Calculate groundwater loads to Tampa Bay segments

Usage

anlz_gw(
  pot_dry,
  pot_wet,
  yrrng = c(2022, 2024),
  wqdat = NULL,
  summtime = c("month", "year")
)

Arguments

pot_dry: SpatRaster (or PackedSpatRaster) of Upper Floridan Aquifer potentiometric head for the dry season, as returned by util_gw_getcontour with season = "dry". The package dataset contdry contains a pre-computed 2022 example.
pot_wet: SpatRaster (or PackedSpatRaster) of Upper Floridan Aquifer potentiometric head for the wet season, as returned by util_gw_getcontour with season = "wet". The package dataset contwet contains a pre-computed 2022 example.
yrrng: integer vector of length 2, start and end year for the load estimates, e.g. c(2022, 2024). The same gradients derived from pot_dry and pot_wet are applied to every year in the range.
wqdat: data frame of Floridan aquifer TN and TP concentrations (mg/L) as returned by util_gw_getwq, with columns bay_seg, tn_mgl, and tp_mgl. When NULL (default), hardcoded concentrations from the 2022-2024 loading analysis are used.
summtime: character, temporal summarization: 'month' (default) returns one row per segment per month, 'year' sums to annual totals.

Value

A data frame with columns:

Year: integer
Month: integer (omitted when summtime = 'year')
source: character, "GW"
segment: character, bay segment name
tn_load: numeric, total nitrogen load (tons/month or tons/year)
tp_load: numeric, total phosphorus load (tons/month or tons/year)
hy_load: numeric, hydrologic load (million m$^3$/month or million m$^3$/year)

Details

Estimates groundwater loads to each Tampa Bay segment for three aquifer layers following the methodology in Zarbock et al. (1994).

Floridan aquifer: Flow is computed with Darcy's Law: $$Q = 7.4805 \times 10^{-6} \cdot T \cdot I \cdot L$$ where $T$ is transmissivity (ft$^2$/day), $I$ is the hydraulic gradient (ft/mile), and $L$ is the flow zone length (miles). $Q$ is in MGD. Nutrient loads (kg/month) are: $$\text{load} = Q \cdot C \cdot 8.342 \cdot 30.5 / 2.2$$ where $C$ is the TN or TP concentration (mg/L). Hydrologic load (m$^3$/month) is $Q \cdot 3785 \cdot 30.5$.

Hydraulic gradients: Gradients are computed once from pot_dry and pot_wet via util_gw_grad and applied to every year in yrrng. Update pot_dry and pot_wet with fresh outputs from util_gw_getcontour when new FDEP potentiometric surface maps become available. See util_gw_grad for details on search areas, zero-gradient segments, and benchmark warnings.

Surficial and intermediate aquifers: Loads are fixed constants per segment. Surficial values are from gwupdate95-98_final.xls (1995-1998 SWFWMD monitoring data). Intermediate values are means from SWFWMD monitoring over 1999-2003. These have not changed since the original analysis.

Season assignment: Months 1-6 and 11-12 are dry season; months 7-10 are wet season.

References

Zarbock, H., A. Janicki, D. Wade, D. Heimbuch, and H. Wilson. 1994. Estimates of Total Nitrogen, Total Phosphorus, and Total Suspended Solids Loadings to Tampa Bay, Florida. Technical Publication #04-94. Prepared by Coastal Environmental, Inc. Prepared for Tampa Bay National Estuary Program. St. Petersburg, FL.

Examples

# contdry and contwet are pre-computed 2022 package datasets
gw <- anlz_gw(contdry, contwet, yrrng = c(2022, 2024))
head(gw)
#>   Year Month source        segment      tn_load     tp_load   hy_load
#> 1 2022     1     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126
#> 2 2022     2     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126
#> 3 2022     3     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126
#> 4 2022     4     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126
#> 5 2022     5     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126
#> 6 2022     6     GW Boca Ciega Bay 0.0004188783 0.003957298 0.0132126

# annual totals
anlz_gw(contdry, contwet, yrrng = c(2022, 2024), summtime = 'year')
#>    Year source          segment     tn_load    tp_load    hy_load
#> 1  2022     GW   Boca Ciega Bay  0.00502654 0.04748757  0.1585512
#> 2  2023     GW   Boca Ciega Bay  0.00502654 0.04748757  0.1585512
#> 3  2024     GW   Boca Ciega Bay  0.00502654 0.04748757  0.1585512
#> 4  2022     GW Hillsborough Bay 19.88198988 2.37177288 70.9236779
#> 5  2023     GW Hillsborough Bay 19.88198988 2.37177288 70.9236779
#> 6  2024     GW Hillsborough Bay 19.88198988 2.37177288 70.9236779
#> 7  2022     GW  Lower Tampa Bay  0.10842020 0.61693145  3.7816227
#> 8  2023     GW  Lower Tampa Bay  0.10842020 0.61693145  3.7816227
#> 9  2024     GW  Lower Tampa Bay  0.10842020 0.61693145  3.7816227
#> 10 2022     GW    Manatee River  0.13199801 0.64376879  4.5718074
#> 11 2023     GW    Manatee River  0.13199801 0.64376879  4.5718074
#> 12 2024     GW    Manatee River  0.13199801 0.64376879  4.5718074
#> 13 2022     GW Middle Tampa Bay  0.25632137 1.45807586  8.9083788
#> 14 2023     GW Middle Tampa Bay  0.25632137 1.45807586  8.9083788
#> 15 2024     GW Middle Tampa Bay  0.25632137 1.45807586  8.9083788
#> 16 2022     GW    Old Tampa Bay  6.54776566 1.94595506 59.8399180
#> 17 2023     GW    Old Tampa Bay  6.54776566 1.94595506 59.8399180
#> 18 2024     GW    Old Tampa Bay  6.54776566 1.94595506 59.8399180
#> 19 2022     GW   Terra Ceia Bay  0.01797800 0.09544564  0.6201936
#> 20 2023     GW   Terra Ceia Bay  0.01797800 0.09544564  0.6201936
#> 21 2024     GW   Terra Ceia Bay  0.01797800 0.09544564  0.6201936

if (FALSE) { # \dontrun{
# update rasters from FDEP for a new year, then compute loads
pot_dry <- util_gw_getcontour("dry", 2025)
pot_wet <- util_gw_getcontour("wet", 2025)
gw <- anlz_gw(pot_dry, pot_wet, yrrng = c(2025, 2025))

# pass concentrations from the Water Atlas API
gw <- anlz_gw(pot_dry, pot_wet, yrrng = c(2025, 2025),
              wqdat = util_gw_getwq())
} # }