Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations

Abstract Despite recent advances in using satellite data for continuous monitoring of estuarine water quality parameters such as turbidity and water clarity, estimating chlorophyll-a concentrations (Chla) has remained problematic due to the optical complexity of estuarine waters and imperfect atmospheric correction. This poses a significant challenge to the community as synoptic and frequent Chla “measurements” from satellites are in high demand by various government agencies and environmental groups to help make management decisions. Here, using 10 years of in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from a moderately sized, turbid estuary, Tampa Bay (Florida, USA), we developed and validated a new algorithm specifically designed for retrieving Chla from MODIS data. The algorithm takes the red-to-green remote-sensing reflectance ( R rs( λ )) band ratio of [ R rs(667) +  R rs(678)]/[ R rs(531) +  R rs(547)] as the independent variable, and estimates Chla through the non-linear regression function: Ln(Chla) = 1.91Ln( x ) + 3.40 ( R 2  = 0.87, N  = 97, p −3 ) where ‘ x ’ is the band ratio. Validation of the algorithm using two independent datasets collected by different groups and near-concurrent MODIS measurements showed robust algorithm performance for Chla within this range, with mean relative errors of 25.8% and 41.7% for the two datasets. Time-series analyses at representative stations using both in situ and MODIS Chla also showed general agreement, with instances of noticeable discrepancy attributed to different measurement frequencies. The algorithm was implemented to establish a 10-year Chla data record for Tampa Bay in order to serve as a baseline for monitoring future phytoplankton bloom events. The 10-year Chla data record showed substantial variability in both space and time, with generally higher Chla observed during the wet season and in upper bay segments, and Chla minima observed in all bay segments during May and June. These spatial and temporal distributions appear to be regulated primarily by wind and river discharge, which also explain the significant declining trend in Chla since 2005. The established 10-year MODIS-based Chla data record provides complementary information to existing field-based monitoring programs, helping to make nutrient reduction management decisions. Furthermore, preliminary tests of the algorithm for the Chesapeake Bay and for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements suggest possible applicability of the proposed approach to other estuaries and satellite ocean color sensors.

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