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Dataset card Data Studio Files
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TEMP S Zcusum
NNB TEMP S
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In summary, results from the ATS analysis (Appedix XXX) indicate that salinity
increased in all sub-basins, perhaps responding to reduced freshwater deliveries and
also to sea-level rise. Likewise, TP increased across the Bay but most changes were
small and non-significant. On the other hand, TN declined across de bay, especially in
MBS and SCI. DIN declined in MBS and increased in SCI with other stations
unchanged. TOC consistently dwindled in all sub-basins especially in NNB, NCI and
SCI. This decline of TOC in BB parallels similar TOC drop in the whole South Florida.
Changes along the POC were not linear, but followed variable, sometimes complex
paths with sharp discontinuities. Table 3.3 shows the most important breaks along the
time series obtained from the cusum analysis charts of key biogeochemical parameters.
Links to hurricane impact may be postulated for breaks in 1998 (Hurricanes Georges
and Mitch), 1999 (topical storm Harvey and hurricane Irene) and late 2005 (hurricanes
Katrina, Rita and Wilma). Breaks in early 2002 are the most common and seem to be
related to water management by the SFWMD.
Table 3.3: Year of occurrence of major breaks along the POR for key biogeochemical
parameters in Biscayne Bay
Main breaks
TP TN Sal TOC CHLa DIN DO Temp
Late 1997 X
Late 1998 X X X X
Late 1999 X X X X
Early 2001 X
Early 2002 X X X X X X X X
Early 2004 X
Late 2004 X X
Late 2005 X X X X X
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SECTION 4:
BOX-MODEL SUMMARY
Cetacean Logic Foundation Inc, under FIU Subcontract No. 205500521-01
developed a box-model to estimate nutrient loads to Biscayne Bay from its watershed
and implemented mass-balance calculations to estimate the long-term average nutrient
concentrations in the Bay based on these loads. The study consisted of a series of
steps to: (1) review an existing nutrient loading study, (2) estimate nutrient loads to the
Bay for all water budget components, (3) expand an existing hydrology/salinity model to
utilize the nutrient loads for mass balance calculations, and (4) use the nutrient box
model with estimated loads for future land use scenarios and interpret the output.
The first step in this study was to review nutrient loads previously estimated in an
engineering study performed for Miami-Dade County using land-use coefficients. The
South Miami-Dade Watershed Study and Plan estimated existing and future nutrient
loads to Biscayne Bay based on patterns of land use in south Miami-Dade County.
However, only one component of the Biscayne Bay water and nutrient budget was
characterized and the estimated loads were found to be inconsistent with more recent
information on nutrient loads based from measured water flows and associated nutrient
concentration data, such as work done by Caccia and Boyer (2007).
Because of this, nutrient loads for Total Phosphorous (TP), ammonium (NHx-N),
nitrate-nitrite (NOx-N), and Dissolved Inorganic Nitrogen (DIN) were independently
developed for all components of the water budget (step 2) based on various existing
sources of information, including canals, overland flow (ungauged surface water),
groundwater, and atmospheric contributions. With the exception of freshwater inflows
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and nutrient loads from canals, few direct data exist for estimating these nutrient loads.
Indirect data and regression models were used to fill the data gaps. Nutrient loads
across the boundaries of the model including the Atlantic Ocean were also estimated
from existing data.
Figure 4.1: Components of box-model used for mass-balance calculations
Calculations of nutrient concentrations in Biscayne Bay based on the estimated
loads extended an existing hydrology/salinity mass-balance model (step 3) that had
been developed previously for the South Florida Water Management District. This
model was used to investigate the linkage between freshwater inflows from the
watershed and salinity patterns in the Bay. The model domain and the
hydrology/salinity calculations were upgraded based on peer-review comments and the
model was extended to incorporate mass-balance nutrient calculations. The model was
then calibrated against measured salinity to estimate the water fluxes between each box
and validated against an independent set of salinity observations.
Evaporation
Rainfall
S, A
d
Net
discharge, QO
Evaporation Rainfall
Exchange
flux, QX
Canal Discharge
Runoff and Groundwater
SO Ocean salinity,
Net Freshwater Supply, QR
A