Bay segment table of TN loads by year

Usage

show_aaloads(
  aa_data,
  bay_seg,
  gw_data,
  spr_data,
  ad_data,
  yrrng = NULL,
  digits = 1,
  family = "Arial",
  txtsz = 11
)

Arguments

aa_data: data frame returned by anlz_aa called with annavg = FALSE
bay_seg: integer bay segment identifier, one of 1L (Old Tampa Bay), 2L (Hillsborough Bay), 3L (Middle Tampa Bay), 4L (Lower Tampa Bay), or 55L (Remaining Lower Tampa Bay).
gw_data: data frame returned by anlz_gw called with summtime = 'year'.
spr_data: data frame returned by anlz_spr called with summ = 'segment' and summtime = 'year'.
ad_data: data frame returned by anlz_ad called with summ = 'segment' and summtime = 'year'.
yrrng: optional integer vector of length 2 restricting the displayed years to a subset of those already present in aa_data. Default NULL shows all years present.
digits: numeric indicating decimal precision for the year columns. Default 1.
family: chr string indicating font family for text labels
txtsz: numeric indicating font size

Value

A flextable object with one row per entity/facility in bay_seg, grouped into sections by source, and one column per year.

Details

Rows are grouped into sections using aa_data's source column: "MS4" (source of "MS4" or "Nonpoint Source/MS4"), "Industrial Point Source" (source == "IPS"), "Domestic Point Source - end of pipe" and "Domestic Point Source - reuse" (source == "DPS - end of pipe"/"DPS - reuse"), "Material Losses" (source == "ML"), and "Nonpoint Source" (the "All" (FDACS) and "Non-MS4/Ag NPS" aggregate rows from aa_data, plus two rows built from gw_data/spr_data/ ad_data - see below; other unmatched source = NA rows in aa_data are negligible land-use slivers dropped by anlz_aa at its 0.01 tons/yr threshold in most years but not all, and are excluded here rather than shown as a spurious partial row). Each facility/entity keeps its own row, even for ishared shared-allocation groups (see anlz_aa). Row labels combine the owning entity with the facility name (e.g., "Mosaic - Riverview").

Atmospheric Deposition and Other (Groundwater, Springs, Conservation): gw_data, spr_data, and ad_data are mapped to bay_seg the same way anlz_aa does internally (Terra Ceia Bay and Manatee River summed into segment 55; Boca Ciega Bay variants dropped, consistent with the allocation framework's existing exclusion) and filtered to the requested bay_seg. ad_data's tn_load becomes the "Atmospheric Deposition" row. gw_data's and spr_data's tn_load (spr_data only has rows for Hillsborough Bay - other segments that have no contribution receive 0) plus aa_data's seg_conserv_tn (TN removed by the conservation-land correction already computed inside anlz_aa(), exposed as a segment total rather than sourced separately) become the "Other (Groundwater, Springs, Conservation)" row. Both are zero-filled for years with no matching input, same as facility/entity rows.

A facility/entity with a real allocation but no load data for a given year (or any year at all) is NA in aa_data by design (see anlz_aa); here it displays as 0 rather than blank.

Values shown are always load_tons (raw, unnormalized loads), never eff_load_tons.

A bolded "Total Load" row sums every displayed row for each year (including the AD and Other rows). A bolded "Normalized Load" row below it applies one hydrologic-normalization ratio to the whole segment's Total Load:

$$ \text{Normalized Load} = \text{Total Load} \times \frac{\text{baseline\_h2o}}{\text{seg\_h2o\_total} + \text{gw\_hy\_load} + \text{spr\_hy\_load} + \text{ad\_hy\_load}} $$

where the denominator is aa_data's seg_h2o_total (NPS+IPS+DPS combined) plus gw_data/spr_data/ad_data's own hy_load, and baseline_h2o is a hardcoded 1992-1994 baseline hydrologic load (million m3/yr) per bay segment:

bay\_seg	baseline\_h2o
1 Old Tampa Bay	449.44
2 Hillsborough Bay	895.62
3 Middle Tampa Bay	645.25
4 Lower Tampa Bay	361.19
55 Remaining Lower Tampa Bay	422.709

An additional "Average" column, appended after the year columns, gives each row's own mean across the displayed years.

Examples

if (FALSE) { # \dontrun{
aa_data <- anlz_aa(c(2022, 2024), dps, ips, ml, nps, tbbase, annavg = FALSE)
gw_data <- anlz_gw(contdry, contwet, yrrng = c(2022, 2024), summtime = 'year')
spr_data <- anlz_spr(tbwxlpth, wqpth, yrrng = c(2022, 2024),
  summ = 'segment', summtime = 'year')
ad_data <- anlz_ad(rain, vernafl, summ = 'segment', summtime = 'year')
show_aaloads(aa_data, bay_seg = 2L, gw_data, spr_data, ad_data)
} # }