Responses of estuarine salinity and transport processes to potential future sea-level rise in the Chesapeake Bay

Hong, Bo; Shen, Jian

doi:10.1016/j.ecss.2012.03.014

Cited by 183 publications

(138 citation statements)

References 30 publications

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“…Equation 9 indicates that H is very important and salinity intrusion length is very sensitive to the tidal range. The power of h in this equation is 0.5, which is supported by the findings of Hong and Shen (2012) in Chesapeake Bay. In brief, the salinity intrusion length is very sensitive to any SLR as it impacts directly on the average depth.…”

Section: Development Of An Equation For the Salinity Intrusion Lengthsupporting

confidence: 72%

Effects of sea level rise on the salinity of Bahmanshir estuary

Etemad‐Shahidi

Rohani

Parsa

et al. 2015

Int. J. Environ. Sci. Technol.

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Bahmanshir estuary, which is connected to the Persian Gulf, is one of the most important water resources in region. In this study, saltwater intrusion due to possible sea level rise in the Bahmanshir estuary was investigated. A one-dimensional hydrodynamic and water quality model was used for the simulation of the salinity intrusion and associated water quality, with measured field data being used for model calibration and verification. The verified model was then used as a virtual laboratory to study the effects of different parameters on the salinity intrusion. A coupled gas-cycle/climate model was used to generate the climate change scenarios in the studied area that showed sea level rises varying from 30 to 90 cm for 2100. The models were then combined to assess the impact of future sea level rise on the salinity distribution in the Bahmanshir estuary. Using important dimensionless numbers, a dimensionally homogenous equation was subsequently developed for the prediction of the salinity intrusion length, showing that the salinity intrusion length is inversely correlated with the discharge and directly with the sea level rise. In addition, the magnitude and frequency of the salinity standard violations at the pump station were predicted for 2100, showing that the salinity violations under climate change effects can increase to 45 % of the times at this location. This reveals the importance of this type of approach for considering future infrastructure management.

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Section: Development Of An Equation For the Salinity Intrusion Lengthsupporting

confidence: 72%

Effects of sea level rise on the salinity of Bahmanshir estuary

Etemad‐Shahidi

Rohani

Parsa

et al. 2015

Int. J. Environ. Sci. Technol.

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“…Sea-level rise can cause saline water to migrate upstream to points where freshwater existed previously (e.g., National Research Council, 1987;Grabemann et al, 2001;Poff et al, 2002). Several studies indicate that sea-level rise will increase the salinity in estuaries (e.g., Hull and Tortoriello, 1979;Hilton et al, 2008;Bhuiyan and Dutta, 2011), which will result in changes in stratification and estuarine circulation (Hong and Shen, 2012). Such salinity migration could cause shifts in salt-sensitive habitats, thereby affecting the distribution of flora and fauna, and affect water availability for municipal supply, irrigation, and industrial uses.…”

Section: Introductionmentioning

confidence: 98%

Assessment of salinity intrusion in the James and Chickahominy Rivers as a result of simulated sea-level rise in Chesapeake Bay, East Coast, USA

Rice

Hong

Shen

2012

Journal of Environmental Management

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“…Model D employs a ROMS implementation for the Chesapeake Bay based on M. Li et al (2005), while Model G uses the ROMS-based Chesapeake Bay Operational Forecast System (CBOFS; Lanerolle et al, 2011). Models A, E, and H each use a different hydrodynamic base model: the Curvilinear Hydrodynamics in Three Dimensions model (CH3D; Cerco et al, 2010), the FiniteVolume Community Ocean Model (FVCOM; Jiang and Xia, 2016), and the Hydrodynamic Eutrophication Model -Environmental Fluid Dynamics Code (EFDC; Park et al, 1995;Hong and Shen, 2012;Du and Shen, 2015), respectively. The only model that employs a non-sigma vertical grid is Model A and the only model utilizing an unstructured horizontal grid is Model E. While Model E contains 10 sigma vertical layers, all of the other sigma grids use 20 layers.…”

Section: Participating Chesapeake Bay Modelsmentioning

confidence: 99%

Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

Irby

Friedrichs

et al. 2016

Biogeosciences

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Abstract. 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 biogeochemical 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 (stratification, 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 parameterizations, in contrast to the more complex full biogeochemical 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 Chesapeake 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.

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Responses of estuarine salinity and transport processes to potential future sea-level rise in the Chesapeake Bay

Cited by 183 publications

References 30 publications

Effects of sea level rise on the salinity of Bahmanshir estuary

Effects of sea level rise on the salinity of Bahmanshir estuary

Assessment of salinity intrusion in the James and Chickahominy Rivers as a result of simulated sea-level rise in Chesapeake Bay, East Coast, USA

Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

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