pnpi: Calculate Percent of Normal Index (PNPI)

In flogrc/piflow: Precipitation and discharge analysis tools with zoo vector

Description

Calculate PNPI and the drought specifications with the length, the drought type and the intensity

Usage

pnpi(monthly_data, time_step = 12)

Arguments

monthly_data	[zoo] rainfall monthly data in zoo class with date in %Y-%m-%d
time_step	[numeric] default = 12, time step (1, 3, 6, 9, 12, 24 and 48)

Value

list that contains

• pnpi [zoo] zoo with the pnpi values with date in

• length_zoo [zoo] zoo with the length of drought with date in %Y-%m-%d [day]

• drought_type [zoo] zoo with the type of the period for each month

• drought_number [data.frame] dataframe with the number of different period by type:

  • Extwet (pnpi >= 160)
    

  • Verywet (160 > pnpi >= 145)
    

  • Wet (145 > pnpi >= 120)
    

  • Normal (120 > pnpi >= 80)
    

  • Dry (80 > pnpi >= 55)
    

  • VeryDry (50 > pnpi >= 40)
    

  • ExtDry (40 > pnpi)

Author(s)

Florine Garcia ([e-mail])

Pierre L'Hermite ([e-mail])

References

Willeke G, Hosking JRM, Wallis JR, Guttman NB (1994) The national drought atlas,Institute for water resources report 94-NDs-4. Army Corps of Engineers, Washington, D.C.
Amirataee, B. and Montaseri, M. (2017) The performance of SPI and PNPI in analyzing the spatial and temporal trend of dry and wet periods over Iran, Natural Hazards, 1, 89-106. https://doi.org/10.1007/s11069-016-2675-4

See Also

plot_trend plot the index

Examples

## Loading data
data("dailyPrec_bv1")

## Index
result <- pnpi(dailyPrec, time_step = 3)

## Plot index
plot_trend(result$pnpi, trend = TRUE, data_kind = "PNPI",
name = PluvioData$PluvioName, axis_name_x = "Date",
axis_name_y = Monthly precipitation [mm/month], midvalue = 100)

flogrc/piflow documentation built on May 24, 2019, 7:34 a.m.