Transform PSCIS Assessment Worksheet Data by Calculating Culvert Slope Score

This function calculates the culvert slope score for BC Provincial Stream Crossing Inventory System (PSCIS) data based on conditions involving culvert slope percent.

Usage

fpr_xfm_paw_score_cv_slope(
  dat,
  col_culvert_slope_percent = culvert_slope_percent,
  col_culvert_slope_score = culvert_slope_score,
  slope_risk_low = 1,
  slope_risk_high = 3,
  risk_mod = 5,
  risk_high = 10,
  risk_low = 0
)

Arguments

dat

[dataframe] A dataframe containing the PSCIS data.

col_culvert_slope_percent

[character] A column name specifying the culvert slope percent, as a string or tidy-select syntax. Default is `culvert_slope_percent`.

col_culvert_slope_score

[character] A column name for the output culvert slope score, as a string or tidy-select syntax. Default is `culvert_slope_score`.

slope_risk_low

[numeric] A numeric value representing the lower threshold for low culvert slope risk (in percent). Default is `1`.

slope_risk_high

[numeric] A numeric value representing the threshold for high culvert slope risk (in percent). Default is `3`.

risk_mod

[numeric] A numeric value representing the risk score for moderate culvert slope conditions. Default is `5`.

risk_high

[numeric] A numeric value representing the risk score for high culvert slope conditions. Default is `10`.

risk_low

[numeric] A numeric value representing the risk score for low culvert slope conditions. Default is `0`.

Value

[dataframe] A dataframe with the specified column for culvert slope score added or updated.

See also

Other xfm paw: fpr_xfm_paw_all_scores_result(), fpr_xfm_paw_barrier_result(), fpr_xfm_paw_score_cv_len(), fpr_xfm_paw_score_embed(), fpr_xfm_paw_score_final(), fpr_xfm_paw_score_outlet_drop(), fpr_xfm_paw_score_swr(), fpr_xfm_paw_swr()

Examples

dat <- data.frame(
  culvert_slope_percent = c(0.5, 1.5, 3.5, NA)
)
fpr_xfm_paw_score_cv_slope(
  dat
)
#>   culvert_slope_percent culvert_slope_score
#> 1                   0.5                   0
#> 2                   1.5                   5
#> 3                   3.5                  10
#> 4                    NA                   0