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

Rodrigues, Thanan; Alcântara, Enner; Watanabe, Fernanda; Imai, Nilton Nobuhiro

doi:10.1016/j.rse.2017.06.018

Cited by 63 publications

(45 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Water transparency is an important and direct parameter for describing the optical characteristics of water bodies and their water quality; transparency is widely measured using Secchi disks to obtain Secchi disk depths (SDDs) in freshwater and marine water monitoring [10,11]. Water transparency visually reflects the clarity and turbidity of a water body and can evaluate trophic status and the underwater light field [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Decline in Transparency of Lake Hongze from Long-Term MODIS Observations: Possible Causes and Potential Significance

Shi

Zhang

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

Transparency is an important indicator of water quality and the underwater light environment and is widely measured in water quality monitoring. Decreasing transparency occurs throughout the world and has become the primary water quality issue for many freshwater and coastal marine ecosystems due to eutrophication and other human activities. Lake Hongze is the fourth largest freshwater lake in China, providing water for surrounding cities and farms but experiencing significant water quality changes. However, there are very few studies about Lake Hongze's transparency due to the lack of long-term monitoring data for the lake. To understand long-term trends, possible causes and potential significance of the transparency in Lake Hongze, an empirical model for estimating transparency (using Secchi disk depth: SDD) based on the moderate resolution image spectroradiometer (MODIS) 645-nm data was validated using an in situ dataset. Model mean absolute percentage and root mean square errors for the validation dataset were 27.7% and RMSE = 0.082 m, respectively, which indicates that the model performs well for SDD estimation in Lake Hongze without any adjustment of model parameters. Subsequently, 1785 cloud-free images were selected for use by the validated model to estimate SDDs of Lake Hongze in 2003-2017. The long-term change of SDD of Lake Hongze showed a decreasing trend from 2007 to 2017, with an average of 0.49 m, ranging from 0.57 m in 2007 to 0.42 m in 2016 (a decrease of 26.3%), which indicates that Lake Hongze experienced increased turbidity in the past 11 years. The loss of aquatic vegetation in the northern bays may be mainly affected by decreases of SDD. Increasing total suspended matter (TSM) concentration resulting from sand mining activities may be responsible for the decreasing trend of SDD.

show abstract

Section: Introductionmentioning

confidence: 99%

Decline in Transparency of Lake Hongze from Long-Term MODIS Observations: Possible Causes and Potential Significance

Shi

Zhang

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Several water types can be found in TCSR identified by ternary diagrams (Figure 3). With absorptions displaced towards the CDOM axes in BAR and IBI, BB showed absorption coefficients displaced towards the phytoplankton axes, and NAV presented absorption coefficients well distributed inside the ternary diagram with slightly higher contributions of NAP [27]. The wide variation in OSC's absorption affects the spectral features in the R rs curves (Figure 4).…”

Section: Discussionmentioning

confidence: 98%

“…Considering several studies about bio-optical modeling for inland waters [27,51,61] and the potential of OLI for its aquatic monitoring [62,63], we evaluated the matching between our glint corrected R rs and LaSRC from OLI. The OLI dataset has been widely applied to inland water systems due to its spatial resolution and the detailed richness of such environments [64][65][66][67].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

et al. 2018

Self Cite

View full text Add to dashboard Cite

The quality control of remote sensing reflectance (R rs ) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the R rs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s −1 ; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected R rs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.

show abstract

“…16 and described in Ref. 17. The R rs spectra were matched with satellite data by convoluting the spectral response functions of Operational Land Imager (OLI) from Landsat-8 and of Ocean and Land Color Instrument (OLCI) from Sentinel-3 bands to derive the band-weighted reflectance data as presented as 18 E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 1 1 6 ; 5 7 3…”

Section: In Situ Radiometric Datamentioning

confidence: 99%

Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters

Rodrigues

Alcântara

Mishra

et al. 2018

J. Appl. Rem. Sens.

Self Cite

View full text Add to dashboard Cite

A semianalytical model developed to estimate the Secchi disk depth (Z SD ) was used in eutrophic-to-hypereutrophic reservoirs (Ibitinga, Ibi, and Barra Bonita, BB) placed in the cascade system of the Tietê River, Brazil. The model was evaluated using the simulated remote sensing reflectance based on the Ocean and Land Color Instrument/Sentinel-3A and the Operational Land Imager/Landsat-8 from both reservoirs. Three quasianalytical algorithm (QAA) versions (QAA v5 , QAA M14 , and QAA W16 ) were evaluated to derive the absorption and backscattering coefficients, and then used for Z SD retrieval. For BB, where the chlorophyll-a concentration exceeded 200 mg m −3 , the model based on QAA v5 showed high uncertainties while the QAA W16 , which was originally parameterized for BB showed better performance regarding the Z SD retrieval (mean absolute percentage errors-MAPE of 22%). However, QAA W16 did not perform satisfactorily for Ibi, which is dominated by colored dissolved organic matter (CDOM). For Ibi, QAA v5 provided the best result with MAPE of 34.60%, followed by QAA M14 with 34.65%. QAA-based Z SD models tend to perform poorly in waters with high concentration of chlorophyll-a possibly due to phytoplankton package effect, whereas the same models may require additional parameterization in waters dominated by CDOM. Landsat-8 data showed significant potential for Z SD retrieval in inland waters. © 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

show abstract

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

Cited by 63 publications

References 77 publications

Decline in Transparency of Lake Hongze from Long-Term MODIS Observations: Possible Causes and Potential Significance

Decline in Transparency of Lake Hongze from Long-Term MODIS Observations: Possible Causes and Potential Significance

Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters

Contact Info

Product

Resources

About