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Research Interests: Environmental Science, Oceanography, Medicine, Multidisciplinary, Erosion, and 4 moreSediment, Estuary, Shore, and Bay
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This data repository is a permanent archive of the results presented in the associated publication (Turner et al. 2020, Science of the Total Environment, doi: 10.1016/j.scitotenv.2021.145157). The objective of this study was to... more
This data repository is a permanent archive of the results presented in the associated publication (Turner et al. 2020, Science of the Total Environment, doi: 10.1016/j.scitotenv.2021.145157). The objective of this study was to investigate the effects of shoreline erosion on water clarity in the Chesapeake Bay. To this end, we used the Chesapeake Bay ROMS Estuarine Carbon and Biogeochemistry (ChesROMS-ECB), a biogeochemical model embedded in the Regional Ocean Modeling System (ROMS). Using this model, we simulated a Chesapeake Bay estuary from 2001-2005 with varying magnitudes of sediment inputs from shoreline erosion and varying seabed erodibility conditions. Model results were compared to long-term cruise data from the Chesapeake Bay Program (CBP) (https://datahub.chesapeakebay.net/). These cruise data were used to calibrate certain components of the model and to evaluate model skill for the Reference Run. Three model runs are compared in the associated publication.Specifically, a Reference Run was used which most closely matched observed conditions, while a More Shoreline Erosion model run used double the realistic shoreline sediment inputs with a more erodible seabed, and a Highly Armored Shorelines model run used no shoreline erosion sediment inputs and a more stable seabed. The full results of these model runs are described in the associated publication
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Research Interests: Geochemistry, Oceanography, Time Series, High Frequency, Plankton, and 15 moreData Collection, Iron, Mathematical Models, Species Composition, Ammonium Nitrate, Solar radiation, Primary Production, Mathematical Model, Equatorial waves, Biological Process, Pacific ocean, Marine ecosystem, Nutrient Concentration, ecosystem model, and Model simulation
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Research Interests: Carbon Cycle and Land Use
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We used a process-based land Mode, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH4+), nitrate (NO3), dissolved organic nitrogen (DON), and particulate organic... more
We used a process-based land Mode, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH4+), nitrate (NO3), dissolved organic nitrogen (DON), and particulate organic nitrogen (PON) from eastern North America, especially the drainage areas of the Gulf of Maine (GOM), Mid-Atlantic Bight (MAB), and South Atlantic Bight (SAB) during 1901–2008. Model simulations indicated that annual fluxes of NH 4 + , NO 3 À , DON, and PON from the study area during 1980–2008 were 0.019 ± 0.003 (mean ± 1 standard deviation) Tg N yr À1 , 0.18 ± 0.035 Tg N yr À1 , 0.10 ± 0.016 Tg N yr À1 , and 0.043 ± 0.008 Tg N yr À1 , respectively. NH 4 + , NO 3 À , and DON exports increased while PON export decreased from 1901 to 2008. Nitrogen export demonstrated substantial spatial variability across the study area. Increased NH 4 + export mainly occurred around major cities in the MAB. NO 3 À export increased in most parts of the MAB but decreased in parts of the GOM. Enhanced DON export was mainly distributed in the GOM and the SAB. PON export increased in coastal areas of the SAB and northern parts of the GOM but decreased in the Piedmont areas and the eastern parts of the MAB. Climate was the primary reason for interannual variability in nitrogen export; fertilizer use and nitrogen deposition tended to enhance the export of all nitrogen species; livestock farming and sewage discharge were also responsible for the increases in NH 4 + and NO 3 À fluxes; and land cover change (especially reforestation of former agricultural land) reduced the export of the four nitrogen species.
We used a process-based land Mode, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH 4 +), nitrate (NO 3 À), dissolved organic nitrogen (DON), and particulate... more
We used a process-based land Mode, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH 4 +), nitrate (NO 3 À), dissolved organic nitrogen (DON), and particulate organic nitrogen (PON) from eastern North America, especially the drainage areas of the Gulf of Maine (GOM), Mid-Atlantic Bight (MAB), and South Atlantic Bight (SAB) during 1901–2008. Model simulations indicated that annual fluxes of NH 4 + , NO 3 À , DON, and PON from the study area during 1980–2008 were 0.019 ± 0.003 (mean ± 1 standard deviation) Tg N yr À1 , 0.18 ± 0.035 Tg N yr À1 , 0.10 ± 0.016 Tg N yr À1 , and 0.043 ± 0.008 Tg N yr À1 , respectively. NH 4 + , NO 3 À , and DON exports increased while PON export decreased from 1901 to 2008. Nitrogen export demonstrated substantial spatial variability across the study area. Increased NH 4 + export mainly occurred around major cities in the MAB. NO 3 À export increased in most parts of the MAB but decreased in parts of the GOM. Enhanced DON export was mainly distributed in the GOM and the SAB. PON export increased in coastal areas of the SAB and northern parts of the GOM but decreased in the Piedmont areas and the eastern parts of the MAB. Climate was the primary reason for interannual variability in nitrogen export; fertilizer use and nitrogen deposition tended to enhance the export of all nitrogen species; livestock farming and sewage discharge were also responsible for the increases in NH4+ and NO3 fluxes; and land cover change (especially reforestation of former agricultural land) reduced the export of the four nitrogen species.
As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D... more
As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and bio-geochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratifica-tion, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen pa-rameterizations, in contrast to the more complex full bio-geochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesa-peake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient .
The overall size of the ''dead zone'' within the main stem of the Chesapeake Bay and its tidal tributaries is quantified by the hypoxic volume (HV), the volume of water with dissolved oxygen (DO) less than 2 mg/L. To improve estimates of... more
The overall size of the ''dead zone'' within the main stem of the Chesapeake Bay and its tidal tributaries is quantified by the hypoxic volume (HV), the volume of water with dissolved oxygen (DO) less than 2 mg/L. To improve estimates of HV, DO was subsampled from the output of 3-D model hindcasts at times/locations matching the set of 2004–2005 stations monitored by the Chesapeake Bay Program. The resulting station profiles were interpolated to produce bay-wide estimates of HV in a manner consistent with nonsynoptic, cruise-based estimates. Interpolations of the same stations sampled synoptically, as well as multiple other combinations of station profiles, were examined in order to quantify uncertainties associated with interpolating HV from observed profiles. The potential uncertainty in summer HV estimates resulting from profiles being collected over 2 weeks rather than synoptically averaged $5 km 3. This is larger than that due to sampling at discrete stations and interpolating/extrapolating to the entire Chesapeake Bay (2.4 km 3). As a result, sampling fewer, selected stations over a shorter time period is likely to reduce uncertainties associated with interpolating HV from observed profiles. A function was derived that when applied to a subset of 13 stations, significantly improved estimates of HV. Finally, multiple metrics for quantifying bay-wide hypoxia were examined, and cumulative hypoxic volume was determined to be particularly useful, as a result of its insensitivity to temporal errors and climate change. A final product of this analysis is a nearly three-decade time series of improved estimates of HV for Chesapeake Bay.