weighted_C: Calculate the Weighted C factor

In iemisc: Irucka Embry's Miscellaneous Functions

Calculate the Weighted C factor

Description

This function computes the weighted C factor using the user-supplied unit or the default unit of an acre for use in the Rational Formula.

Usage

weighted_C(
  C = NULL,
  area = NULL,
  area_pct = NULL,
  area_units = c("acre", "square feet", "square mile", "hectare", "square kilometer"),
  C_area_table = NULL,
  C_area_pct_table = NULL
)

Arguments

C	numeric vector containing dimensionless C factor(s)
area	numeric vector containing the surface land area
area_pct	numeric vector containing the surface land area, as a percent (decimal or whole number)
area_units	character vector containing the units for area (default = "acre"). The other possible units are "square feet", "square mile", "hectare", or "square kilometer". The units should be consistent and not mixed.
C_area_table	data.frame/data.table/tibble, list, or matrix containing the C in column 1 and the area in column 2
C_area_pct_table	data.frame/data.table/tibble, list, or matrix containing the C in column 1 and the area_pct in column 2

Value

Weighted C factor as a single numeric vector, in the range [0, 1]

Author(s)

Irucka Embry

References

Engineering Hydrology Training Series Module 104 - Runoff Curve Number Computations Study Guide, United States Department of Agriculture Soil Conservation Service National Employee Development Staff, September 1989, page 21 https://web.archive.org/web/20210414043852/https://www.wcc.nrcs.usda.gov/ftpref/wntsc/H&H/training/runoff-curve-numbers1.pdf. Retrieved thanks to the Internet Archive: Wayback Machine

Examples

# Note: the default area unit is acre

# Example 1

library(iemisc)

area1 <- c(220, 150, 30)
C1 <- c(75, 89, 80)
weighted_C(C = C1, area = area1)


# Example 2

library(iemisc)

area2 <- c(220, 150, 30)
area_pct2 <- area2 / sum(area2)
C2 <- c(80, 95, 80)
C_area_pct_table2 <- data.frame(C2, area_pct2)
weighted_C(C_area_pct_table = C_area_pct_table2)


# Example 3

install.load::load_package("iemisc", "data.table")

C_area_table3 <- data.table(C = c(98, 100, 45), area = c(2.53, 453.00, 0.21))
weighted_C(C_area_table = C_area_table3)


# Example 4

library(iemisc)

C4 <- c(98, 100, 45)
area_pct4 <- c(0.15, 0.23, 0.62)
weighted_C(C = C4, area_pct = area_pct4)


# Example 5

library(iemisc)

data_matrix5a <- matrix(c(98, 30, 40, 43, 57, 3.24, 1, 30, 50, 123), nrow = 5,
ncol = 2, dimnames = list(rep("", 5), c("C", "Area")))
weighted_C(C_area_table = data_matrix5a)


# using ramify to create the matrix

import::from(ramify, mat)

data_matrix5b <- mat("98 30 40 43 57;3.24 1 30 50 123", rows = FALSE, sep = " ",
dimnames = list(rep("", 5), c("C", "Area")))
weighted_C(C_area_table = data_matrix5b)


# Example 6 - using area in square feet

library(iemisc)

data_list6 <- list(C = c(77, 29, 68), Area = c(43560, 56893, 345329.32))
weighted_C(C_area_table = data_list6, area_units = "square feet")


# Example 7

install.load::load_package("iemisc", "data.table")

# Impervious area - 3.04 acre
# 45% of total area
# 0.80 C Factor

# Pervious area - 4.67 acre
# 55% of total area
# 0.20 C factor

C_area_table7 <- data.table(C = c(0.80, 0.20), area = c(3.04, 4.67))
weighted_C(C_area_table = C_area_table7)


# Example 8

# Impervious area - 2.44 acre
# 32% of total area
# 0.80 C Factor

# Pervious area - 5.03 acre
# 68% of total area
# 0.20 C factor

C8 <- c(0.80, 0.20)
area_pct8 <- c(0.32, 0.68)
weighted_C(C = C8, area_pct = area_pct8)


# Example 9

library(iemisc)

# Medium density residential area - 30 hectares (75.0% of total area),
# 0.31 - 0.40 C factor
# High density residential area - 3 hectares (7.50% of total area),
# 0.49 - 0.60 C factor
# Agricultural area - 7 hectares (17.5% of total area), 0.15 - 0.21 C factor

C3 <- c(mean(seq(0.31, 0.40, by = 0.01)), mean(seq(0.49, 0.60, by = 0.01)),
mean(seq(0.15, 0.21, by = 0.01)))
area3 <- c(30, 3, 7)
weighted_C(C = C3, area = area3, area_units = "hectare")

iemisc documentation built on Sept. 25, 2023, 5:09 p.m.