Investigation of Colored Dissolved Organic Matter and Dissolved Organic Carbon Using Combination of Ocean Color Data and Numerical Model in the Northern Gulf of Mexico

The first part of this thesis includes evaluating and developing empirical band ratio algorithms for the estimation of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) for SeaWiFS, MODIS and MERIS ocean color sensors for the northern Gulf of Mexico. For CDOM, matchup comparison between SeaWiFS-derived CDOM absorption coefficients and in situ absorption measurements at 412 nm (aCDOM(412)) were examined using the D’Sa et al. (2006) and the Mannino et al. (2008) algorithms. These reflectance band ratio algorithms were also assessed to retrieve aCDOM(412) from MODIS and MERIS data using the Rrs(488)/Rrs(555) and Rrs(510)/Rrs(560) band ratios, respectively. Since DOC cannot be measured directly by remote sensors, CDOM as the colored component of DOC is utilized as a proxy to estimate DOC remotely. A seasonal relationship between CDOM and DOC was established for the summer and spring-winter with high correlation for both periods. Seasonal band ratio empirical algorithms to estimate DOC were thus developed. In the second part of this study, a numerical model to study CDOM dynamics in the northern Gulf of Mexico was examined. To derive surface CDOM concentration maps from simulated salinity output from the Navy Coastal Ocean Model (NCOM), a highly correlated linear inverse relationship between CDOM and salinity is required which was examined for both inner-shelf and outer-shelf areas for the spring-winter and the summer periods. Applying these relationships on NCOM simulated salinity resulted in hourly maps of CDOM exhibiting high consistency with CDOM patterns derived from SeaWiFS sensor. Overlaying the NCOM-derived CDOM maps on the simulated currents showed the profound effect of currents on CDOM advection. Cold fronts strongly impact CDOM advection in both the inner and outer shelves by flushing CDOM-laden waters out of the coastal bays

Dissolved organic carbon fluxes in the Middle Atlantic Bight: An integrated approach based on satellite data and ocean model products

Continental margins play an important role in global carbon cycle, accounting for 15-21% of the global marine primary production. Since carbon fluxes across continental margins from land to the open ocean are not well constrained, we undertook a study to develop satellite algorithms to retrieve dissolved organic carbon (DOC) and combined these satellite data with physical circulation model products to quantify the shelf boundary fluxes of DOC for the U.S. Middle Atlantic Bight (MAB). Satellite DOC was computed through seasonal relationships of DOC with colored dissolved organic matter absorption coefficients, which were derived from an extensive set of in situ measurements. The multiyear time series of satellite-derived DOC stocks (4.9TeragramsC; Tg) shows that freshwater discharge influences the magnitude and seasonal variability of DOC on the continental shelf. For the 2010-2012 period studied, the average total estuarine export of DOC into the MAB shelf is 0.77TgCyr(-1) (year). The integrated DOC tracer fluxes across the shelf boundaries are 12.1TgCyr(-1) entering the MAB from the southwest alongshore boundary, 18.5TgCyr(-1) entering the MAB from the northeast alongshore boundary, and 29.0TgCyr(-1) flowing out of the MAB across the entire length of the 100m isobath. The magnitude of the cross-shelf DOC flux is quite variable in time (monthly) and space (north to south). The highly dynamic exchange of water along the shelf boundaries regulates the DOC budget of the MAB at subseasonal time scales

Remote Sensing of Harmful Algal Blooms in the Mississippi Sound and Mobile Bay: Modelling and Algorithm Formation

The incidence and severity of harmful algal blooms have increased in recent decades, as have the economic effects of their occurrence./The diatom Pseudo-nitzschia spp. caused fisheries closures in Mobile Bay during 2005 due to elevated levels of domoic acid. In the previous 4 years Karenia brevis counts of \u3e5,000 cells L 1 have occurred in Mobile Bay and the Mississippi Sound. Population levels of this magnitude had previously been recorded only in 1996. Increases in human populations, urban sprawl, development of shoreline properties, sewage effluent and resultant changes in NP ratios of discharge waters, and decline in forest and marsh lands, will potentially increase future harmful algal bloom occurrences in the northern Gulf of Mexico. Due to this trend in occurrence of harmful algal populations, there has been an increasing awareness of the need for development of monitoring systems in this region. Traditional methods of sampling have proven costly in terms of time and resources, and increasing attention has been turned toward use of satellite data in phytoplankton monitoring and prediction. This study shows that remote sensing does have utility in monitoring and predicting locations of phytoplankton blooms in this region. It has described the composition and spatial and temporal relationships of these populations, inferring salinity, total nitrogen and total phosphorous as the primary variables driving phytoplankton populations in Mobile Bay and the Mississippi Sound. Diatoms, chlorophytes, cryptophytes, and dinoflagellates were most abundant in collections. Correlations between SeaWiFS, MODIS and in situ data have shown relationships between Rrs reflectance and phytoplankton populations. These data were used in formation of a decision tree model predicting environmental conditions conducive to the formation of phytoplankton blooms that is driven completely by satellite data. Empirical algorithms were developed for prediction of salinity, based on Rrs ratios of 510 nm/ 555 nm, creating a new data product for use in harmful algal bloom prediction. The capacity of satellite data for rapid, synoptic coverage shows great promise in supplementing future efforts to monitor and predict harmful algal bloom events in the increasingly eutrophic waters of Mobile Bay and the Mississippi Sound

Evaluation of Remote Sensing Methods as Proxy for Salinity Measurements in the Lower Mekong Delta

No abstract availabl

Alkalinity and Buffering in Estuarine, Coastal and Shelf Waters

As anthropogenic climate change continues to elevate the amount of carbon dioxide (CO2) in the Earth’s atmosphere, the absorption of a large portion of this CO2 by Earth’s oceans has resulted in a steady decrease in pH. The consequent phenomenon of ocean acidification (OA) is a result of shifts in the carbonate chemistry system of the ocean- a system which can be analytically described by several factors, including total alkalinity (TA). TA in the oceans has been measured for over a century, but analytical and operational constraints have limited these measurements in time and space. Additionally, recent work has highlighted gaps in our knowledge of the species which collectively comprise TA. This dissertation describes efforts to examine TA through several novel applications: by deploying an automated TA analyzer aboard a survey vessel to map East Coast USA TA distributions, using the same analyzer in a long-term fixed coastal location to build a timeseries and examine seasonal biogeochemical dynamics, and measuring the concentrations and properties of the poorly understood organic component of TA in two Gulf of Maine estuaries. East Coast regional distributions of salinity (S) and TA generally agreed with prior findings, but linear TA:S regressions varied markedly over time and deviated from previously developed models. This variability is likely due to a combination of biological, seasonal, and episodic influences and indicates that substantial errors of ±10-20 μmol kg−1 in TA estimation from S can be expected due to these factors. This finding has likely implications for numerical ecosystem modeling and inorganic carbon system calculations. New results presented in Chapter 1 provide refined surface TA:S relationships, present more data in space and time, and improve TA modeling uncertainty. Coastal timeseries observations were collected hourly over 28 months representing all seasons between May 2016 and December 2019. Results presented in Chapter 2 indicated that endmember mixing explained most of the observed variability in TA and dissolved inorganic carbon (DIC), concentrations of which varied strongly with season. For much of the year, mixing dictated the relative proportions of salinity-normalized TA and DIC as well, but a fall season shift in these proportions indicated that aerobic respiration was observed, which would decrease buffering (β-H) by decreasing TA and increasing DIC. However, fall was also the season of weakest statistical correspondence between salinity and both TA and DIC, as well as the overall highest salinity, TA and β-H. Potential biogeochemically-driven β-H decreases were overshadowed by increased buffering capacity supplied by coastal ocean water. A simple modeling exercise showed that mixing processes controlled most monthly change in TA and DIC, obscuring impacts from air-sea exchange or metabolic processes. Advective mixing contributions, more than biogeochemically-driven changes, are critical to observe when evaluating local estuarine and coastal ocean acidification. Chapter 3 describes the first comparison study of both organic alkalinity (OrgAlk) distributions and acid-base properties in contrasting Gulf of Maine estuary-plume systems: the Pleasant (Maine USA) and St. John (New Brunswick CA). Four surveys of each estuary were conducted between May 2018 and October 2019. Substantial amounts of OrgAlk were measured in each estuary, whose distributions were sometimes not conservative with salinity. Two measures of OrgAlk produced consistently differing results, indicating acid-base characteristics that may be inconsistent with the definition of TA. OrgAlk and dissolved organic carbon (DOC) concentrations varied seasonally in the St. John Estuary, but not in the St. John. The fraction of TA represented by OrgAlk ranged from a maximum of 78% at low salinity in the St. John Estuary to less than 0.4% at the coastal ocean endmember. While the range of St. John OrgAlk concentrations was comparable to other studies, the St. John Estuary demonstrated a broader distribution. The acid dissociation constant (pKa) of the estuary samples was modeled according to a combined speciation and mixing approach, while the organic carbon acid dissociation constant (pKDOC) was estimated using a separate method. Results showed general agreement, but with some notable exceptions in the St. John estuary. OrgAlk modeling results from the Pleasant Estuary were more consistent than the St. John, despite St. John OrgAlk, DOC and pH results exhibiting much less seasonal variability. The mean OrgAlk pKa was higher in the Pleasant than in the St. John, while the mean Pleasant pKDOC was higher or lower than that in the St. John depending on which OrgAlk analysis approach was employed. Application of a bulk pKa or pKDOC to model OrgAlk from more common measurements such as pH, salinity, or DOC may offer promise (as in the Pleasant), but should be undertaken with caution as variability can pose challenges (as in the St. John). Future work should blend the analyses described in the chapters of this dissertation. For example, by collecting discrete samples aboard the survey vessel or at the coastal laboratory organic alkalinity contributions could be used to refine carbonate system calculations. Regional shifts in TA:S could be used to differentiate local and remote coastal endmember TA shifts. While this work utilized novel TA and OrgAlk analyses in three specific applications, the applicability of these analyses is broad and offers the potential to greatly enhance monitoring efforts and ecosystem biogeochemical studies

Studies of net community productivity in a near-coastal temperate ecosystem

Understanding the biological contribution to the carbon cycle is important to accurately calculate oceanic carbon budgets. The biological contribution to air-sea flux can be expressed as net community productivity (NCP), or the difference between gross primary production and community respiration. This study conducted two experiments to constrain NCP in a near-coastal region. The first experiment conducted in the western Gulf of Maine (GoM) sought to identify an indirect optical proxy for NCP that would allow for the determination of NCP remotely by satellite in the future. NCP results indicated that the GoM was near equilibrium during our study. Changes in particulate organic carbon inventory derived from beam attenuation proved to be the most robust proxy of NCP. The second experiment evaluated a novel custom-built autonomous incubation instrument for continuous NCP and respiration measurement in the Piscataqua Estuary Inlet. Although some questionable data patterns were occasionally observed, NCP and respiration rates correlated well with the literature where good data was recorded

The Observation, Modeling, and Retrieval of Bio-Optical Properties for Coastal Waters of the Southern Chesapeake Bay

The primary purpose of this study was to develop an inverse method to retrieve the inherent optical properties (IOPs) and biogeochemical parameters (e.g. chlorophyll a concentration and salinity) appropriate to monitor the water quality and biogeochemical processes from remote sensing of the coastal waters in the southern Chesapeake Bay and coastal Mid-Atlantic Bight region (MAB) dominated by Case 2 waters. For this purpose, knowledge of the relationship between remote sensing reflectance (Rrs) and IOPs and the effect from bottom reflectance on Rrs, is required. A substantial investigation of IOPs has been conducted for the coastal waters of the southern Chesapeake Bay. Although phytoplankton are the dominant contributors to IOPs of oceanic Case 1 waters, colored dissolved organic matter (CDOM) derived from non-phytoplankton sources and sedimentary particles also play very important roles in coastal Case 2 waters. Strongly influenced by riverine discharge, the shallow coastal waters of the southern Chesapeake Bay provide challenges and opportunities to develop regionally specific IOP retrieval methods from remotely sensed ocean color imagery. A semi-analytical radiative transfer model (PZ06_Ed), based on the analysis of the simulated results of an exact radiative transfer model, Hydrolight® [Mobley, 1994], was developed to estimate the vertical distribution of downwelling plane irradiance [Ed(z)] from IOPs and sky conditions (e.g. cloud coverage and solar zenith angle). Compared to the significant overestimation of the simple Gordon [1989] model for particle-rich environments, PZ06_Ed agreed with Hydrolight® with \u3c 6% of the root-mean-square (RMS) error. Field observations from the coastal waters of the southern Chesapeake Bay validated the predictions of PZ06_ Edwith RMS error from 10% to 14%. The SeaWiFS imagery of the diffuse attenuation coefficient (Kd) estimated from PZ06_Ed is significantly improved from the Mueller [2000] model and displays obviously the coastal processes in the lower MAB, including the riverine outflow from the Chesapeake Bay and the mixing of the Gulf Stream with the local waters. The quadratic model (e.g. GSMO1) describing Rrs and IOPs has been widely used in bio-optics to retrieve inherent optical properties (IOPs). In this study, the derived coefficients (l1 and l2) by Gordon et al. [1988] were re-evaluated from Hydrolight® simulations and incorporated into a semi-analytical radiative transfer model (PZ06_ Rrs) that included bottom effects for optically shallow waters. Compared with Hydrolight® simulations and field observations in the Chesapeake Light Tower (CLT), Rrs calculated from PZ06_Rrs typically agreed within 5% and about 7% to 13% of RMS, respectively. Hydrolight ® simulations and field observations also confirmed that PZ06_Rrs improved the retrieval of biogeochemical-related parameters, including [Chl], adg(443), and bbp(443), compared to global ocean color algorithms (e.g. OC3M) and semi-analytic models without considering the bottom effects (e.g. GSM01-CLT). Finally, the relatively successful inverse modeling provides a promising method to study ecosystem-level biogeochemical and physical parameters from remote sensing for coastal waters of southern Chesapeake Bay and even lower MAB

Red Tides In the Gulf of Mexico: Where, When, and Why?

Independent data from the Gulf of Mexico are used to develop and test the hypothesis that the same sequence of physical and ecological events each year allows the toxic dinoflagellate Karenia brevis to become dominant. A phosphorus-rich nutrient supply initiates phytoplankton succession, once deposition events of Saharan iron-rich dust allow Trichodesmium blooms to utilize ubiquitous dissolved nitrogen gas within otherwise nitrogen-poor sea water. They and the co-occurring K. brevis are positioned within the bottom Ekman layers, as a consequence of their similar diel vertical migration patterns on the middle shelf. Upon onshore upwelling of these near-bottom seed populations to CDOM-rich surface waters of coastal regions, light-inhibition of the small red tide of similar to 1 ug chl l(-1) of ichthytoxic K. brevis is alleviated. Thence, dead fish serve as a supplementary nutrient source, yielding large, self-shaded red tides of similar to 10 ug chl l(-1). The source of phosphorus is mainly of fossil origin off west Florida, where past nutrient additions from the eutrophied Lake Okeechobee had minimal impact. In contrast, the P-sources are of mainly anthropogenic origin off Texas, since both the nutrient loadings of Mississippi River and the spatial extent of the downstream red tides have increased over the last 100 years. During the past century and particularly within the last decade, previously cryptic Karenia spp. have caused toxic red tides in similar coastal habitats of other western boundary currents off Japan, China, New Zealand, Australia, and South Africa, downstream of the Gobi, Simpson, Great Western, and Kalahari Deserts, in a global response to both desertification and eutrophication

Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir

Colored dissolved organic matter (CDOM) in inland waters is used as a proxy to estimate dissolved organic carbon (DOC) and may be a key indicator of water quality and nutrient enrichment. CDOM is optically active fraction of DOC so that remote sensing techniques can remotely monitor CDOM with wide spatial coverage. However, to effectively retrieve CDOM using optical algorithms, it may be critical to select the absorption co-efficient at an appropriate wavelength as an output variable and to optimize input reflectance wavelengths. In this study, we constructed a CDOM retrieval model using airborne hyperspectral reflectance data and a machine learning model such as random forest. We evaluated the best combination of input wavelength bands and the CDOM absorption coefficient at various wavelengths. Seven sampling events for airborne hyperspectral imagery and CDOM absorption coefficient data from 350 nm to 440 nm over two years (2016-2017) were used, and the collected data helped train and validate the random forest model in a freshwater reservoir. An absorption co-efficient of 355 nm was selected to best represent the CDOM concentration. The random forest exhibited the best performance for CDOM estimation with an R2 of 0.85, Nash-Sutcliffe efficiency of 0.77, and percent bias of 3.88, by using a combination of three reflectance bands: 475, 497, and 660 nm. The results show that our model can be utilized to construct a CDOM retrieving algorithm and evaluate its spatiotemporal variation across a reservoir

Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 32 (2018): 389-416, doi:10.1002/2017GB005790.Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.NASA Interdisciplinary Science program Grant Number: NNX14AF93G; NASA Carbon Cycle Science Program Grant Number: NNX14AM37G; NASA Ocean Biology and Biogeochemistry Program Grant Number: NNX11AD47G; National Science Foundation's Chemical Oceanography Program Grant Number: OCE‐12605742018-10-0