Light absorption properties of southeastern Bering Sea waters: Analysis, parameterization and implications for remote sensing.

The absorption coefficients of phytoplankton (aPHY(λ)), non-algal particles (NAP) (aNAP(λ)) and colored dissolved organic matter (CDOM) (aCDOM(λ)) were investigated and parameterized in the southeastern Bering Sea during July 2008. The absorption coefficients were well structured with respect to hydrographic and biogeochemical characteristics of the shelf. The highest values of aPHY(443) were observed offshore and the lowest values of aPHY(443) were found in the coastal domain, a low productivity region associated with limited macronutrients. Values of aDG(λ) (aCDOM(λ) + aNAP(λ)) revealed an east–west gradient pattern with higher values in the coastal domain, and lower values in the outer domain. Lower chlorophyll specific aPHY(λ) (a*PHY(λ)) observed relative to middle and lower latitude waters indicated a change in pigment composition and/or package effect, which was consistent with phytoplankton community structure. aCDOM(λ) was the dominant light absorbing coefficient at all wavelengths examined except at 676 nm. Modeling of remote-sensing reflectance (Rrs(λ)) and the diffuse attenuation coefficient (Kd(λ)) from inherent optical properties revealed the strong influence of aCDOM(λ) on Rrs(λ) and Kd(λ). Good optical closure was achieved between modeled and radiometer measured Rrs(λ) and Kd(λ) with average percent difference of less than 25% and 19% respectively, except at red wavelengths. The aCDOM(λ) accounted for > 50% of Kd(λ) which was vertically variable. Chlorophyll-a calculated by the NASA standard chlorophyll-a algorithm (OC4.v6) was overestimated due to higher aCDOM(λ) and underestimated due to lower a*PHY(λ) at low and high concentrations of chlorophyll-a, respectively

Seasonal Variation of Colored Dissolved Organic Matter in Barataria Bay, Louisiana, Using Combined Landsat and Field Data

Coastal bays, such as Barataria Bay, are important transition zones between the terrigenous and marine environments that are also optically complex due to elevated amounts of particulate and dissolved constituents. Monthly field data collected over a period of 15 months in 2010 and 2011 in Barataria Bay were used to develop an empirical band ratio algorithm for the Landsat-5 TM that showed a good correlation with the Colored Dissolved Organic Matter (CDOM) absorption coefficient at 355 nm (ag355) (R2 = 0.74). Landsat-derived CDOM maps generally captured the major details of CDOM distribution and seasonal influences, suggesting the potential use of Landsat imagery to monitor biogeochemistry in coastal water environments. An investigation of the seasonal variation in ag355 conducted using Landsat-derived ag355 as well as field data suggested the strong influence of seasonality in the different regions of the bay with the marine end members (lower bay) experiencing generally low but highly variable ag355 and the freshwater end members (upper bay) experiencing high ag355 with low variability. Barataria Bay experienced a significant increase in ag355 during the freshwater release at the Davis Pond Freshwater Diversion (DPFD) following the Deep Water Horizon oil spill in 2010 and following the Mississippi River (MR) flood conditions in 2011, resulting in a weak linkage to salinity in comparison to the other seasons. Tree based statistical analysis showed the influence of high river flow conditions, high- and low-pressure systems that appeared to control ag355 by ~28%, 29% and 43% of the time duration over the study period at the marine end member just outside the bay. An analysis of CDOM variability in 2010 revealed the strong influence of the MR in controlling CDOM abundance in the lower bay during the high flow conditions, while strong winds associated with cold fronts significantly increase CDOM abundance in the upper bay, thus revealing the important role these events play in the CDOM dynamics of the bay

Potential of MODIS EVI in Identifying Hurricane Disturbance to Coastal Vegetation in the Northern Gulf of Mexico

Frequent hurricane landfalls along the northern Gulf of Mexico, in addition to causing immediate damage to vegetation, also have long term effects on coastal ecosystem structure and function. This study investigated the utility of using time series enhanced vegetation index (EVI) imagery composited in MODIS product MOD13Q1 for assessing hurricane damage to vegetation and its recovery. Vegetation in four US coastal states disturbed by five hurricanes between 2002 and 2008 were explored by change imagery derived from pre- and post-hurricane EVI data. Interpretation of the EVI changes within months and between years distinguished a clear disturbance pattern caused by Hurricanes Katrina and Rita in 2005, and a recovering trend of the vegetation between 2005 and 2008, particularly within the 100 km coastal zone. However, for Hurricanes Gustav, Ike, and Lili, the disturbance pattern which varied by the change imagery were not noticeable in some images due to lighter vegetation damage. The EVI pre- and post-hurricane differences between two adjacent years and around one month after hurricane disturbance provided the most likely damage area and patterns. The study also revealed that as hurricanes damaged vegetation in some coastal areas, strong precipitation associated with these storms may benefit growth of vegetation in other areas. Overall, the study illustrated that the MODIS product could be employed to detect severe hurricane damage to vegetation, monitor vegetation recovery dynamics, and assess benefits of hurricanes to vegetation

Short-term Influences on Suspended Particulate Matter Distribution in the Northern Gulf of Mexico: Satellite and Model Observations

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A Two Decadal (1993–2012) Numerical Assessment of Sediment Dynamics in the Northern Gulf of Mexico

We adapted the coupled ocean-sediment transport model to the northern Gulf of Mexico to examine sediment dynamics on seasonal-to-decadal time scales as well as its response to decreased fluvial inputs from the Mississippi-Atchafalaya River. Sediment transport on the shelf exhibited contrasting conditions in a year, with strong westward transport in spring, fall, and winter, and relatively weak eastward transport in summer. Sedimentation rate varied from almost zero on the open shelf to more than 10 cm/year near river mouths. A phase shift in river discharge was detected in 1999 and was associated with the El Niño-Southern Oscillation (ENSO) event, after which, water and sediment fluxes decreased by ~20% and ~40%, respectively. Two sensitivity tests were carried out to examine the response of sediment dynamics to high and low river discharge, respectively. With a decreased fluvial supply, sediment flux and sedimentation rate were largely reduced in areas proximal to the deltas, which might accelerate the land loss in down-coast bays and estuaries. The results of two sensitivity tests indicated the decreased river discharge would largely affect sediment balance in waters around the delta. The impact from decreased fluvial input was minimum on the sandy shoals ~100 km west of the Mississippi Delta, where deposition of fluvial sediments was highly affected by winds

Estimation of Cyanobacterial Pigments in a Freshwater Lake using OCM Satellite Data

Cyanobacteria represent a major harmful algal group in fresh to brackish water environments. Lac des Allemands, a freshwater lake of 49 km2 southwest of New Orleans, Louisiana on the upper end of the Barataria Estuary, provides a natural laboratory for remote characterization of cyanobacterial blooms because of their seasonal occurrence. The Oceansat-1 satellite Ocean Colour Monitor (OCM) provides measurements similar to SeaWiFS but with higher spatial resolution, and this work is the first attempt to use OCM measurements to quantify cyanobacterial pigments. The satellite signal was first vicariously calibrated using SeaWiFS as a reference, and then corrected to remove the atmospheric effects using a customized atmospheric correction procedure. Then, empirical inversion algorithms were developed to convert the OCM remote sensing reflectance (Rrs) at bands 4 and 5 (centered at 510.6 and 556.4 nm, respectively) to concentrations of phycocyanin (PC), the primary cyanobacterial pigment. A holistic approach was used to minimize the influence of other optically active constituents on the PC algorithm. Similarly, empirical algorithms to estimate chlorophyll a (Chl a) concentrations were developed using OCM bands 5 and 6 (centered at 556.4 and 669 nm, respectively). The best PC algorithm (R2 = 0.7450, p \u3c 0.0001, n = 72) yielded a root mean square error (RMSE) of 36.92 μg/L with a relative RMSE of 10.27% (PC from 2.75 to 363.50 μg/L, n = 48). The best algorithm for Chl a (R2 = 0.7510, p \u3c 0.0001, n = 72) produced an RMSE of 31.19 μg/L with a relative RMSE of 16.56% (Chl a from 9.46 to 212.76 μg/L, n = 48). While more field data are required to further validate the long-term performance of these algorithms, currently they represent the best protocol for establishing a long time-series of cyanobacterial blooms in the Lac des Allemands using OCM data