2014
DOI: 10.2112/jcoastres-d-12-00015.1
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Spatial and Temporal Variations in Nutrients and Water-Quality Parameters in the Mississippi River-Influenced Breton Sound Estuary

Abstract: Lundberg, C.J.; Lane, R.R., and Day, J.W., Jr., 2014. Spatial and temporal variations in nutrients and water-quality parameters in the Mississippi River-influenced Breton Sound estuary. Journal of Coastal Research, 30(2), 328-336. Coconut Creek (Florida), ISSN 0749-0208.The purpose of this study is to investigate the long-term temporal and spatial nutrient patterns in the Breton Sound estuary, an estuarine wetland complex in coastal Louisiana that is highly influenced by the Caernarvon river diversion. A water… Show more

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Cited by 13 publications
(10 citation statements)
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“…The development of catchment typologies based on solute export behaviour and hysteresis could be useful for the transfer of information from data-rich to data-poor catchments [74], for impact assessment of climate, environmental and management changes on water quality and for parameterisation of water quality models [35]. However, finding the association between the typology presented here and catchment characteristics, e.g., topography, geology, and land use may be challenging owing to the complexity of different responses to both spatial and temporal mechanisms [5,14]. Within-catchment heterogeneity may also affect the links between catchment characteristics and C-Q relationships [23,32,75].…”
Section: Associations Between C-q Types and Catchment Characteristicsmentioning
confidence: 99%
“…The development of catchment typologies based on solute export behaviour and hysteresis could be useful for the transfer of information from data-rich to data-poor catchments [74], for impact assessment of climate, environmental and management changes on water quality and for parameterisation of water quality models [35]. However, finding the association between the typology presented here and catchment characteristics, e.g., topography, geology, and land use may be challenging owing to the complexity of different responses to both spatial and temporal mechanisms [5,14]. Within-catchment heterogeneity may also affect the links between catchment characteristics and C-Q relationships [23,32,75].…”
Section: Associations Between C-q Types and Catchment Characteristicsmentioning
confidence: 99%
“…Removal efficiencies were much greater in March and February than January, associated with factors of temperature and frequency of wetland inundation noted in previous paragraph. These total NO 3 − removal efficiencies are much lower than the 55-86% removal based on changes in NO 3 − concentration in the upper Breton Sound outfall region [26,30,62]. These reported removal efficiencies consider the differences in upstream and downstream concentrations of NO 3 − accounting for dilution using salinity as a conservative constituent.…”
Section: Nitrate Removalmentioning
confidence: 73%
“…Following the fate of NO 3 − during river-pulse events in upper Breton Sound using the methods described in this study does not account for the net flux of total nitrogen (TN) during these events. The loss of TN in the outfall region has been noted to average about 50% [26,30,62], based on the decrease in concentration greater than the dilution with seawater downstream from the diversion input. It is obvious in our few sediment flux observations that while there may be a net uptake of NO 3 − and dissolved inorganic nitrogen (DIN) by subtidal and intertidal soils, there were several observations of significant efflux of DON.…”
Section: Conclusion-ecosystem Designmentioning
confidence: 99%
“…Forcing functions for the Delft3D-WAQ model include freshwater flow, tidal exchange, water temperature, light, wind, and nutrients from the Caernarvon diversion and atmospheric deposition. The BSE water quality model was calibrated and validated using observed data in 2009 on salinity, TSS, and Chl-α at 16 water quality stations (Lane et al, 2007;Day et al, 2009;Lundberg et al, 2014) and 22 LDWF stations (LDWF unpublished data, Fig. 1).…”
Section: Modeling Systemmentioning
confidence: 99%
“…Linking spatial and temporal changes in water quality to oyster growth rate and production requires coupling of hydrodynamic, sediment transport and water quality models with an oyster population model. While studies in BSE have demonstrated that CFD causes changes in the spatial and temporal patterns of temperature, salinity, total suspended solids (TSS), Chl-α, and velocity with large pulses of water released during the springtime (Lane et al, 2007;Lundberg et al, 2014), the highly dynamic and variable water quality makes it difficult to fully capture all of the changes through discrete field sampling. As such, hydrodynamic, sediment transport and water quality modeling is required to fully capture such dynamic changes in space and time with sufficient spatial and temporal resolutions.…”
Section: Introductionmentioning
confidence: 99%