Long-term distribution patterns of remotely sensed water quality parameters in Chesapeake Bay

Abstract Chesapeake Bay is the largest and one of the most productive estuaries in the U.S., where long-term monitoring and assessment of its water quality are necessary to understand trends and events in order to support management decisions. Significant progress has been made during the past decade in developing remote sensing algorithms for estimating two key water quality parameters, chlorophyll- a concentration (Chl a , mg m −3 ) and diffuse light attenuation coefficient at 490 nm ( K d (490), m −1 ), from satellite ocean color measurements in oceanic, coastal, and estuarine waters. Yet deriving a robust Chl a data product for Chesapeake Bay still remains a challenge because of its complex optical properties. Here, a recently developed algorithm approach (Red–Green Chlorophyll Index or RGCI, based on red–green remote-sensing reflectance (Rrs (λ)) ratios) was tested, validated, and applied to Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to establish a 14-year (September 1997 to December 2011) Chl a Environmental Data Record (EDR). The new approach showed significant improvement over the traditional blue–green Rrs (λ) band-ratio algorithms (e.g., OC4, OC3M), with consistent performance for MODIS (mean relative error = 40.9%, mean ratio = 1.09) and SeaWiFS (MRE = 45.8%, mean ratio = 1.09) for Chl a ranging between 1 and 50 mg m −3 . Anomaly and EOF analyses revealed strong spatial gradients, seasonality, and climate-driven inter-annual changes in the satellite-based Chl a EDR. These changes were highly correlated with satellite-based K d (490) EDR, leading to the development of a Water Quality Decision Matrix (WQDM) and providing support to on-going nutrient reduction management programs for this estuary.

[1]  K. Voss,et al.  Spectral optimization for constituent retrieval in Case 2 waters II: Validation study in the Chesapeake Bay , 2009 .

[2]  J. Adolf,et al.  Bio-optical model for Chesapeake Bay and the Middle Atlantic Bight , 2004 .

[3]  Jun Zhao,et al.  Inherent and apparent optical properties of the complex estuarine waters of Tampa Bay: What controls light? , 2013 .

[4]  Charles,et al.  SeaWiFS Postlaunch Calibration and Validation Analyses , Part 1 , 2000 .

[5]  Menghua Wang,et al.  Water properties in Chesapeake Bay from MODIS-Aqua measurements , 2012 .

[6]  C. Davis,et al.  Chesapeake Bay outflow plume and coastal upwelling events: Physical and optical properties , 2001 .

[7]  Chengfeng Le,et al.  Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations , 2013 .

[8]  J. O'Reilly,et al.  Climatological phytoplankton chlorophyll and sea surface temperature patterns in continental shelf and slope waters off the northeast U.S. coast , 2002 .

[9]  Maria Tzortziou,et al.  Atmospheric correction for NO2 absorption in retrieving water-leaving reflectances from the SeaWiFS and MODIS measurements. , 2007, Applied optics.

[10]  L. Harding,et al.  Bio-Optical and Remote Sensing Observations in Chesapeake Bay. Chapter 7 , 2003 .

[11]  J. R. Zaneveld,et al.  In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. , 2006, Applied optics.

[12]  J. Hagy,et al.  Cultural eutrophication in the Choptank and Patuxent estuaries of Chesapeake Bay , 2006 .

[13]  D. Conley,et al.  Scales of nutrient-limited phytoplankton productivity in Chesapeake Bay , 1996 .

[14]  Chengfeng Le,et al.  Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management , 2013 .

[15]  R. Arnone,et al.  A model for the diffuse attenuation coefficient of downwelling irradiance , 2005 .

[16]  Richard Boler,et al.  Variations in water clarity and chlorophylla in Tampa Bay, Florida, in response to annual rainfall, 1985–2004 , 2006 .

[17]  Menghua Wang,et al.  The United States' Next Generation of Atmospheric Composition and Coastal Ecosystem Measurements: NASA's Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission , 2012 .

[18]  L. Ward,et al.  Phytoplankton, nutrients, and turbidity in the Chesapeake, Delaware, and Hudson estuaries , 1988 .

[19]  R. Arnone,et al.  Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. , 2002, Applied optics.

[20]  J. Gower,et al.  The information content of different optical spectral ranges for remote chlorophyll estimation in coastal waters , 1984 .

[21]  Simon Albert,et al.  Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia. , 2005, Marine pollution bulletin.

[22]  J. Kindle,et al.  Euphotic zone depth: Its derivation and implication to ocean-color remote sensing , 2007 .

[23]  A. Gitelson,et al.  Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands , 2005 .

[24]  Dariusz Stramski,et al.  Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe , 2003 .

[25]  Menghua Wang,et al.  Seawifs Postlaunch Calibration and Validation Analyses , 2013 .

[26]  Maria Tzortziou,et al.  Remote sensing reflectance and inherent optical properties in the mid Chesapeake Bay , 2007 .

[27]  F. Muller‐Karger,et al.  How precise are SeaWiFS ocean color estimates? Implications of digitization-noise errors , 2001 .

[28]  W. Gregg.  Reports of the International Ocean-Colour Coordinating Group , 2007 .

[29]  J. M. Landwehr,et al.  Habitat requirements for submerged aquatic vegetation in Chesapeake Bay: Water quality, light regime, and physical-chemical factors , 2004 .

[30]  James D. Hagy,et al.  Hypoxia in Chesapeake Bay, 1950–2001: Long-term change in relation to nutrient loading and river flow , 2004 .

[31]  Stéphane Maritorena,et al.  Optimization of a semianalytical ocean color model for global-scale applications. , 2002, Applied optics.

[32]  B. Franz,et al.  Regional and seasonal variability of chlorophyll-a in Chesapeake Bay as observed by SeaWiFS and MODIS-Aqua , 2009 .

[33]  Harry V. Wang,et al.  Determining the age of water and long-term transport timescale of the Chesapeake Bay , 2007 .

[34]  Maria Tzortziou,et al.  Bio-optics of the Chesapeake Bay from measurements and radiative transfer closure , 2006 .

[35]  D. W. Pritchard,et al.  Responses of upper Chesapeake Bay to variations in discharge of the Susquehanna River , 1986 .

[36]  Anatoly A. Gitelson,et al.  Remote chlorophyll-a retrieval in turbid, productive estuaries : Chesapeake Bay case study , 2007 .

[37]  L. Harding,et al.  SeaWiFS retrievals of chlorophyll in Chesapeake Bay and the mid-Atlantic bight , 2005 .

[38]  P. J. Werdell,et al.  A multi-sensor approach for the on-orbit validation of ocean color satellite data products , 2006 .

[39]  Michael R. Roman,et al.  Eutrophication of Chesapeake Bay: historical trends and ecological interactions , 2005 .

[40]  J. Cloern.  Our evolving conceptual model of the coastal eutrophication problem , 2001 .

[41]  W. Gregg,et al.  Global and regional evaluation of the SeaWiFS chlorophyll data set , 2004 .

[42]  Xiaoju Pan,et al.  Remote sensing of the absorption coefficients and chlorophyll a concentration in the United States southern Middle Atlantic Bight from SeaWiFS and MODIS-Aqua , 2008 .