Multi-sensor analysis to study turbidity patterns in the Guadalquivir estuary

I. Caballero, G. Navarro

Abstract

A detailed study of the mechanisms generated through the turbidity plume and its variability at the Guadalquivir estuary has been carried out with remote sensing and in situ data. Several sensors with different characteristics have been required (spatial, temporal and spectral resolution), thereby providing information for a multi-sensor analysis. The main objective was to determine the water quality parameters (suspended solids and chlorophyll) and implement the methodology to define the empirical and semi-analytical algorithms from satellite data (MODIS, METIS, Deimos-1). The processes occurred in the estuary and adjacent region have been examined identifying those involved in the different variability scales. The forcings associated with rainfall and discharge from Alcalá del Río dam in addition to the climatic NAO index control seasonal and inter-annual fluctuations, while tide effects (semi-daily and fortnightly cycles) modulate the plume at the mouth throughout the year with significant variability. Special emphasis is focused on diagnosing the role of these mechanisms on the continental shelf ecosystems, constituting a powerful tool for the water quality management and coastal resources.


Keywords

suspended solids; ocean colour; spatio-temporal variability; Deimos-1; MODIS; MERIS

Full Text:

PDF

References

Baban, S. M. J. 1995. The use of Landsat imagery to map fluvial sediment discharge into coastal waters. Marine Geology, 123(3-4), 263-270. http://dx.doi. org/10.1016/0025-3227(95)00003-H

Björnsson, H., Venegas, S. A. 1997. A Manual for EOF and SVD Analyses of Climate

Data. Department of Atmospheric and Oceanic Sciences and Centre for Climate and Global Change, McGill University, Technical report, 97(1).

Bustamante, J., Pacios, F., Díaz-Delgado R., Aragonés, D. 2009. Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images. Journal of Environmental Management, 90(7), 2219-2225. http://dx.doi. org/10.1016/j.jenvman.2007.08.021

Caballero, I., Morris, E. P., Navarro, G. 2012. DEIMOS-1 Satellite Provides Imagery for Coastal Management. Sea Technology, 53(2),10-13.

Caballero, I., Morris, E. P., Ruiz, J., Navarro, G. 2014a. Assessment of suspended solids in the Guadalquivir estuary using new DEIMOS-1 medium spatial resolution imagery. Remote Sensing of Environment, 146, 148-158. http://dx.doi.org/10.1016/j. rse.2013.08.047

Caballero, I., Morris, E., Prieto, L., Navarro, G. 2014b. The influence of the Guadalquivir River on spatio-temporal variability of suspended solids and chlorophyll in the Eastern Gulf of Cádiz. Mediterranean Marine Science, 15(4), 721-738.

Chen, Z., Hu, C., Muller-Karger, F. 2007. Monitoring turbidity in Tampa Bay using MODIS/Aqua 250- m imagery. Remote Sensing of Environment, 109(2), 207-220. http://dx.doi.org/10.1016/j. rse.2006.12.019

Chen, Z., Hu, C., Muller-Karger, F. E., Luther, M. E., 2010. Short-term variability of suspended sediment and phytoplankton in Tampa Bay, Florida: observations from a coastal oceanographic tower and ocean color satellites. Estuarine, Coastal and Shelf Science, 89(1), 62-72. http://dx.doi.org/10.1016/j. ecss.2010.05.014

Contreras, E., Polo, M. J. 2012. Measurement frequency and sampling spatial domains required to characterize turbidity and salinity events in the Guadalquivir estuary (Spain). Natural Hazards and Earth System Science, 12(8), 2581-2589. http:// dx.doi.org/10.5194/nhess-12-2581-2012

Díez-Minguito, M., Baquerizo, A., Ortega-Sánchez, M., Navarro, G., Losada, M. 2012. Tide transformation in the Guadalquivir estuary (SW Spain) and process-based zonation. Journal of Geophysical Research: Oceans, 117(C3), 1978-2012. http://dx.doi. org/10.1029/2011JC007344

Díez-Minguito, M., Baquerizo, A., de Swart, H.E., Losada, M. A. 2014. Structure of the turbidity field in the Guadalquivir estuary: Analysis of observations and a box mode approach. Journal of Geophysical Research: Oceans, 119(10), 7190-7204. http:// dx.doi.org/10.1002/2014jc010210

Dyer, K. R. 1973. Estuaries: A physical introduction. John Wiley & Sons, New York, p. 140.

Goslee, S.C. 2011. Analyzing remote sensing data in R: The landsat package. Journal of Statistical Software, 43(4), 1-25. http://dx.doi.org/10.18637/jss.v043.i04

Hijmans, R. J., Etten, J. 2011. Raster: Geographic analysis and modeling with raster data. R package version 2.0-12 (http://CRAN.R-project.org/ package=raster).

Hu, C., Chen, Z., Clayton, T., Swarzenski, P., Brock, J., Muller-Karger, F. 2004. Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: Initial results from Tampa Bay, FL. Remote Sensing of Environment, 93(3), 423-441. http://dx.doi.org/10.1016/j.rse.2004.08.007

Lahet, F., Forget, P., Ouillon, S. 2001. Application of a colour classification method to quantify the constituents of coastal waters from in situ reflectances sampled at satellite sensor wavebands. International Journal of Remote Sensing, 22(5), 909-914. http:// dx.doi.org/10.1080/01431160051060444

Loisel, H., Bosc, E., Stramski, D., Oubelkheir, K., Deschamps, P. Y. 2001. Seasonal variability of the backscattering coefficient in the Mediterranean Sea based on satellite SeaWiFS imagery. Geophysical Research Letters, 28(22), 4203-4206. http://dx.doi. org/10.1029/2001GL013863

Lorenz, E.N. 1956. Empirical orthogonal functions and statistical weather prediction. Sci. Rep. Statistcal Forecasting Project, Department of Meteorology, MIT, 1, 49 pp.

Miller, R. L., McKee, B. A. 2004. Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters. Remote Sensing of Environment, 93(1-2), 259-266. http://dx.doi. org/10.1016/j.rse.2004.07.012

Navarro, G., Gutiérrez, F. J., Díez-Minguito, M., Losada, M., Ruiz, J. 2011. Temporal and spatial variability in the Guadalquivir estuary: a challenge for real-time telemetry. Ocean Dynamics, 61(6), 753-765. http:// dx.doi.org/10.1007/s10236-011-0379-6

Navarro, G., Caballero, I., Prieto, L., Vázquez, A., Flecha, S., Huertas, I. E., Ruiz, J. 2012a. Seasonal-to-interannual variability of chlorophyll-a bloom timing associated with physical forcing in the Gulf of Cádiz. Advances in Space Research, 50(8), 1164- 1172. http://dx.doi.org/10.1016/j.asr.2011.11.034

Navarro, G., Huertas, I. E., Costas, E., Flecha, S., Díez-Minguito, M., Caballero, I., López-Rodas, V., Prieto, L., Ruiz, J., 2012b. Use of a real-time remote monitoring network (RTRM) to characterize the Guadalquivir estuary (Spain). Sensors, 12(2), 1398- 1421. http://dx.doi.org/10.3390/s120201398

Nechad, B., Ruddick, K., Park, Y. 2010. Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sensing of Environment, 114(4), 854-866. http://dx.doi.org/10.1016/j.rse.2009.11.022

Nechad, B., Ruddick, K., Schroeder, T., Oubelkheir, K., Blondeau-Patissier, D., Cherukuru, N., Brando, V., Dekker, A., Clementson, L., Banks, A. C., Maritorena, S., Werdell, P. J., Sá, C., Brotas, V., Caballero de Frutos, I., Ahn, Y.-H., Salama, S., Tilstone, G., Martinez- Vicente, V., Foley, D., McKibben, M., Nahorniak, J., Peterson, T., Siliò-Calzada, A., Röttgers, R., Lee, Z., Peters, M., Brockmann, C. 2015. CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters. Earth System Science Data, 8, 173-258. http://dx.doi.org/10.5194/ essdd-8-173-2015

Neckel, H., Labs, D. 1984. The solar radiation between 3300 and 12500 Å. Solar Physics, 90(2), 205-258. http://dx.doi.org/10.1007/BF00173953

Nezlin, N. P., DiGiacomo, P. M., 2005. Satellite ocean color observations of stormwater runoff plumes along the San Pedro Shelf (southern California) during 1997–2003. Continental Shelf Research, 25(14), 1692-1711. http://dx.doi.org/10.1016/j. csr.2005.05.001

Ondrusek, M., Stengel, E., Kinkade, C. S., Vogel, R. L., Keegstra, P., Hunter, C., Kim, C. 2012. The development of a new optical total suspended matter algorithm for the Chesapeake Bay. Remote Sensing of Environment, 119, 243-254. http://dx.doi. org/10.1016/j.rse.2011.12.018

O’Reilly, J. E., Maritorena, S., Siegel, D. A., O’Brien, M. C., Toole, D., Mitchell, B. G., et al., 2000. Ocean color chlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. SeaWiFS postlaunch calibration and validation analyses, 3, 9-23.

Otero, M. P., Siegel, D. 2004. Spatial and temporal characteristics of sediment plumes and phytoplankton blooms in the Santa Barbara Channel. Deep Sea Research Part II: Topical Studies in Oceanography, 51(10), 1129-1149.

Parsons, T.R., Maita, Y., Lalli, C.M. 1984. A manual of chemical and biological methods for seawater analysis. Pergamon Press, Oxford, 173 pp.

Prieto, L., Navarro, G., Rodríguez-Gálvez, S., Huertas, I. E., Naranjo J. M., Ruiz, J. 2009. Oceanographic and meteorological forcing of the pelagic ecosystem on the Gulf of Cádiz shelf (SW Iberian Peninsula). Continental Shelf Research, 29(17), 2122-2137. http://dx.doi.org/10.1016/j.csr.2009.08.007

Ritchie, J. C., Cooper, C. M. 1988. Comparison of measured suspended sediment concentrations with suspended sediment concentrations estimated from Landsat MSS data. International Journal of Remote Sensing, 9, 379-387. http://dx.doi. org/10.1080/01431168808954861

Ritchie, J. C., Cooper, C. M., Schiebe, F. R. 1990. The relationship of MSS and TM digital data with suspended sediments, chlorophyll, and temperature in Moon lake, Mississippi. Remote Sensing of Environment, 33(2), 137-148. http://dx.doi. org/10.1016/0034-4257(90)90039-O

Ruiz, J., González-Quirós, R., Prieto, L., Navarro, G. 2009. A Bayesian model for anchovy (Engraulis encrasicolus): The combined forcing of man and environment. Fisheries Oceanography, 18(1), 62-76. http://dx.doi.org/10.1111/j.1365-2419.2008.00497.xSá, C., Da Silva, J., Oliveira, P. B., Brotas, V. 2008. Comparison of MERIS (Algal_1 and Algal_2) and MODIS (OC3M) chlorophyll products and validation with HPLC insitu data collected off the Western Iberian Peninsula. Proceedings of the 2nd MERIS/(A) ATSR User Workshop, Frascati, Italy, 22-26 September.

Shen, F., Salama, M., Zhou, Y., Li, J., Su, Z., Kuang, D. 2010. Remote-sensing reflectance characteristics of highly turbid estuarine waters – a comparative experiment of the Yangtze River and the Yellow River. International Journal of Remote Sensing, 31(10), 2639-2654. http://dx.doi.org/10.1080/01431160903085610

Stumpf, R. P., Gelfenbaum, G., Pennock, J. R. 1993. Wind and tidal forcing of a buoyant plume, Mobile Bay, Alabama. Continental Shelf Research, 13(11), 1281-1301. http://dx.doi.org/10.1016/0278-4343(93)90053-Z

Thomas, A. C., Weatherbee, R. A. 2006. Satellite-measured temporal variability of the Columbia River plume. Remote Sensing of Environment, 100(2), 167-178. http://dx.doi.org/10.1016/j.rse.2005.10.018

Toole, D. A., Siegel, D. A., 2001. Modes and mechanisms of ocean color variability in the Santa Barbara Channel. Journal of Geophysical Research: Oceans (1978–2012), 106(C11), 26985-27000. http://dx.doi.org/10.1029/2000JC000371

UNESCO, 1994. Protocols for the Joint Global Ocean Flux Study (JGOFS) Core Measurements. IOC Manuals and Guides. Paris, UNESCO, 170 pp.

Valente, A.S., da Silva, J.C. 2009. On the observability of the fortnightly cycle of the Tagus estuary turbid plume using MODIS ocean colour images. Journal of Marine Systems, 75(1), 131-137. http://dx.doi.org/10.1016/j.jmarsys.2008.08.008

Abstract Views

1032
Metrics Loading ...

Metrics powered by PLOS ALM




Licencia Creative Commons

This journal is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

Universitat Politècnica de València

Official Journal of the Spanish Association of Remote Sensing

EISSN: 1988-8740    ISSN: 1133-0953