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Title: Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations

Abstract

Understanding the role of estuarine-carbon fluxes is essential to improve estimates of the global carbon budget. Dissolved organic matter (DOM) plays an important role in aquatic carbon cycling. Here, the chromophoric fraction of DOM (CDOM) can be readily detected via in situ and remotely-sensed optical measurements. DOM properties, including CDOM absorption coefficient at 412 nm (a g412) and dissolved organic carbon (DOC) concentrations were examined in Apalachicola Bay, a national estuarine research reserve located in the northeast Gulf of Mexico, using in situ and satellite observations during the spring and fall of 2015. Synoptic and accurate representation of estuarine-scale processes using satellite ocean color imagery necessitates the removal of atmospheric contribu- tion (~90%) to signals received by satellite sensors to successfully link to in situ observations. Three atmospheric correction schemes (e.g., Standard NIR correction, Iterative NIR correction, and SWIR correction) were tested first to find a suitable correction scheme for the VIIRS imagery in low to moderately turbid Apalachicola Bay. The iterative NIR correction performed well, and validation showed high correlation (R 2 = 0.95, N = 25) against in situ light measurements. A VIIRS-based CDOM algorithm was developed (R 2 = 0.87, N = 9) and validated (R 2more » = 0.76, N = 20, RMSE = 0.29 m -1) against in situ observations. Subsequently, ag412 was used as a proxy of DOC in March (DOC = 1.08 + 0.94 × a g412,R 2 =0.88, N = 13)and in November (DOC= 1.61 + 1.33 × a g412, R 2 = 0.83, N = 24) to derive DOC maps that provided synoptic views of DOC distribution, sources, and their transport to the coastal waters during the wet and dry seasons. The estimated DOC stocks were ~3.71 × 10 6 kg C in March and ~4.07 × 10 6 kg C in November over an area of ~560 km2. Volume flux (out of the bay) almost doubled for March 24 (735 m 3 s -1) relative to November 4 (378 m 3 s -1). However, estimates of DOC fluxes exported out of the bay from model-derived currents and satellite-derived DOC were only marginally greater in March (0.163 × 10 6 kg C d -1) than in November (0.124 × 10 6 kg C d -1) and reflected greater DOC stocks in the fall. Finally, the combination of satellite-, field-, and model-based observations revealed the strong linkage between the Apalachicola River plume, a major source of DOM, and the overall hydrodynamic forcing that controlled distributions of CDOM abundance, DOC concentration, stocks, and fluxes in the bay.« less

Authors:
 [1];  [1];  [2];  [3];  [4];  [2];  [3];  [5]
  1. Louisiana State Univ., Baton Rouge, LA (United States)
  2. North Carolina State Univ., Raleigh, NC (United States)
  3. Univ. of Florida, Gainesville, FL (United States)
  4. Naval Research Lab., Stennis Space Centre, MS (United States)
  5. Univ. of Florida, Gainesville, FL (United States); Univ. of Florida, St. Augustine, FL (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1347848
Report Number(s):
PNNL-SA-124218
Journal ID: ISSN 0034-4257
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Remote Sensing of Environment
Additional Journal Information:
Journal Volume: 191; Journal Issue: C; Journal ID: ISSN 0034-4257
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; satellite; remote sensing; CDOM; organic carbon; estuarine; flux; stock; aquatic; terrestrial; interface; ecosystem; Apalachicola Bay; atmospheric-correction; carbon stocks & fluxes; CDOM algorithm; DOC; VIIRS

Citation Formats

Joshi, Ishan D., D'Sa, Eurico J., Osburn, Christopher L., Bianchi, Thomas S., Ko, Dong S., Oviedo-Vargas, Diana, Arellano, Ana R., and Ward, Nicholas D. Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations. United States: N. p., 2017. Web. doi:10.1016/j.rse.2017.01.039.
Joshi, Ishan D., D'Sa, Eurico J., Osburn, Christopher L., Bianchi, Thomas S., Ko, Dong S., Oviedo-Vargas, Diana, Arellano, Ana R., & Ward, Nicholas D. Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations. United States. doi:10.1016/j.rse.2017.01.039.
Joshi, Ishan D., D'Sa, Eurico J., Osburn, Christopher L., Bianchi, Thomas S., Ko, Dong S., Oviedo-Vargas, Diana, Arellano, Ana R., and Ward, Nicholas D. Mon . "Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations". United States. doi:10.1016/j.rse.2017.01.039. https://www.osti.gov/servlets/purl/1347848.
@article{osti_1347848,
title = {Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations},
author = {Joshi, Ishan D. and D'Sa, Eurico J. and Osburn, Christopher L. and Bianchi, Thomas S. and Ko, Dong S. and Oviedo-Vargas, Diana and Arellano, Ana R. and Ward, Nicholas D.},
abstractNote = {Understanding the role of estuarine-carbon fluxes is essential to improve estimates of the global carbon budget. Dissolved organic matter (DOM) plays an important role in aquatic carbon cycling. Here, the chromophoric fraction of DOM (CDOM) can be readily detected via in situ and remotely-sensed optical measurements. DOM properties, including CDOM absorption coefficient at 412 nm (ag412) and dissolved organic carbon (DOC) concentrations were examined in Apalachicola Bay, a national estuarine research reserve located in the northeast Gulf of Mexico, using in situ and satellite observations during the spring and fall of 2015. Synoptic and accurate representation of estuarine-scale processes using satellite ocean color imagery necessitates the removal of atmospheric contribu- tion (~90%) to signals received by satellite sensors to successfully link to in situ observations. Three atmospheric correction schemes (e.g., Standard NIR correction, Iterative NIR correction, and SWIR correction) were tested first to find a suitable correction scheme for the VIIRS imagery in low to moderately turbid Apalachicola Bay. The iterative NIR correction performed well, and validation showed high correlation (R2 = 0.95, N = 25) against in situ light measurements. A VIIRS-based CDOM algorithm was developed (R2 = 0.87, N = 9) and validated (R2 = 0.76, N = 20, RMSE = 0.29 m-1) against in situ observations. Subsequently, ag412 was used as a proxy of DOC in March (DOC = 1.08 + 0.94 × ag412,R2 =0.88, N = 13)and in November (DOC= 1.61 + 1.33 × ag412, R2 = 0.83, N = 24) to derive DOC maps that provided synoptic views of DOC distribution, sources, and their transport to the coastal waters during the wet and dry seasons. The estimated DOC stocks were ~3.71 × 106 kg C in March and ~4.07 × 106 kg C in November over an area of ~560 km2. Volume flux (out of the bay) almost doubled for March 24 (735 m3 s-1) relative to November 4 (378 m3 s-1). However, estimates of DOC fluxes exported out of the bay from model-derived currents and satellite-derived DOC were only marginally greater in March (0.163 × 106 kg C d-1) than in November (0.124 × 106 kg C d-1) and reflected greater DOC stocks in the fall. Finally, the combination of satellite-, field-, and model-based observations revealed the strong linkage between the Apalachicola River plume, a major source of DOM, and the overall hydrodynamic forcing that controlled distributions of CDOM abundance, DOC concentration, stocks, and fluxes in the bay.},
doi = {10.1016/j.rse.2017.01.039},
journal = {Remote Sensing of Environment},
number = C,
volume = 191,
place = {United States},
year = {Mon Feb 06 00:00:00 EST 2017},
month = {Mon Feb 06 00:00:00 EST 2017}
}

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