hydroTSM (version 0.7-0)

si: Seasonality Index

Description

Function to compute the seasonality index defined by Walsh and Lawler (1981) to classify the precipitation regime.

Usage

si(x, na.rm=TRUE, from=start(x), to=end(x), date.fmt="%Y-%m-%d", start.month=1)

Value

numeric with the seasonality index

Arguments

x

zoo object with daily or subdaily precipitation data.

na.rm

Logical. Should missing values be removed?
-) TRUE : the monthly values are computed considering only those values different from NA
-) FALSE: if there is AT LEAST one NA within a month, the resulting average monthly value is NA .

from

OPTIONAL, used for extracting a subset of values.
Character indicating the starting date for the values to be extracted. It must be provided in the format specified by date.fmt.

to

OPTIONAL, used for extracting a subset of values.
Character indicating the ending date for the values to be extracted. It must be provided in the format specified by date.fmt.

date.fmt

Character indicating the format in which the dates are stored in dates, from and to. See format in as.Date.
ONLY required when class(dates)=="factor" or class(dates)=="numeric".

start.month

[OPTIONAL]. Only used when the (hydrological) year of interest is different from the calendar year.

numeric in [1:12] indicating the starting month of the (hydrological) year. Numeric values in [1, 12] represents months in [January, December]. By default start.month=1.

Author

Mauricio Zambrano-Bigiarini,

Details

The seasonality index is computed as following:

si = (1/R) *sum(i=1, i=12, abs(xi - R/12) )
where:
-) xi: mean monthly precipitation for month i
-) R: mean annual precipitation

This index can theoretically vary from 0 (when all months have the same rainfall) to 1.83 (when all the rainfall ocurrs in a single month). A qualitative classification of degrees of seasonality is the following:
--------------------------------------------------------
si values | Rainfall regime
--------------------------------------------------------
<= 0.19 | Very equable
0.20 - 0.39 | Equable but with a definite wetter season
0.40 - 0.59 | Rather seasonal with a short drier season
0.60 - 0.79 | Seasonal
0.80 - 0.99 | Markedly seasonal with a long drier season
1.00 - 1.19 | Most rain in 3 months or less
>= 1.20 | Extreme, almost all rain in 1-2 months

References

Walsh, R. and Lawler, D. (1981). Rainfall seasonality: Description, spatial patterns and change through time (British Isles, Africa). Weather, 36(7), 201-208. doi:10.1002/j.1477-8696.1981.tb05400.x.

See Also

subdaily2daily

Examples

############################
## Ex 1: Seasonality index for a rain gauge with equable precipitation , 
##       but with a definite wetter season 

## Loading daily precipitation data at the station San Martino di Castrozza, 
## Trento Province, Italy, from 01/Jan/1921 to 31/Dec/1990.
data(SanMartinoPPts)
x <- SanMartinoPPts

## Amount of years in 'x' (needed for computations)
( nyears <- yip(from=start(x), to=end(x), out.type="nmbr" ) )


## Boxplot of monthly values, to look at the seasonal cycle

## Daily to Monthly
m <- daily2monthly(x, FUN=sum, na.rm=TRUE)

## Mean monthly values at the station
monthlyfunction(m, FUN=sum, na.rm=TRUE) / nyears

## Vector with the three-letter abbreviations of the month names
cmonth <- format(time(m), "%b")

## Creating ordered monthly factors
months <- factor(cmonth, levels=unique(cmonth), ordered=TRUE)

## Boxplot of the monthly values of precipitation
boxplot( coredata(m) ~ months, col="lightblue", 
         main="Monthly precipitation, [mm]", ylab="P, [mm]")

# computing seasonality index
( si(x) )

############################
## Ex 2: Seasonality index for a rain gauge with markedly seasonal regime 
##       with a long dry season

## Loading daily precipitation data at the station Cauquenes en El Arrayan, 
## Maule Region, Chile, from 01/Jan/1979 to 31/Dec/2020.
data(Cauquenes7336001)
x <- Cauquenes7336001[, 1] # P is the first column

## Boxplot of monthly values, to look at the seasonal cycle

## Daily to Monthly
m <- daily2monthly(x, FUN=sum, na.rm=TRUE)

## Mean monthly values at the station
monthlyfunction(m, FUN=sum, na.rm=TRUE) / nyears

## Vector with the three-letter abbreviations of the month names
cmonth <- format(time(m), "%b")

## Creating ordered monthly factors
months <- factor(cmonth, levels=unique(cmonth), ordered=TRUE)

## Boxplot of the monthly values of precipitation
boxplot( coredata(m) ~ months, col="lightblue", 
         main="Monthly precipitation, [mm]", ylab="P, [mm]")

# computing seasonality index
( si(x) )