IDFCurve: Compute Intensity-Duration-Frequency curve

Description Usage Arguments Value Author(s) Examples

View source: R/IDFCurve.R

Description

An Intensity-Duration-Frequency curve (IDF Curve) is a graphical representation of the probability that a given average rainfall intensity will occur. This function allows to fit different probability distribution functions (see selecDIST) by means of four fit methods (see fitDISTRI) to determine intensity [mm/h] for different return periods and per specific time durations. Finally, it computes equations parameters of the IDF curves (see regIDF)

Usage

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IDFCurve(Data = ..., Station = "2610516", Duration = FALSE,
  Periods = FALSE, Type = "gumbel", M.fit = "lmoments", Plot = 1234,
  Strategy = 1:3, logaxe = "", CI = FALSE, CIpdf = TRUE, iter = 500,
  goodtest = FALSE, Resolution = 300, SAVE = FALSE, name = TRUE)

Arguments

Data:

a numeric matrix with years in the first column and intensity values for each Duration time in the other columns.

Station:

a string with a name to identify source of Data.

Duration:

a logical value or numeric vector. If it is TRUE the durations (in minutes) by default will be used: 5, 10 ,15, 20, 30, 60, 120 y 360. In case of a numeric vector the durations must be in minutes.

Periods:

a logical value or numeric vector.

Type:

a character specifying the name of the distribution function that will be employed: exponencial, gamma, gev, gumbel, log.normal3, normal, pearson, log.pearson3 and wakeby (see selecDIST).

M.fit:

a character specifying a name of fit method employed on pdf, just three options are available: L-moments (Lmoments), Probability-Weighted Moments (PWD), Maximum Likelihood (MLEZ) and Moments (MME) (see MME_DIST).

Plot:

it is a number of one to four digits. a number (1) to plot density curves both empirical as modeled (pdf).(2) to plot if it will be plotted curves between return Periods and intensity computed by pdf fitted. Or use (12) to get both graphs. (3) to plot IDF curves for all return periods: (Durations versus Intensity) for all return Periods. (4) to plot IDF curve each for return Periods with its confidence and prediction intervals. Or use (34) to get both graphs. If other is used the graphs will not appear.

Strategy:

a numeric vector used to identify Strategies to compute IDF curves with different data sets: 1 just data from Ideam, 2 just data from HIDFUN tool and 3 used this data sets.

logaxe:

a character to plot axis in log scale: x, y or both (xy). In other case use "".

CI:

a logical value specifying whether confidence and prediction intervals will be computed.

CIpdf:

a logical value specifying whether confidence of pdf will be computed.

iter:

an integer representing number of resamples to conduct when confidence interval is computed (see bootstrapCI). Use it only if CI is equal to TRUE.

goodtest:

a logical value specifying whether goodness-fit tests should be cumputed to pdf fitted by means of goodfit function.

Resolution:

a number to determine the resolution that the plot function will used to save graphs. It has two options: 300 and 600 ppi. See resoPLOT.

SAVE:

a logical value. TRUE will save Plot, FALSE will just show Plot.

name:

a logical value. TRUE will use a default names to identify strategies: (1) "HIDFUN", (2) "IDEAM", (3) "AMBOS". In other case FALSE allows: i) selected years of data sets, and ii) to insert durations to do IDF curves (in minutes)

Value

A list of:

Author(s)

David Zamora <[email protected]> Albeiro Figueroa <[email protected]> Water Resources Engineering Research Group - GIREH

Examples

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# Meteorology station in the Farfan Airport in Tulua, Colombia.
data(inten)
Test.idftool <- IDFCurve(Data = inten, Station='2610516', Duration = FALSE,
Periods = FALSE, Type = "gumbel", M.fit = "lmoments",
Plot = 1234, Strategy = 1, logaxe = "", CI = FALSE, iter = 100,
goodtest = FALSE, Resolution = 300, SAVE = FALSE, name = TRUE)

dazamora/IDFtool documentation built on March 20, 2018, 8:56 p.m.