Estuaries and Coasts (2014) 37:493–507 DOI 10.1007/s12237-013-9691-3
Alteration of Residual Circulation Due to Large-Scale Infrastructure in a Coastal Plain Estuary Steven D. Meyers & Amanda J. Linville & Mark E. Luther
Received: 16 May 2012 / Revised: 25 June 2013 / Accepted: 29 July 2013 / Published online: 18 September 2013 # Coastal and Estuarine Research Federation 2013
Abstract Large-scale human-built infrastructure is shown to alter the salinity and subtidal residual flow in a realistic numerical simulation of hydrodynamic circulation in a coastal plain estuary (Tampa Bay). Two model scenarios are considered. The first uses a modern bathymetry and boundary conditions from the years 2001–2003. The second is identical to the first except that the bathymetry is based on depth soundings from the pre-construction year 1879. Differences between the models' output can only result from changes in bay morphology, in particular built infrastructure such as bridges, causeways, and dredging of the shipping channel. Thirty-day means of model output are calculated to remove the dominant tidal signals and allow examination of the subtidal dynamics. Infrastructure is found to steepen the mean axial salinity gradient ∂s=dx by ~40% when there is low freshwater input but flatten ∂s=dx by ~25% under more typical conditions during moderate freshwater inflow to the estuary. Deepening of the shipping channel also increases the magnitude of the residual Eulerian circulation, allowing for larger up-estuary salt transport. Local bathymetry and morphology are important. Some regions within the estuary show little change in residual circulation due to infrastructure. In others, the residual circulation can vary by a factor of 4 or more. Major features of the circulation and changes due to infrastructure can be partially accounted for with linear theory.
Keywords Estuary . Residual circulation . Bathymetry . Fluid–structure interaction . Infrastructure . Exchange flow
S. D. Meyers (*) : M. E. Luther College of Marine Science, University of South Florida, 140 7th Avenue South, St. Petersburg, FL 33701, USA e-mail:
[email protected] Present Address: A. J. Linville 5215 Bernadette Dr., Zephyrhills, FL 33541, USA
Introduction The transport of salt, nutrients, and other biological, chemical, and geological materials within an estuary is often controlled by the exchange circulation (Kim and Voulgaris 2005), which is driven by horizontal density gradients generated by freshwater input from rivers near the estuary head and ocean water at the mouth under the influence of tidal mixing as represented by eddy viscosity (Knudsen 1900; Pritchard 1956; Rattray and Hansen 1962). Exchange velocities are typically an order of magnitude smaller than root mean square (RMS) tidal velocities and given by uE ¼
gβH 3 ∂s 48K M ∂x
ð1Þ
with sðxÞ as the depth-averaged salinity; x is the axial distance from the estuarine head, β (~ 2 × 10−4 psu−1) is the haline contraction coefficient, H is the water depth, and KM is the vertical eddy viscosity. These analytical models, and their variations (Hetland and Geyer 2004; MacCready 2007), are generally restricted to the vertical and axial variations of velocity and salinity. Lateral bathymetry and coastline morphology add spatial complexity to the residual circulation (Valle-Levinson et al. 2003; Winant 2004). Exchange flow in the lateral plane can be modeled analytically through a balance between pressure, friction, and Coriolis (Valle-Levinson 2008). The controlling parameters are the Ekman number Ek=(Az/fH)1/2 and the Kelvin number Ke=B/ Ri, where B is the estuarine width and Ri is the internal Rossby radius of deformation. Under the assumptions that will be specified later, the exchange flow w=u+iv, where u is the axial velocity component, pvffiffiffiffiffiisffi the lateral (cross-estuary) velocity component and i ¼ −1 , is found to be w=giNf-−1F1+F2. Here f is the Coriolis parameter, N is the sea surface slope, N¼
∂η ∂η þi ∂x ∂y
ð2Þ
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y is the lateral (across-estuary) distance, z is the vertical coordinate, and i 1−coshðαzÞ F1 ¼ f coshðαhÞ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi The parameter α ¼ ð1 þ iÞ f =ð2Az Þ is the inverse Ekman depth and h(y) is the bottom depth. Further, iD ðcoshαzÞ F2 ¼ expðαzÞ−ðαzÞ−ðexpðαhÞ þ αhÞ αf ðcoshαhÞ D is the internal pressure (density) gradient g ∂ρ ∂ρ þi D¼ ρ ∂x ∂y
ð3Þ
which is dynamically related to N by Z D¼Z
Rv −αg
B
N ½tanhðαhÞ−αhdy
0 B 0
ðexpð−αhÞ þ αhÞtanhðαhÞ− 1−expð−αhÞ þ
ðαhÞ2 2
!! dy
ð4Þ and the net volume flux is determined by Rv (Valle-Levinson, personal communication). The solution is obtained under the assumption the surface slope N=N0 +iN0 exp[−((y−yc)/Ri)2]. This formulation yields a wide range of structures from classic vertically sheared exchange flow to horizontally sheared exchange flow (Huijts et al. 2009; Valle-Levinson 2008) and has been shown to reproduce major features of the axial residual circulation across one observational transect located in Tampa Bay (TB) (Arnott et al. 2012). Over the past 100 years, many coastal areas have experienced rapid human population growth. In the USA, coastal counties represent just 17% of the land, yet in 2002 they were home to more than half of the nation's people (Beach 2002). This high population density has generated a need for all types of infrastructure including roads, causeways, bridges, and navigational channels. Many of these are built within semienclosed waterways, such as bays and estuaries, directly altering their bathymetry and thereby impacting the exchange flow. Over the coming decades, as population increases, so will the need for additional infrastructure (Beach 2002). Changes in residual circulation are known to impact residence (flushing) times (Oliveira and Baptista 1997), which affect the chemistry (Dettmann 2001) and biological communities (Crump et al. 2004; Josefson and Rasmussen 2000) within estuaries. Identifying and assessing the environmental impacts of urbanization on estuarine systems is essential to managing their ecological health. However, to date, there have
been few peer-reviewed studies on how large-scale engineering of estuaries alters their hydrodynamics, and many of these are restricted to changes in tidal circulation. Some published works are available in grey literature (Galagan et al. 2003; Richards and Granat 1986; Vaughan et al. 2005), and some focus on the impact of future construction (Liu et al. 2005). Perillo et al. (2005) used field measurements and a numerical model to demonstrate changes in circulation and sedimentation in the Quequén Grande River Estuary, Argentina, due to human infrastructure. Coleman et al. (2009) reported on field studies before and after a restoration project in the Golden Horn Estuary, Istanbul, Turkey, where the partial removal of a floating bridge was followed by improved water quality in the estuary. Cuvilliez et al. (2009) observed the reduction in the tidal prism and area of vegetated mudflats in the Seine Estuary, France, due to construction within the estuary. An observational study of the flow in Sheepscot River Estuary, ME, USA, found that tidal flows in the main channel increased by almost 50% following the removal of a causeway (Mcalice and Jaeger 1983). Goodwin (1987) used a 2D hydrodynamic model to simulate tidal flood and ebb velocities and residual transport of both water and dissolved constituents for the physical conditions that existed in TB during the years 1880, 1972, and 1985. The use of a 2D model in that study necessarily precluded the three-dimensional overturning circulation which dominates transport at subtidal time scales. The importance of this baroclinic flow in TB was demonstrated using a model similar to the one used here (Galperin et al. 1991; Galperin et al. 1992) and examined further with a finite volume model by Weisberg and Zheng (2006). This study examines changes to the three-dimensional hydrodynamics of a coastal plain estuary, TB, due to largescale human infrastructure (i.e., bridges, causeways, and dredging) at subtidal timescales. TB contains naturally occurring channels that have been deepened by dredging (Zervas 1993). A major ship channel stretches from the mouth to the upper reaches of Lower Tampa Bay (LTB) and into Middle Tampa Bay (MTB), where it splits into two branches, one entering Old Tampa Bay (OTB) and the other going into Hillsborough Bay (HB) (Fig. 1). Dredging has increased the main channel maximum depths from 10 to 15 m (Vincent 2001). In addition to the dredging, four major bridges now span the Bay: the Courtney Campbell Causeway (CCC), the Howard Franklin Bridge (HFB), the Gandy Bridge (GB), and the Sunshine Skyway Bridge (SSB). Physical alterations like these are expected to influence circulation and transport time in estuaries. These alterations might also influence seagrass and other benthic communities (Lewis et al. 1999). A relatively recent list of studies of the chemical impacts from human activities in TB is available from Swarzenski et al. (2007). Effects of infrastructure on residence time are examined separately (Meyers et al. 2013).
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Fig. 1 Tampa Bay and its major features
A three-dimensional numerical ocean model of Tampa Bay, described in the following section, is used to simulate the circulation for 2001–2003 using present-day bathymetry. Then, an identical simulation is performed using the bathymetry generated from the 1879 depth soundings (Figs. 2 and 3). In ”Results”, model output is examined during three distinct time periods (Table 1) representing three different dynamical regimes and compared to analytical solutions for exchange flow. “Discussion and Conclusions” presents conclusions from these experiments.
Model and Methods The numerical model used here is based on the Estuarine and Coastal Ocean Model (ECOM-3D), a variation of the Princeton Ocean Model (Blumberg and Mellor 1987) and was originally implemented for TB by Vincent (2001). The model is a threedimensional, primitive equation, time-dependent model. Some
basic features are finite element, vertical sigma coordinates, boundary fitted curvilinear grid, a split time step for the solution of the baroclinic 3D mode and the barotropic 2D mode, and an embedded Mellor–Yamada second-order turbulence closure scheme (Mellor and Yamada 1982) to provide vertical kinematic viscosity. A Smagorinsky diffusivity (Smagorinsky 1963) is used for the horizontal diffusion. The model forcing functions are National Oceanic and Atmospheric Administration (NOAA) daily average surface windstress and precipitation, US Geological Survey (USGS) river inflow, elevation at the open boundary from NOAA Physical Oceanographic Real Time System (PORTS), and salinity at the open boundary from the Hillsborough County Environmental Protection Commission. Temperature is set to a uniform 25°C. Detailed discussions of these functions, model calibration, and accuracy have been published previously (Meyers et al. 2007) and hence are briefly summarized: a location far from the forcing boundary in the northeastern region of the model was chosen to compare model elevation
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Fig. 2 Locations of 1879 depth soundings in Tampa Bay as provided by USGS
to observed sea level. The correlation is r=0.91, with a mean error of 0.03 m. Mean salinity errors through the model domain and time of integration are 1.8 psu, and mean velocity errors and mean axial velocity errors are about 0.5 cm/s. Calibration of salinity represents an indirect calibration of velocity as the distribution of salinity is controlled by the velocity field. Two model runs are performed. The first utilizes realistic boundary conditions and a modern bathymetry (“Present”), representing the contemporary circulation. The second model run is identical to the first except that the bathymetry is based on depth soundings from 1879 (“PreC”). By only changing the bathymetric grid, differences in model output between each simulation will solely derive from changes due to construction and dredging. This is not an attempt to recreate the circulation in 1879. Depth soundings from the year 1879 are obtained from the USGS of St. Petersburg Florida (Fig. 2). Active and inactive model grid cells are determined relative to the coastline.
The depth soundings that fall within each active cell are averaged to obtain the depth for that particular cell. Where active cells have no soundings, their depths are interpolated from neighboring cells. The inactive cells are land locations where flow is prohibited. A zero-flow boundary condition is used at land points adjacent to water points. Land cells are added to Hillsborough Bay (where the Hillsborough power plant is now located) because ECOM requires at least one land grid cell adjacent to any freshwater inflow. Some of the largest changes in bathymetry between Present and PreC are seen in HB (Fig. 3). In the Present scenario, the ship channel has been extended to reach upper Hillsborough Bay, increasing the local depth by 3 to 4 m. The depth around Port of Tampa has been deepened by up to 9 m. The natural channels in OTB, MTB, and LTB have also been dredged, resulting in a channel depth increase of about 2 to 3 meters. Eight meters of dredged soil has been added to areas in HB, creating two spoil islands. In OTB, bridges/causeways now
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Fig. 3 Model depth (meters) relative to mean sea level for a Present, b PreC, and c the change Present minus PreC. Location of three vertical transects across the bay are indicated as well as the location of the along-axis sampling
span the bay, resulting in a 9-m bathymetric gain in some areas. The 4-m gain in areas of LTB is the result of the Sunshine Skyway Bridge. Model output for both runs is archived every hour. For simplicity, three 30-day time periods are examined: when changes in circulation due to bathymetric changes are small (T1), moderate (T2), and large (T3). In order to select these times, the RMS of the three-dimensional velocity difference field rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi −1 X 2
δðt Þ ¼ nx ny nz u ðx; y; z; t Þ þ vd 2 ðx; y; z; t Þ ð5Þ xyz d
is calculated every hour, where ud is the difference of the u-component of velocity between Present and PreC ud ðx; y; z; t Þ ¼ uPresent ðx; y; z; t Þ
uPreC ðx; y; z; t Þ
ð6Þ
and x, y, z represent the model's spatial coordinates (Fig. 4). Analogous definitions are applied to vd. All time periods have durations of 30 days. This is sufficiently long to filter out most tidal and synoptic effects but not so long that changing environmental conditions significantly alter the baroclinic circulation. The results presented here are not sensitive to small (~10%) changes in window size.
Results Analyses are presented for three 30-day periods from the 3-year model simulation, T1, T2, and T3. These represent three distinct values of δ(t) (Fig. 4; Table 1), with T1 having the lowest value and T3 the highest. This differs from previous temporal partitions of estuarine circulation which were based on total freshwater inflow (Meyers and Luther 2008). Residual quantities, as defined by their 30-day averages, are analyzed. Salinity and Elevation During T1, salinity throughout the bay is close to the open boundary value in both Present and PreC model runs. There is little spatial variation of Present surface salinity with an average ± standard deviation of S =34.7 ± 0.8 ppt, where the overbar indicates area-weighted spatial average (Fig. 5). The vertical gradient of salinity is negligible (
