Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters

He, Xianqiang; Bai, Yan; Pan, Delu; Huang, Ningli; Dong, Xu; Chen, Jinshun; Chen, Chen‐Tung Arthur; Cui, Qianfang

doi:10.1016/j.rse.2013.01.023

Cited by 228 publications

(158 citation statements)

References 51 publications

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“…This relationship still needs to be improved to increase the accuracy of atmospheric correction and empirical inversion algorithms. The average relative bias in the empirical inversion algorithm are 13.3% and 14.2% and the absolute relative errors are 25.2% and 56.0% for SSC ď 300 mg/L and SSC > 300 mg/L, respectively [32]. The results showed a relatively small prediction error in the GOCI derived SSC when its concentration was smaller than 300 mg/L, but had a relatively large error when its concentration exceeded 300 mg/L.…”

Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 84%

“…It was shown to apply to the SSC range of 8 mg/L to 5275 mg/L seen in Hangzhou Bay. For more detailed information about the UV-AC algorithm and SSC retrieval algorithm, a full description is presented in He et al [32]. The resulting algorithm is expressed by the following: …”

Section: Retrieval Of Ssc From Gocimentioning

confidence: 99%

“…Maps of SSC are generated from R rs images using an empirical algorithm based on the observed relationship between in-situ measurements of R rs and SSC. The following algorithm was developed by He et al [32], and was derived from observations taken by the '908 Project' [32]. It was shown to apply to the SSC range of 8 mg/L to 5275 mg/L seen in Hangzhou Bay.…”

Section: Retrieval Of Ssc From Gocimentioning

confidence: 99%

“…A reasonable explanation for this relatively large difference is that the sediment types in Hangzhou Bay are naturally complicated. Due to lack of in-situ data from this region, it is hard to determine the sediment's composition, size and shape [32]. In addition, measurement errors, including time differences between reflectance measurement and SSC sampling, water volume measurement, weighting and sedimentation in the sampling bottles might be another reason for some of the discrepancies [32].…”

Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 99%

“…Due to lack of in-situ data from this region, it is hard to determine the sediment's composition, size and shape [32]. In addition, measurement errors, including time differences between reflectance measurement and SSC sampling, water volume measurement, weighting and sedimentation in the sampling bottles might be another reason for some of the discrepancies [32]. Suspended sediment modeling is based on the variations of dynamic marine environments in both the hydrodynamic and sediment transport models as described by the governing equations.…”

Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 99%

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Using GOCI Retrieval Data to Initialize and Validate a Sediment Transport Model for Monitoring Diurnal Variation of SSC in Hangzhou Bay, China

Yang

Mao

Huang

et al. 2016

Water

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Abstract:The diurnal variation of the suspended sediment concentration (SSC) in Hangzhou Bay, China has been investigated using remotely-sensed SSC derived from the Geostationary Ocean Color Imager (GOCI) in combination with a coupled hydrodynamic-ecological model for regional and shelf seas (COHERENS). The SSC maps were inferred through a UV-AC atmospheric correction algorithm and an empirical inversion algorithm from the GOCI Level-1B data. The sediment transport model was initialized from maps of the GOCI-derived SSC and the model results were validated through a comparison with remotely-sensed data. The comparison demonstrated that the model results agreed well with the observations. The relationship between SSC distribution and hydrodynamic conditions was analyzed to investigate the sediment transport dynamics. The model's results indicate that the action of tidal currents dominate the sediment deposition and re-suspension in the coastal waters of the East China Sea. This is especially the case in Hangzhou Bay where the tidal currents are strongest. The satellite-derived sediment data product can not only dramatically improve the specification of the initial conditions for the sediment model, but can also provide valuable information for the model validation, thereby improving the model's overall performance.

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Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 84%

Section: Retrieval Of Ssc From Gocimentioning

confidence: 99%

Section: Retrieval Of Ssc From Gocimentioning

confidence: 99%

Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 99%

Section: Improvements Of Model/satellite Comparisonsmentioning

confidence: 99%

See 3 more Smart Citations

Using GOCI Retrieval Data to Initialize and Validate a Sediment Transport Model for Monitoring Diurnal Variation of SSC in Hangzhou Bay, China

Yang

Mao

Huang

et al. 2016

Water

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Summertime Changjiang River plume variation during 1998–2010

Bai

Pan

et al. 2014

JGR Oceans

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Using an improved satellite-derived salinity algorithm in the East China Sea (ECS), we presented and examined a general view on summertime Changjiang River plume variation during 1998-2010. Three types of plume shapes were identified: (1) the commonly known northeastward transportation, (2) a case in which most of the plume water crossed the Cheju Strait into the Tsushima-Korea Straits with only a small fraction staying on the shelf of the ECS, and (3) a rare case in which the plume front moved southeastward. Satellite time-series data suggested that, during the peak river discharge time in July with favorable southwest monsoon, the plume area was highly correlated with the river discharge of the same month. Interestingly, the plume area in August was also dominated by the discharge in July. In August, as the direct effect of freshwater discharge weakening, the plume area also became positively correlated with wind speed in the 45 and 60 direction, suggesting that the plume extension was more influenced by the southwesterly wind during periods of smaller discharge. Furthermore, a few special cases with unique plume extensions were found under extreme weather conditions. Finally, we found no significant long-term trend of plume area change over 1998-2010 in summertime and concluded that the interannual variation was probably regulated by natural variation rather than anthropogenic effects, such as construction of the Three Gorges Dam. This study will have implications for biogeochemical and modeling studies in large river plume areas.

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Satellite views of the episodic terrestrial material transport to the southern Okinawa Trough driven by typhoon

Bai

Chen

et al. 2014

JGR Oceans

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Using satellite-derived water transparency (alias Secchi depth) images, we found clear signals of terrestrial material transport to the southern Okinawa Trough triggered by the Typhoon Morakot in August 2009. Three sources were identified: one is from the eastern coast of Taiwan, another is from the western coast of Taiwan, and the other is from the coast of mainland China. Carried by northward flows, typhoon-triggered terrestrial materials from both sides of Taiwan's coasts were transported to the region northeast of Taiwan. Moreover, the terrestrial material from the coast of mainland China could cross the Taiwan Strait and be further transported to the region northeast of Taiwan. These typhoon-induced terrestrial materials off northeastern Taiwan could then be transported to the southern Okinawa Trough along the western edge of the Kuroshio. In addition to the particulate terrestrial material transported, nutrients might also be transported to the Kuroshio main stream. A significant phytoplankton bloom was observed along the Kuroshio path for about 300 km off northeast of Taiwan. Our results indicate that episodic cyclonedriven terrestrial material transport could be another source of mud in the southern Okinawa Trough.

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Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters

Cited by 228 publications

References 51 publications

Using GOCI Retrieval Data to Initialize and Validate a Sediment Transport Model for Monitoring Diurnal Variation of SSC in Hangzhou Bay, China

Using GOCI Retrieval Data to Initialize and Validate a Sediment Transport Model for Monitoring Diurnal Variation of SSC in Hangzhou Bay, China

Summertime Changjiang River plume variation during 1998–2010

Satellite views of the episodic terrestrial material transport to the southern Okinawa Trough driven by typhoon

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