CODEWITHSUNDEEP
rtime
uared1776
uared1776

Reputation: 87

hydrological year time series

Currently I am working on a river discharge data analysis. I have the daily discharge record from 1935 to now. I want to extract the annual maximum discharge for each hydrolocial year (start from 01/11 to next year 31/10). However, I found that the hydroTSM package can only deal with the natural year. I tried to use the "zoo" package, but I found it's difficult to compute, as each year have different days. Does anyone have some idea? Thanks.

the data looks like:

01-11-1935 663
02-11-1935 596
03-11-1935 450
04-11-1935 381
05-11-1935 354
06-11-1935 312

my code:

mydata<-read.table("discharge")
colnames(mydata) <- c("date","discharge")

library(zoo)
z<-zooreg(mydata[,2],start=as.Date("1935-11-1"))

mydta$date <- as.POSIXct(dat$date)

q.month<-daily2monthly(z,FUN=max,na.rm = TRUE,date.fmt = "%Y-%m-%d",out.fmt="numeric")
q.month.plain=coredata(q.month)

z.month<-zooreg(q.month.plain,start=1,frequency=12)

Upvotes: 6

Views: 2220

Answers (4)

Forever
Forever

Reputation: 545

You can use the apply.seasonal function from lfstat package which operates over xts objects.

To solve your case in one line:

apply.seasonal(mydata, varying = "yearly", fun = max, origin = 11)

origin = 11 means that the hydrological year will start in november.

Upvotes: 0

G. Grothendieck
G. Grothendieck

Reputation: 269704

Here is a one-liner to do that.

First convert the dates to "yearmon" class. This class represents a year month as the sum of a year as the integer part and a month as the fractional part (Jan = 0, Feb = 1/12, etc.). Add 2/12 to shift November to January and then truncate to give just the years. Aggregate over those. Although the test data we used starts at the beginning of the hydro year this solution works even if the data does not start on the beginning of the hydro year. 

# test data
library(zoo)
z <- zooreg(1:1000, as.Date("2000-11-01")) # test input

aggregate(z, as.integer(as.yearmon(time(z)) + 2/12), max)

This gives:

2001 2002 2003 
 365  730 1000

Upvotes: 3

Josh O&#39;Brien
Josh O&#39;Brien

Reputation: 162351

With dates stored in a vector of class Date, you can just use cut() and tapply(), like this:

## Example data
df <- data.frame(date = seq(as.Date("1935-01-01"), length = 100, by = "week"),
                 flow = (runif(n = 100, min = 0, max = 1000)))

## Use vector of November 1st dates to cut data into hydro-years
breaks <- seq(as.Date("1934-11-01"), length=4, by="year")
df$hydroYear <- cut(df$date, breaks, labels=1935:1937)

## Find the maximum flow in each hydro-year
with(df, tapply(flow, hydroYear, max))
#     1935     1936     1937 
# 984.7327 951.0440 727.4210 


## Note: whenever using `cut()`, I take care to double-check that 
## I've got the cuts exactly right
cut(as.Date(c("1935-10-31", "1935-11-01")), breaks, labels=1935:1937)
# [1] 1935 1936
# Levels: 1935 1936 1937

Upvotes: 8

Fernando
Fernando

Reputation: 7895

Try the xts package, which works together with zoo:

require(zoo)    
require(xts)

dates = seq(Sys.Date(), by = 'day', length = 365 * 3)
y = cumsum(rnorm(365 * 3))    
serie = zoo(y, dates)

# if you need to specify `start` and `end`
# serie = window(serie, start = "2015-06-01")

# xts function
apply.yearly(serie, FUN = max)

Upvotes: 2

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