient (ag(λ)) can be used as an indicator to trace the distribution and variation characteristics of the Changjiang diluted water, and further to help understand estuarine and coastal biogeochemical processes in large spatial and temporal scales. The quasi-analytical algorithm (QAA) has been widely applied to remote sensing inversions of optical and biogeochemical parameters in water bodies such as oceanic and coastal waters, however, whether the algorithm can be applicable to highly turbid waters (i.e., Changjiang estuarine and coastal waters) is still unknown. In this study, large amounts of in situ data accumulated in the Changjiang estuarine and coastal waters from 9 cruise campaigns during 2011 and 2015 are used to verify and calibrate the QAA. Furthermore, the QAA is remodified for CDOM retrieval by employing a CDOM algorithm (QAA_CDOM). Consequently, based on the QAA and the QAA_CDOM, we developed a new version of algorithm, named QAA_cj, which is more suitable for highly turbid waters, e.g., Changjiang estuarine and coastal waters, to decompose ag from adg (CDOM and non-pigmented particles absorption coefficient). By comparison of matchups between Geostationary Ocean Color Imager (GOCI) retrievals and in situ data, it reveals that the accuracy of retrievals from calibrated QAA is significantly improved. The root mean square error (RMSE), mean absolute relative error (MARE) and bias of total absorption coefficients (a(λ)) are lower than 1.17, 0.52 and 0.66 m−1, and ag(λ) at 443 nm are lower than 0.07, 0.42 and 0.018 m−1. These results indicate that the calibrated algorithm has a better applicability and prospect for highly turbid coastal waters with extremely complicated optical properties. Thus, reliable CDOM products from the improved QAA_cj can advance our understanding of the land-ocean interaction process by earth observations in monitoring spatial-temporal distribution of the river plume into sea.

[1]  Robert F. Chen,et al.  Estimation of chromophoric dissolved organic matter in the Mississippi and Atchafalaya river plume regions using above‐surface hyperspectral remote sensing , 2011 .

[2]  C. Mobley,et al.  Removal of surface-reflected light for the measurement of remote-sensing reflectance from an above-surface platform. , 2010, Optics express.

[3]  K. Carder,et al.  Semianalytic Moderate‐Resolution Imaging Spectrometer algorithms for chlorophyll a and absorption with bio‐optical domains based on nitrate‐depletion temperatures , 1999 .

[4]  James W. Brown,et al.  A semianalytic radiance model of ocean color , 1988 .

[5]  L. Prieur,et al.  Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains1 , 1981 .

[6]  ZhongPing Lee,et al.  Effects of molecular and particle scatterings on the model parameter for remote-sensing reflectance. , 2004, Applied optics.

[7]  R. Arnone,et al.  Time series of bio-optical properties in a subtropical gyre: Implications for the evaluation of interannual trends of biogeochemical properties , 2010 .

[8]  R. Arnone,et al.  Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. , 2002, Applied optics.

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

[10]  Zhongbo Su,et al.  Remote-sensing reflectance characteristics of highly turbid estuarine waters – a comparative experiment of the Yangtze River and the Yellow River , 2010 .

[11]  P. Kowalczuk,et al.  Optical characteristics of two contrasting Case 2 waters and their influence on remote sensing algorithms , 2003 .

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

[13]  H. Dierssen,et al.  Advantages and limitations of ocean color remote sensing in CDOM-dominated, mineral-rich coastal and estuarine waters , 2012 .

[14]  Frank E. Hoge,et al.  An analysis of model and radiance measurement errors , 1996 .

[15]  C. Davis,et al.  Method to derive ocean absorption coefficients from remote-sensing reflectance. , 1996, Applied optics.

[16]  S. Hooker,et al.  Algorithm development and validation for satellite‐derived distributions of DOC and CDOM in the U.S. Middle Atlantic Bight , 2008 .

[17]  B. Nechad,et al.  Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters , 2010 .

[18]  Dariusz Stramski,et al.  The role of seawater constituents in light backscattering in the ocean , 2004 .

[19]  Lee Zhong-ping An evaluation of two semi-analytical ocean color algorithms for waters of the South China Sea , 2009 .

[20]  C. Mobley,et al.  Estimation of the remote-sensing reflectance from above-surface measurements. , 1999, Applied optics.

[21]  Jianrong Zhu,et al.  The response time of the Changjiang plume to river discharge in summer , 2016 .

[22]  Xiaolong Yu,et al.  Light absorption properties of CDOM in the Changjiang (Yangtze) estuarine and coastal waters: An alternative approach for DOC estimation , 2016 .

[23]  H. Gordon,et al.  Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review , 1983 .

[24]  Scott A. Freeman,et al.  An assessment of optical properties and primary production derived from remote sensing in the Southern Ocean (SO GasEx) , 2011 .

[25]  Ying Zhao,et al.  Evaluation of the Quasi-Analytical Algorithm (QAA) for Estimating Total Absorption Coefficient of Turbid Inland Waters in Northeast China , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  Deyong Sun,et al.  Validation of a Quasi-Analytical Algorithm for Highly Turbid Eutrophic Water of Meiliang Bay in Taihu Lake, China , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Leonid G. Sokoletsky,et al.  Suspended sediment concentration mapping based on the MODIS satellite imagery in the East China inland, estuarine, and coastal waters , 2017, Chinese Journal of Oceanology and Limnology.

[28]  Jin Chen,et al.  A Relaxed Matrix Inversion Method for Retrieving Water Constituent Concentrations in Case II Waters: The Case of Lake Kasumigaura, Japan , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Leonid G. Sokoletsky,et al.  Optical closure for remote-sensing reflectance based on accurate radiative transfer approximations: the case of the Changjiang (Yangtze) River Estuary and its adjacent coastal area, China , 2014 .

[30]  Yong Q. Tian,et al.  An assessment of remote sensing algorithms for colored dissolved organic matter in complex freshwater environments , 2014 .

[31]  Jong-Kuk Choi,et al.  GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity , 2012 .

[32]  Ross S. Lunetta,et al.  Assessment of the water quality components in turbid estuarine waters based on radiative transfer approximations , 2012 .

[33]  Stéphane Maritorena,et al.  Optimization of a semianalytical ocean color model for global-scale applications. , 2002, Applied optics.

[34]  Menghua Wang,et al.  Remote Sensing of Inherent Optical Properties : Fundamentals , 2009 .

[35]  Zhongping Lee,et al.  Characterization of MODIS-derived euphotic zone depth: Results for the China Sea , 2011 .

[36]  Pil-Hun Chang,et al.  A numerical study on the Changjiang diluted water in the Yellow and East China Seas , 2003 .

[37]  C. Mobley Light and Water: Radiative Transfer in Natural Waters , 1994 .

[38]  E. Aas,et al.  Estimates of radiance reflected towards the zenith at the surface of the sea , 2010 .

[39]  Tiit Kutser,et al.  Using Satellite Remote Sensing to Estimate the Colored Dissolved Organic Matter Absorption Coefficient in Lakes , 2005, Ecosystems.

[40]  Marcel Babin,et al.  Light absorption and fluorescence properties of chromophoric dissolved organic matter (CDOM), in the St. Lawrence Estuary (Case 2 waters) , 1997 .

[41]  Fang Shen,et al.  Absorption Property of Non-algal Particles and Contribution to Total Light Absorption in Optically Complex Waters, a Case Study in Yangtze Estuary and Adjacent Coast , 2012 .

[42]  David Bowers,et al.  The relationship between CDOM and salinity in estuaries: An analytical and graphical solution , 2008 .

[43]  M. Perry,et al.  In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance , 1995 .

[44]  R. Arnone,et al.  Uncertainties of Optical Parameters and Their Propagations in an Analytical Ocean Color Inversion Algorithm , 2010 .

[45]  Fang Shen,et al.  Evaluation of Empirical and Semianalytical Spectral Reflectance Models for Surface Suspended Sediment Concentration in the Highly Variable Estuarine and Coastal Waters of East China , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[46]  Jerzy Dera,et al.  Remote sensing reflectance of Pomeranian lakes and the Baltic , 2011 .

[47]  J R Zaneveld,et al.  Absorption and attenuation of visible and near-infrared light in water: dependence on temperature and salinity. , 1997, Applied optics.

[48]  P. Kowalczuk,et al.  Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters , 2005 .

[49]  John Rogan,et al.  Spatial and interannual variability of dissolved organic matter in the Kolyma River, East Siberia, observed using satellite imagery , 2011 .

[50]  Dariusz Stramski,et al.  Evaluation of the Quasi-Analytical Algorithm for estimating the inherent optical properties of seawater from ocean color: Comparison of Arctic and lower-latitude waters , 2014 .

[51]  Qian Yu,et al.  Inversion of Chromophoric Dissolved Organic Matter From EO-1 Hyperion Imagery for Turbid Estuarine and Coastal Waters , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[52]  K. Carder,et al.  Absorption Spectrum of Phytoplankton Pigments Derived from Hyperspectral Remote-Sensing Reflectance , 2004 .

[53]  Peng Wang,et al.  Uncertainties of inherent optical properties obtained from semianalytical inversions of ocean color. , 2005, Applied optics.

[54]  N. K. Højerslev,et al.  Analytic remote-sensing optical algorithms requiring simple and practical field parameter inputs. , 2001, Applied optics.

[55]  David Doxaran,et al.  A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters , 2002 .

[56]  Palanisamy Shanmugam,et al.  An evaluation of inversion models for retrieval of inherent optical properties from ocean color in coastal and open sea waters around Korea , 2010 .

[57]  Jing Zhang,et al.  Characteristics of the Changjiang plume and its extension along the Jiangsu Coast , 2014 .

[58]  Richard L. Miller,et al.  Bio-optical properties in waters influenced by the Mississippi River during low flow conditions , 2003 .

[59]  J. Kindle,et al.  Euphotic zone depth: Its derivation and implication to ocean-color remote sensing , 2007 .

[60]  Richard L. Miller,et al.  On the Use of Ocean Color Remote Sensing to Measure the Transport of Dissolved Organic Carbon by the Mississippi River Plume , 2008 .

[61]  F. Muller‐Karger,et al.  Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters , 2005 .

[62]  Vittorio E. Brando,et al.  Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality , 2003, IEEE Trans. Geosci. Remote. Sens..

[63]  Wouter Verhoef,et al.  An improved spectral optimization algorithm for atmospheric correction over turbid coastal waters: A case study from the Changjiang (Yangtze) estuary and the adjacent coast , 2017 .

[64]  Jin Chen,et al.  Retrieval of Inherent Optical Properties for Turbid Inland Waters From Remote-Sensing Reflectance , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[65]  A. Dekker,et al.  Validity of SeaDAS water constituents retrieval algorithms in Australian tropical coastal waters , 2007 .

[66]  Zhu Jian OBSERVATION OF THE DILUTED WATER AND PLUME FRONT OFF THE CHANGJIANG RIVER ESTUARY DURING AUGUST 2000 , 2003 .

[67]  C. Davis,et al.  Diffuse attenuation coefficient of downwelling irradiance: An evaluation of remote sensing methods , 2005 .