Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme

Abstract The mechanistic model reported in Lee et al. (2015) estimating the Secchi disk depth (ZSD) was applied to an oligo- to mesotrophic reservoir in Brazil. The model was originally validated with data covering lake, oceanic, and coastal waters; however, the model used the quasi-analytical algorithm (QAA) designed for optically deep waters as input and was applied to oceanic and coastal waters to derive absorption [a] and backscattering [bb] coefficients. The hypothesis is that the use of QAAv5 ( http://www.ioccg.org/groups/Software_OCA/QAA_v5.pdf ) to estimate both a and bb (step M1) to retrieve Kd (step M2) and ZSD (step M3) will lead to errors caused by M1 preventing an accurate estimate in oligo- to mesotrophic water. To test this hypothesis, data collected in three field trips were used to apply the mechanistic model based on the spectral bands from OLI/Landsat-8, (often applied to oceanic and coastal waters), and multispectral instrument (MSI)/Sentinel-2 bands (applied to QAA designed for very turbid inland water). The impact of step M1 over steps M2 and M3 was analyzed by the error analysis. The mean absolute percentage error (MAPE) for Kd using QAAv5 ranged between 10.35% and 19.76%, while the error using QAAM14 varied between 12.68% and 28.29%. Regarding the errors of step M3 and applying QAAv5, the total root-mean-square difference (RMSD) varied from 0.55 to 1.18 m and MAPE ranged between 12.86% and 31.17%, while the RMSD ranged between 0.70 and 1.50 m and MAPE varied from 14.33% to 39.13% when using QAAM14. However, the result from QAAv5 showed a better correlation with in situ data, although underestimating Kd and ZSD. Therefore, a modified version of QAAv5 (QAAR17) was evaluated. The results showed an improvement of Kd (MAPE ranging between 8.89% to 18.76%) and ZSD (RMSD ranging between 0.32 and 0.90 m and MAPE ranging between 8.65 and 19.75%), bringing the values close to the 1:1 line. The largest error was observed for the data of the second field trip, where the bio-optical properties showed a horizontal gradient along the reservoir. In addition, the magnitude of the remote sensing reflectance (Rrs) also varied depending on the water quality. Thus, with respect to ZSD mapping, this research showed that environments with a high variability in Rrs can limit the accurate estimation of inherent optical properties (IOPs) based on QAAv5. Therefore, the limiting step of the model was attributed to M1, which means that the mechanistic model from Lee et al. (2015) can be considered an universal approach if M1 is modified based on the type of water.

[1]  Gong Lin,et al.  Changes in water clarity of the Bohai Sea: Observations from MODIS , 2016 .

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

[3]  Jie Dou,et al.  Remote sensing of chlorophyll-a as a measure of red tide in Tokyo Bay using hotspot analysis , 2015 .

[4]  Stelvio Tassan,et al.  Measurement of light absorption by aquatic particles retained on filters: determination of the optical pathlength amplification by the ‘transmittance-reflectance’ method , 1998 .

[5]  H. Buiteveld,et al.  A model for calculation of diffuse light attenuation (PAR) and Secchi depth , 1995, Netherland Journal of Aquatic Ecology.

[6]  D. Siegel,et al.  Modes and mechanisms of ocean color variability in the Santa Barbara Channel , 2001 .

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

[8]  A. Gitelson,et al.  Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. , 2012, Water research.

[9]  Arnold G. Dekker,et al.  Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing , 1993 .

[10]  J. A. Monteiro,et al.  Urbanization and agriculture increase exports and differentially alter elemental stoichiometry of dissolved organic matter (DOM) from tropical catchments. , 2016, The Science of the total environment.

[11]  Maria de Lourdes Bueno Trindade Galo,et al.  Caracterização da qualidade de água e sedimento relacionados com a ocorrência de plantas aquáticas em cinco reservatórios da bacia do rio Tietê , 2003 .

[12]  Kai Sørensen,et al.  Secchi depth in the Oslofjord-Skagerrak area: theory, experiments and relationships to other quantities , 2014 .

[13]  Nilton Nobuhiro Imai,et al.  Analyzing the status of submerged aquatic vegetation using novel optical parameters , 2016 .

[14]  ZhongPing Lee,et al.  Bio-Optical Inversion in Highly Turbid and Cyanobacteria-Dominated Waters , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[15]  M. Koentopp,et al.  ウエッデル海における海氷への潮汐の影響 高分解能ダイナッミック・サーモダイナミック海氷モデルを用いた研究 , 2005 .

[16]  C. A. Coelho,et al.  Precipitation diagnostics of an exceptionally dry event in São Paulo, Brazil , 2016, Theoretical and Applied Climatology.

[17]  Igor Ogashawara,et al.  Coupling remote sensing bio-optical and three-dimensional hydrodynamic modeling to study the phytoplankton dynamics in a tropical hydroelectric reservoir , 2015 .

[18]  Qian Shen,et al.  MODIS-Based Radiometric Color Extraction and Classification of Inland Water With the Forel-Ule Scale: A Case Study of Lake Taihu , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[19]  E. Alcântara,et al.  DELINEAMENTO AMOSTRAL EM RESERVATÓRIOS UTILIZANDO IMAGENS LANDSAT-8/OLI: UM ESTUDO DE CASO NO RESERVATÓRIO DE NOVA AVANHANDAVA (ESTADO DE SÃO PAULO, BRASIL) , 2016 .

[20]  D. Rundquist,et al.  Characterizing the vertical diffuse attenuation coefficient for downwelling irradiance in coastal waters: Implications for water penetration by high resolution satellite data , 2005 .

[21]  Chunmei Cheng,et al.  Estimation of Chlorophyll-a Concentration in Turbid Lake Using Spectral Smoothing and Derivative Analysis , 2013, International journal of environmental research and public health.

[22]  Peter D. Hunter,et al.  Spatial variability of absorption coefficients over a biogeochemical gradient in a large and optically complex shallow lake , 2015 .

[23]  Jun Zhao,et al.  MODIS-Based Mapping of Secchi Disk Depth Using a Qualitative Algorithm in the Shallow Arabian Gulf , 2016, Remote. Sens..

[24]  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.

[25]  Jochen Wollschläger,et al.  Modern approaches to shipborne ocean color remote sensing , 2015 .

[26]  A. Morel.  Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters) , 1988 .

[27]  R. Arnone,et al.  A model for the diffuse attenuation coefficient of downwelling irradiance , 2005 .

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

[29]  Jin Chen,et al.  Application of a Semianalytical Algorithm to Remotely Estimate Diffuse Attenuation Coefficient in Turbid Inland Waters , 2014, IEEE Geoscience and Remote Sensing Letters.

[30]  S. Maritorena,et al.  Bio-optical properties of oceanic waters: A reappraisal , 2001 .

[31]  Wesley J Moses,et al.  NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters: Lake Kinneret case study. , 2011, Water research.

[32]  H. Gordon.  Remote sensing of ocean color: a methodology for dealing with broad spectral bands and significant out-of-band response. , 1995, Applied optics.

[33]  Michele Scardi,et al.  Assessing the Uncertainties of Model Estimates of Primary Productivity in the Tropical Pacific Ocean Revised , 2008 .

[34]  Michael Sydor,et al.  Surface Corrections for Remote Sensing Reflectance in Case 2 Waters of Lake Superior , 2006 .

[35]  R. Arnone,et al.  Penetration of UV-visible solar radiation in the global oceans: Insights from ocean color remote sensing , 2013 .

[36]  M. Petrere,et al.  Defining a fish bio-assessment tool to monitoring the biological condition of a cascade reservoirs system in tropical area , 2014 .

[37]  J. Talling,et al.  Methods for physical and chemical analysis of fresh waters , 1980 .

[38]  C. Barbosa,et al.  Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters , 2016 .

[39]  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.

[40]  Jing Yang,et al.  A Semi-Analytical Model for Remote Sensing Retrieval of Suspended Sediment Concentration in the Gulf of Bohai, China , 2015, Remote. Sens..

[41]  Hugh L. MacIntyre,et al.  Relation between inherent optical properties and land use and land cover across Gulf Coast estuaries , 2015 .

[42]  E. Espíndola,et al.  Environmental gradient in reservoirs of the medium and low Tietê River: limnological differences through the habitat sequence , 2014 .

[43]  J. Allan.  Landscapes and Riverscapes: The Influence of Land Use on Stream Ecosystems , 2004 .

[44]  Weilin Hou,et al.  Secchi disk depth: A new theory and mechanistic model for underwater visibility , 2015 .

[45]  Yongqiang Zhou,et al.  Seasonal-Spatial Distribution and Long-Term Variation of Transparency in Xin’anjiang Reservoir: Implications for Reservoir Management , 2015, International journal of environmental research and public health.

[46]  J. LaBounty.  Secchi transparency of Boulder Basin, Lake Mead, Arizona-Nevada: 1990–2007 , 2008 .

[47]  K. Ruddick,et al.  Turbid wakes associated with offshore wind turbines observed with Landsat 8 , 2014 .

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

[49]  Nilton Nobuhiro Imai,et al.  Drought can cause phytoplankton growth intensification in Barra Bonita reservoir , 2016, Modeling Earth Systems and Environment.

[50]  M. A. Harwell,et al.  Detecting the spatial and temporal variability of chlorophyll-a concentration and total suspended solids in Apalachicola Bay, Florida using MODIS imagery , 2010 .

[51]  Bryan A. Franz,et al.  Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS , 2015 .

[52]  J. Kirk.  A THEORETICAL ANALYSIS OF THE CONTRIBUTION OF ALGAL CELLS TO THE ATTENUATION OF LIGHT WITHIN NATURAL WATERS I. GENERAL TREATMENT OF SUSPENSIONS OF PIGMENTED CELLS , 1975 .

[53]  Kenton Lee,et al.  The Spectral Response of the Landsat-8 Operational Land Imager , 2014, Remote. Sens..

[54]  Stelvio Tassan,et al.  An alternative approach to absorption measurements of aquatic particles retained on filters , 1995 .

[55]  A. Mangin,et al.  Estimation of light penetration, and horizontal and vertical visibility in oceanic and coastal waters from surface reflectance , 2007 .

[56]  J. Zaneveld,et al.  Robust underwater visibility parameter. , 2003, Optics express.

[57]  Igor Ogashawara,et al.  Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[58]  C. Townsend,et al.  Stream Communities Along a Catchment Land-Use Gradient: Subsidy-Stress Responses to Pastoral Development , 2007, Environmental management.

[59]  Gong Lin,et al.  A semi-analytical scheme to estimate Secchi-disk depth from Landsat-8 measurements , 2016 .

[60]  P. Ghosh,et al.  Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal , 2016, Modeling Earth Systems and Environment.

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

[62]  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.

[63]  John E. Tyler,et al.  THE SECCHI DISC , 1968 .

[64]  B. Matsushita,et al.  Semi-analytical prediction of Secchi depth using remote-sensing reflectance for lakes with a wide range of turbidity , 2015, Hydrobiologia.

[65]  J. Kindle,et al.  Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment , 2009 .

[66]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[67]  James L. Mueller,et al.  SeaWiFS Algorithm for the Diffuse Attenuation Coefficient K(490) Using Water-Leaving Radiances at 490 and 555nm , 2000 .

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

[69]  Andrea Cavallaro,et al.  Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing , 2015, Remote. Sens..

[70]  John R. Schott,et al.  Retrieval of color producing agents in Case 2 waters using Landsat 8 , 2016 .

[71]  H. Loisel,et al.  Variability and classification of remote sensing reflectance spectra in the eastern English Channel and southern North Sea , 2007 .

[72]  Rudolph W. Preisendorfer,et al.  Secchi disk science: Visual optics of natural waters1 , 1986 .

[73]  John R. Schott,et al.  Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements , 2017 .

[74]  K. Ruddick,et al.  Advantages of high quality SWIR bands for ocean colour processing: Examples from Landsat-8 , 2015 .

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

[76]  K. Baker,et al.  Optical properties of the clearest natural waters (200-800 nm). , 1981, Applied optics.

[77]  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 .

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

[79]  Jin Chen,et al.  A Modified Semianalytical Algorithm for Remotely Estimating Euphotic Zone Depth in Turbid Inland Waters , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[80]  Tiit Kutser,et al.  Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters , 2016, Remote. Sens..

[81]  Siyue Li,et al.  Water quality in relation to land use and land cover in the upper Han River Basin, China , 2008 .

[82]  Curtis D. Mobley,et al.  Hydrolight 3.0 User's Guide. , 1995 .

[83]  K. Ruddick,et al.  In situ determination of the remote sensing reflectance : an inter comparison , 2012 .

[84]  Mhd. Suhyb Salama,et al.  Remote sensing of euphotic depth in shallow tropical inland waters of Lake Naivasha using MERIS data , 2014 .