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Size a parameter to reach a target guarantee level

Source: R/iso-curves.R
rh_size_for.Rd

Generalises the zero-deficit sizing functions (rh_guaranteed_capacity() etc.) to any guarantee level: it finds the value of one design parameter ("capacity", "area" or "demand") at which a chosen guarantee metric reaches target_value. Because the metric is monotone in each parameter the search is a bisection: for capacity/area it returns the smallest value that reaches the target; for demand the largest value that still does.

Usage

rh_size_for(
  precip,
  base = list(),
  vary,
  target_value,
  metric = "attendance_pct",
  tol = 0.01,
  max = NULL,
  dates = NULL,
  climatology = FALSE
)

Arguments

precip

Numeric vector of daily precipitation (mm). If climatology = TRUE, it is first collapsed to its day-of-year mean (see dates).

base

Named list of the fixed rh_simulate() arguments (everything except vary).

vary

Parameter to solve for: "capacity", "area" or "demand".

target_value

Target guarantee value (e.g. 95 for 95 percent).

metric

Guarantee metric: "attendance_pct" (default, volumetric) or "reliability_pct" (time-based).

tol

Search tolerance (in units of vary).

max

Optional upper bound for the search; grown automatically if needed.

dates

Optional date vector aligned with precip, required only when climatology = TRUE.

climatology

If TRUE, simulate on the day-of-year climatology (much faster) instead of the full series. Default FALSE.

Value

A single numeric value of vary.

See also

rh_iso_curve(), rh_resource_curve().

Examples

# capacity needed for 90% volumetric attendance
rh_size_for(precip_pi$value,
            base = list(demand = 6.6, area = 4170, runoff = 0.85, efficiency = 1),
            vary = "capacity", target_value = 90,
            dates = precip_pi$date, climatology = TRUE)
#> [1] 569.9067