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Deep Sea Res
Le, C., Hu, C., English, D., Cannizzaro, J., & Kovach, C. (2013). Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management.
Remote Sensing of Environment
Significant advances have been made in ocean color remote sensing of turbidity and water clarity for estuarine waters, yet accurate estimations of chlorophyll-a concentrations (Chla in mg m− 3) has been problematic, posing a challenge to the research community and an obstacle to managers for long-term water quality assessment. Here, a novel empirical Chla algorithm based on a Red-Green-Chorophyll-Index (RGCI) was developed and validated for MODIS and SeaWiFS observations between 1998 and 2011. The algorithm showed robust performance with two independent datasets, with relative mean uncertainties of ~ 30% and ~ 50% and RMS uncertainties of ~ 40% and ~ 65%, respectively, for Chla ranging between 1.0 and > 30.0 mg m− 3. These uncertainties are comparable or even lower than those reported for the global open oceans when traditional blue-green band ratio algorithms are used. A long-term Chla time series generated from SeaWiFS and MODIS observations showed excellent agreement between sensors and with in situ measurements. Substantial variability in both space and time was observed in the four bay segments, with higher Chla in the upper bay segments and lower Chla in the lower bay segments, and higher Chla in the wet season and lower Chla in the dry season. On average, river discharge could explain ~ 60% of the seasonal changes and ~ 90% of the inter-annual changes, with the latter mainly driven by climate variability (e.g. El Niño and La Niña years) and anomaly events (e.g. tropical cyclones). Significant positive correlation was found between monthly mean Chla anomalies and monthly Multivariate ENSO Index (MEI) (Pearson correlation coefficient = 0.43, p < 0.01, N = 147), with high Chla associated with El Niño and lower Chla associated with La Niña. Further, a Water Quality Decision Matrix (WQDM) was established from satellite observations, providing complementary and more reliable information to the existing WQDM based on less synoptic and less frequent field measurements. The satellite-derived WQDM and long-term time-series data support the decision making efforts of the management agencies that regulate nutrient discharge to the bay. Similar approaches may be established for other estuaries where field data are much more limited than for Tampa Bay.
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