Package 'nwmTools'

Title: nwmTools
Description: Tools for working with operational and historic National Water Model Output.
Authors: Mike Johnson [aut, cre] , Lauren Bolotin [ctb], CUAHSI [fnd], NSF [fnd], Lynker [fnd]
Maintainer: Mike Johnson <[email protected]>
License: CC0
Version: 0.0.4
Built: 2025-03-04 06:35:40 UTC
Source: https://github.com/mikejohnson51/nwmTools

Help Index

Add Water Year Column

Description

Add Water Year Column

Usage

add_waterYear(dateVec)

Arguments

dateVec

raw data returned from readNWMdata

Value

vector of water years

Aggregate by DOWY

Description

Aggregate by DOWY

Usage

aggregate_dowy(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Julien Day

Description

Aggregate by Julien Day

Usage

aggregate_j(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Month

Description

Aggregate by Month

Usage

aggregate_m(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Record

Description

Aggregate by Record

Usage

aggregate_record(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Season

Description

Aggregate by Season

Usage

aggregate_s(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Water Year

Description

Aggregate by Water Year

Usage

aggregate_wy(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Water Year - Month

Description

Aggregate by Water Year - Month

Usage

aggregate_wym(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Water Year - Month - Day

Description

Aggregate by Water Year - Month - Day

Usage

aggregate_wymd(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Water Year - Season

Description

Aggregate by Water Year - Season

Usage

aggregate_wys(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Year

Description

Aggregate by Year

Usage

aggregate_y(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_ys()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Year-Julien Day

Description

Aggregate by Year-Julien Day

Usage

aggregate_yj(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_ymd(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Year-Month

Description

Aggregate by Year-Month

Usage

aggregate_ym(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Year-Month-Day

Description

Aggregate by Year-Month-Day

Usage

aggregate_ymd(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ym(), aggregate_ys(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Aggregate by Year-Season

Description

Aggregate by Year-Season

Usage

aggregate_ys(rawData, fun = "mean", na.rm = TRUE)

Arguments

rawData

data extracted with readNWMdata
fun

function to be applied to the flows column default = 'mean'
na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

NWM data is extracted as hourly values.

To aggregate hourly data to different time chunks the nwmHistoric package offers a family of aggregate functions.

Each of these begins with the prefix 'aggregate_' and is followed by the date symbol to aggregate to.

Symbol Aggregate
y year
m month
d day
j julien day
s season
wy water year

See Also

Other aggregate functions: aggregate_dowy(), aggregate_j(), aggregate_m(), aggregate_record(), aggregate_s(), aggregate_wymd(), aggregate_wym(), aggregate_wys(), aggregate_wy(), aggregate_yj(), aggregate_ymd(), aggregate_ym(), aggregate_y()

Examples

## Not run: 
# Get flow record for COMID 101
flows = readNWMdata(comid = 101)

# Aggregate to yearly average (y)
yearly = aggregate_y(flows, fun = 'mean')

# Aggregate to monthly
# minimum and maximum per year (ym)
ym = aggregate_ym(flows, fun = list(min, max))

# Aggregate to seasonal 95th percetile 
# with using custom function
s95 = aggregate_s(flows, fun = function(x){quantile(x,.95)})

## End(Not run)

Crop Flipped Raster

Description

Crop Flipped Raster

Usage

crop_flipped_nwm(x, AOI)

Arguments

x

SpatRast object
AOI

a sf polygon

Value

SpatRast object (x cropped to AOI)

Download Remote Files

Description

Download Remote Files

Usage

download_files(fileList, outdir = ".")

Arguments

fileList

fileList object
outdir

directory to write files

Value

data.frame

Get GCP file list

Description

Get GCP file list

Usage

get_aws_urls(
  version = 2.1,
  output = "CHRTOUT",
  config = NULL,
  ensemble = NULL,
  date = "2010-10-29",
  hour = "00",
  minute = "00",
  num = 3,
  outdir = NULL
)

Arguments

version

NWM model version
output

the NWM model output type
config

the NWM model configurarion
ensemble

the NWM ensemble number
date

date of interest
hour

hour of interest
minute

minute of interest
num

number of files to get (forward from provides data-hour-minute)

Value

data.frame

Get GCP file list

Description

Get GCP file list

Usage

get_gcp_urls(
  config = "short_range",
  domain = "conus",
  date,
  hour = "00",
  minute = "00",
  num,
  ensemble = NULL,
  output = "channel_rt"
)

Arguments

config

the NWM model configurarion
domain

the NWM model domain
date

date of interest
hour

hour of interest
minute

minute of interest
num

number of files to get (forward from provides data-hour-minute)
ensemble

the NWM ensemble number
output

the NWM model output type

Value

data.frame

Extract Gridded Data from fileList

Description

Extract Gridded Data from fileList

Usage

get_gridded_data(fileList, AOI, varname, outfile = NULL)

Arguments

fileList

a list of gridded NWM outputs
AOI

area of interest (sf POLYGON) to subset
varname

the name of the variable to extract
outfile

filepath to save data (with .nc extension)

Value

data.frame

Get NOMADs File List

Description

Get NOMADs File List

Usage

get_nomads_urls(
  config = "short_range",
  domain = "conus",
  date = NULL,
  hour = NULL,
  minute = "00",
  num,
  ensemble = NULL,
  output = "channel_rt",
  version = "prod",
  outdir = NULL
)

Arguments

config

the NWM model configurarion
domain

the NWM model domain
date

date of interest
hour

hour of interest
minute

minute of interest
num

number of files to get (forward from provides data-hour-minute)
ensemble

the NWM ensemble number
output

the NWM model output type
version

server version (prod or para)

Value

data.frame

NWM metadata

Description

NWM metadata

Usage

get_nwm_meta(version = NULL)

Arguments

version

Which version of NWM should be returned? (1.2, 2.0, 2.1)

Value

data.frame

Extract Timeseries from file list

Description

Extract Timeseries from file list

Usage

get_timeseries(
  fileList,
  ids = NULL,
  index_id = "feature_id",
  varname = "streamflow",
  outfile = NULL
)

Arguments

fileList

a list of non-gridded NWM outputs
ids

a set of ids to limit the returned data to
index_id

the name of the id attributes
varname

the name of the variable
outfile

file path to save data to (.nc extension)

Value

data.frame

NWM Data Types

Description

NWM Data Types

Usage

nwm_data

Format

An object of class tbl_df (inherits from tbl, data.frame) with 603 rows and 13 columns.

NWM Reanalysis Extraction

Description

Download hourly flow values for an NHD COMID from the National Water Model version 1.2 or 2.0. Returned data is available between "1993-01-01 00" and "2017-12-31 23" but can be subset using a startDate and endDate.

Usage

readNWMdata(
  AOI = NULL,
  comid = NULL,
  siteID = NULL,
  startDate = NULL,
  endDate = NULL,
  tz = "UTC",
  version = 2.1,
  addObs = FALSE,
  add_nhd = FALSE
)

Arguments

AOI

spatial polygon or point to extract data for
comid

a NHD common identifier
siteID

a USGS NWIS site identifier (eight digits)
startDate

a start date (YYYY-MM-DD) or (YYYY-MM-DD HH)
endDate

an end date (YYYY-MM-DD) or (YYYY-MM-DD HH)
tz

the desired timezone of the data. Can be found with OlsonNames
version

the NWM version to extract (current = 1.2 or 2 (default))
addObs

should observation data be added? Only available when !is.null(siteID)
add_nhd

should the NHD spatial features be added to the output

Value

data.frame or sf object

Examples

## Not run: 
readNWMdata(comid = 101)
readNWMdata(comid = 101, version = 1.2)
readNWMdata(comid = 101, tz = "US/Pacific")

## End(Not run)

Split Y-M-D-H into time components

Description

Split Y-M-D-H into time components

Usage

split_time(rawData, time_col)

Arguments

rawData

rawData with time column
time_col

the column name holding dateTime

Value

data.frame with added time components

NWM THREDDS Servers

Description

NWM THREDDS Servers

Usage

tds_meta

Format

An object of class data.frame with 3 rows and 7 columns.