MC_logit: Overflow counting for simulated data

In dax44/OvfSim: Simulate number of catchment overflow

Overflow counting for simulated data

Description

Function simulate given number of rainfall event by Monte-Carlo method and calculate number of overflows in them based on logistic regression model. Rainfall distributions are estimated based on sample data.

Usage

MC_logit(
  dt,
  logit.model = mod,
  rt,
  n = 1000,
  Imp = NULL,
  Impu = NULL,
  Gk = NULL,
  plot = TRUE
)

Arguments

dt	data frame, sample of rainfall events based on which rainfall parameters will be estimated
logit.model	name of logistic regression for Overflow already fitted
rt	numeric vector of length 2, lower and upper bound of rainfall event duration. See details
n	number of simulations
Imp	level of imperviousness of the catchment, in %. Default value NULL - no control for Imp
Impu	the level of imperviousness of the area lying below the analysed catchment, in %. Default value NULL - no control for Impu
Gk	unitary length of the main collector in the catchment per impervious area, in m/ha. Default value NULL - no controln for Gk
plot	logical, choose is you want to plot CDFs

Details

You can choose bounds of rainfall event duration, which filter all events to particular type of rainfall (convectional, frontal or convergence zones)

Value

MC_logit returns number of overflows, CDFs of overflow probability and rainfall intensity for different sets of catchment area parameters

Warning

before you use this function you should fit logistic regression for Overflow

Examples

dt <- data.frame(P = rgamma(100, shape = 12, rate = 0.2),
                 t = rlnorm(100, meanlog = 5, sdlog = 1.5))
mod <- logit(dt.logit)
MC_logit(dt, mod, rt = c(0,150), n = 1000, Imp = 0.2, Impu = 0.1, Gk = 0.05)
mod2 <- logit(dt.logit[, c(1:2,6)]) # no Imp, Impu, Gk
MC_logit(dt, mod2, rt = c(150,630), n = 1000)

dax44/OvfSim documentation built on April 29, 2022, 6:53 a.m.