| Title: | Helper Tools for Australian Hydrologists |
|---|---|
| Description: | Functions to speed up work flow for hydrological analysis. Focused on Australian climate data (SILO climate data), hydrological models (eWater Source) and in particular South Australia (<https://water.data.sa.gov.au> hydrological data). |
| Authors: | Matt Gibbs [aut, cre] |
| Maintainer: | Matt Gibbs <[email protected]> |
| License: | GPL-3 |
| Version: | 1.1.0 |
| Built: | 2024-11-13 06:01:10 UTC |
| Source: | https://github.com/matt-s-gibbs/swtools |
Functions to speed up workflow for hydrological analysis. Focused on Australian climate data (SILO climate data), hydrological models (eWater Source) and South Australian hydrological data (from Water Data SA).
SILO is a database of Australian climate data from 1889 to the present. It provides daily meteorological datasets for a range of climate variables in ready-to-use formats suitable for biophysical modelling, research and climate applications SILO Website.
These functions allow SILO data to be downloaded from the SILO Website, imported into R,
calculate some basic statistics and undertake some quality assurance tests to easily visualise how much data has been interpolated, and to compare nearby sites to identify potential data issues.
SILODownload,SILOLoad and SILOReport functions allow a vector of SILO sites to be downloaded and summarised in a Microsoft Word report.
eWater Source is the Australia's national hydrological modelling platform, and is increasing in use around the world.
Functions are included to write SILO climate data to the format expected for Source SILOWriteforSource,
and reading in model outputs, read_res.csv.
Veneer is a RESTful API for interacting with Source models. Functions are included that are wrappers for Veneer, to build URLs to get or set data in the Source model, and process the json object returned.
South Australia's hydrological data is hosted on Water Data SA.
The Export link creates URLs that enable multiple datasets to be downloaded.
AQWPDownload builds these URLs to download data in json format, and AQWPLoad loads this json file into the R interface.
New South Wales, Queensland and Victoria use a Hydstra database, with the site information available over a
Kisters API.
HydstraSiteDetails will use this API to download streamflow site information, such as
the cross section, rating curve, gaugings as well as the daily (9am-9am) time series of discharge data.
Maintainer: Matt Gibbs [email protected]
Useful links:
Report bugs at https://github.com/matt-s-gibbs/swtools/issues
For most inputs, valid options will be returned if an unexpected input is provided. The exception are Location and Dataset, if the location, or dataset for that location, don't exist no data will be returned. Browse the Export tab on https://water.data.sa.gov.au to find Location and Dataset that exists.
AQWPDownload( Location, Dataset, Unit, file = "AQWP.json", Interval = "Daily", Calculation = "Aggregate", Calendar = "CALENDARYEAR", Step = 1, DateRange = "EntirePeriodOfRecord", StartTime = NULL, EndTime = NULL )AQWPDownload( Location, Dataset, Unit, file = "AQWP.json", Interval = "Daily", Calculation = "Aggregate", Calendar = "CALENDARYEAR", Step = 1, DateRange = "EntirePeriodOfRecord", StartTime = NULL, EndTime = NULL )
Location |
A string or vector of strings, with site numbers, e.g. "A4261001" |
Dataset |
A string or vector of strings, with dataset names, as expected by AWQP, e.g. "Tide Height.Best Available–Continuous" |
Unit |
A string or vector of strings, with units, e.g. "Metres" or "mg/L". If only 1 is string is provided it will be used for each site in Location |
file |
Location and name of json file to download. Defaults to "AQWP.json". |
Interval |
Interval of output, e.g. "PointsAsRecorded", or "Daily" |
Calculation |
For larger intervals, what calculation to do, e.g. "Aggregate" (average) or "Maximum" |
Calendar |
When to start the periods, e.g. "WATERDAY9AM" |
Step |
How many intervals e.g. 15 with Interval="Minutely" returns 15 minute data. |
DateRange |
Period of data to return, e.g. "EntirePeriodOfRecord" or "Custom". "Years1" seems to not work on AWQP. |
StartTime |
Start Date and Time if DateRange="Custom", in a format that as.POSIXct will convert, e.g 2000-01-01 00:00 |
EndTime |
End Date and Time if DateRange="Custom", in a format that as.POSIXct will convert, e.g 2001-01-02 00:00 |
The lnk created to download the data, which is useful for debugging. The data is saved to "file", that can then be read in with AQWPLoad()
## Not run: Location=c("A4260633","A4261209","A4260572") Dataset=rep("Tide Height.Best Available--Continuous",3) Unit=rep("Metres",3) S="2020-01-01 00:00" E="2020-01-02 00:00" AQWPDownload(Location,Dataset,Unit,DateRange="Custom", StartTime=S,EndTime=E,file=tempfile("AQWP",fileext=".json")) ## End(Not run)## Not run: Location=c("A4260633","A4261209","A4260572") Dataset=rep("Tide Height.Best Available--Continuous",3) Unit=rep("Metres",3) S="2020-01-01 00:00" E="2020-01-02 00:00" AQWPDownload(Location,Dataset,Unit,DateRange="Custom", StartTime=S,EndTime=E,file=tempfile("AQWP",fileext=".json")) ## End(Not run)
Function to load in an Aquarius json file, downloaded from https://water.data.sa.gov.au, possibly using AWQPDownload()
AQWPLoad(filename, qual_codes = TRUE, long_format = TRUE)AQWPLoad(filename, qual_codes = TRUE, long_format = TRUE)
filename |
A file downloaded from the Export Data tab on https://water.data.sa.gov.au, or using AQWPDownload() |
qual_codes |
TRUE/FALSE to return quality codes. Defaults to true |
long_format |
TRUE/FALSE to return data in long format, rather than wide (e.g. a spreadsheet). Long is useful for plotting with ggplot |
A tibble with the data in the file
## Not run: AQWPLoad("AQWP.json") ## End(Not run)## Not run: AQWPLoad("AQWP.json") ## End(Not run)
This function use the API associated with states' Hydstra databases to return useful site information.
HydstraSiteDetails(site, state, out_folder, flood_level = NA)HydstraSiteDetails(site, state, out_folder, flood_level = NA)
site |
station number, e.g. "425018" |
state |
relevant state database foro the station, e.g. "NSW" |
out_folder |
path to folder to save outputs |
flood_level |
optional, water level in stage datum to plot on the cross section data |
Currently, the relevant websites are useful for site discovery:
https://water-monitoring.information.qld.gov.au
https://realtimedata.waternsw.com.au
https://data.water.vic.gov.au/WMIS
The Bureau of Meteorology's Water Data Online site is also useful, which can also be queried using get_station_list() from BomWater package.
The function will save a number of files to out_folder that have a file name starting with the station number followed by:
site_info.csv: general site information returned, e.g. site name, coordinates, length of record, elevation
x_sec.csv: chainage chain and elevation (rl in gauge datum) of the control section
rating.csv: current rating curve, the discharge (vf in ML/d) for a gauge height vf, and also as above the cease to flow level (above_ctf)
gaugings.csv: record of streamflow gaugings available
discharge.csv: daily time series of streamflow, over a 9am - 9am period
plot.png: summary plot of the above data
Quality codes shown on the plot are those used by the Bureau of Meteorology defined here
a vector of length 3, with the number of cross sections, rating curves and streamflow gaugings found, respectively.
## Not run: HydstraSiteDetails("425018","NSW","c:/Temp") ## End(Not run)## Not run: HydstraSiteDetails("425018","NSW","c:/Temp") ## End(Not run)
Function to import a Source .res.csv File Returns data (as a Data Frame, Zoo, or tibble) as a time Series with all Results Read Source .res.csv file into a data table or zoo time series
read_res.csv(resFile, returnType = "df")read_res.csv(resFile, returnType = "df")
resFile |
A character string representing the full file path of the .res.csv file |
returnType |
A character string to set the return type: "z", "t", "df". If not matching "t" (tibble) or "z" (zoo), data frame returned. |
Data in the format selected with all data read in from the Source .res.csv file
## Not run: X = read_res.csv("./SWTools/extdata/Scenario1.res.csv",returnType="t") ## End(Not run)## Not run: X = read_res.csv("./SWTools/extdata/Scenario1.res.csv",returnType="t") ## End(Not run)
Compute tests on rainfall double mass curves and cumulative deviation in annual rainfall totals to test for consistency between a rainfall station and the average of another group of stations. Non-homogeneity can occur for a number of reasons, such as interception from vegetation or buildings over time, moving of a station location, or due to interpolation of missing data or station closure
SILOCheckConsistency(X, folder = NA, pvallim = 0.05, changelim = 0.025)SILOCheckConsistency(X, folder = NA, pvallim = 0.05, changelim = 0.025)
X |
A list of SILO station data, in the format created by |
folder |
Path to folder to save resulting images to. Will be created if it doesn't exist |
pvallim |
p value limit of the break point detection to display the double mass break point. Defaults to p=0.05 |
changelim |
significant slope limit display the double mass break point. Defaults to a slope change of 0.025 |
Two tests are calculated by SILOCheckConsistency, which are outlined in Annex 4 of Allen et al. (1998).
The first considers the residual errors in annual rainfall at a station, compared to the straight line (intercept=0) regression with the average annual rainfall from the other sites in X.
The residuals should follow a normal distribution with mean zero and standard deviation s_y,x. The annual rainfall data is plotted to visually assess the homoscedasticity requirement (constant variance).
Ellipses for 80\
The second test tests for a break point in the plot of cumulative annual rainfall, commonly referred to as a double-mass analysis. This analysis is outlined in Allen et al. (1998) and also Chang and Lee (1974). A bootstraped estimate of any breakpoint in the double-mass plot, indicating a change in the relationship between rainfall at the station and the average of all other stations, is assessed using the method of Muggeo (2003), as provided in segmented.
If folder is not specified (or NA) the plots are shown in the R environment. If folder is specified, a figure for each station in X is saved to folder. There are 4 panels on the figure:
Annual rainfall for a given station, against the average across all stations in X (except the station presented).
Cumulative residuals of the annual rainfall from the straight line regression shown in the first panel. Assuming the residuals are are independent random variables, this figure include ellipses representing 80th and 95th percentile that the hypothesis that there is no change in slope can be rejected.
double mass curve, plotting the cumulative annual rainfall for the station against the station average. If a breakpoint is identified, this is displayed on the plot.The colours represent the median quality code for each year, with the same colour palette as SILOQualityCodes
Residuals of the cumulative rainfall from the straight line fitted to the double mass curve.
Chang, M., and Lee, R. (1974) Objective double-mass analysis, Water Resour. Res., 10( 6), 1123-1126, doi:10.1029/WR010i006p01123.
Allan, R., Pereira, L. and Smith, M. (1998) Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56.
Muggeo, V.M.R. (2003) Estimating regression models with unknown break-points. Statistics in Medicine 22, 3055-3071.
SILOLoad, SILOSiteSummary, SILOQualityCodes,SILOCorrectSite
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOCheckConsistency(X,tempdir()) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOCheckConsistency(X,tempdir()) ## End(Not run)
If the break point of a non-homogenous rainfall station has been identified (potentially using SILOCheckConsistency), correct the data on one side of the breakpoint
SILOCorrectSite( X, s_correct, s_reference, year_break, year_start = NULL, year_end = NULL, after = TRUE, plot = NA )SILOCorrectSite( X, s_correct, s_reference, year_break, year_start = NULL, year_end = NULL, after = TRUE, plot = NA )
X |
A list of SILO station data, in the format created by |
s_correct |
Station number that exists in |
s_reference |
Station number that exists in |
year_break |
year in the time series that the break points exists |
year_start |
first year of data (before |
year_end |
last year of data (after |
after |
TRUE/FALSE value, indicating if the homogeneous data to develop the relationship to correct the non-homogeneous data is after the breakpoint ( |
plot |
if specified, the file (including path if necessary) to save a scatter plot of the annual rainfall totals, including regression equations used to correct the non-homogeneous data. |
The method of cumulative residuals outlined in Annex 4 of Allen et al. (1998) has been used.
That is, two linear regressions between the annual rainfall totals are calculated P_s_correct~P_s_reference over the periods year_start:year_break and year_break:year_end
For the period to correct (after the breakpoint if after=TRUE) an annual scaling factor is calculated from the ratio of the predicted rainfall total from the two regression equations, based on the rainfall total for each year at the reference site.
This scaling factor is then applied to the daily rainfall data for that year.
A list with the same structure as X, with the element for s_correct updated with the corrections on one side of the breakpoint year.
Chang, M., and Lee, R. (1974) Objective double-mass analysis, Water Resour. Res., 10( 6), 1123– 1126, doi:10.1029/WR010i006p01123.
SILOLoad, SILOSiteSummary, SILOQualityCodes,SILOCorrectSite
## Not run: stations<-c("23313","23302","23300","23317","23725","23705") SILODownload(stations) X<-SILOLoad(stations,startdate="1891-01-01",enddate="2020-12-31") X<-SILOCorrectSite(X,"23313","23705",1970,after=FALSE) ## End(Not run)## Not run: stations<-c("23313","23302","23300","23317","23725","23705") SILODownload(stations) X<-SILOLoad(stations,startdate="1891-01-01",enddate="2020-12-31") X<-SILOCorrectSite(X,"23313","23705",1970,after=FALSE) ## End(Not run)
Plot the cumulative deviation from the mean for each silo station on one plot
SILOCumulativeDeviation(SILO, filename = NULL, cols = pkg.env$cols)SILOCumulativeDeviation(SILO, filename = NULL, cols = pkg.env$cols)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
optional, filename to write the plot to, including extension (e.g. .png). Filename can include full path or sub folders. |
cols |
optional, a vector of colours to use for the plotting |
a ggplot plot of the cumulative deviation from the mean.
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOCumulativeDeviation(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOCumulativeDeviation(X) ## End(Not run)
Plot double mass curves of each rainfall site against each other
SILODoubleMass(SILO, filename = NULL, plotsperpage = 4)SILODoubleMass(SILO, filename = NULL, plotsperpage = 4)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
optional, filename to write the plot to, including extension. Filename can include full path or sub folders. |
plotsperpage |
optional, number of plots to output per element of the list returned. Defaults to 4 |
a list of ggplot objects that plot of the double mass curves of each station in the SILO list against each other. The double mass plot is on the bottom diagonal, and the slope of the line for each case in the upper diagonal. Each list element contains plotsperpage (default to 4) double mass plots, to allow them to be plotted on multiple pages
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILODoubleMass(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILODoubleMass(X) ## End(Not run)
Download SILO data
SILODownload( SiteList, username = "[email protected]", password = "gui", path = getwd(), startdate = "18890101", enddate = NULL, ssl = FALSE )SILODownload( SiteList, username = "[email protected]", password = "gui", path = getwd(), startdate = "18890101", enddate = NULL, ssl = FALSE )
SiteList |
A station number or vector of station numbers, as a string (e.g. "24001") |
username |
SILO user name. Defaults to credentials used by https://www.longpaddock.qld.gov.au/silo/point-data/ |
password |
SILO password |
path |
Where to save the output. Will default to getwd() if not specified |
startdate |
First day of data, in the format "YYYYMMDD". Will default to the first day of the record "18890101" if not specified |
enddate |
Last day of data, in the format "YYYYMMDD". Will default to yesterday if not specified |
ssl |
if true set ssl_cipher_list to "RC4-SHA" for file download. Seems to be necessary on some machines. default to FALSE |
A file for each station will be saved to path, named station number.txt. Nothing is returned to the R environment.
## Not run: SILODownload(c("24001","24002","24003"), path=tempdir(), startdate="20180101",enddate="20200101") ## End(Not run)## Not run: SILODownload(c("24001","24002","24003"), path=tempdir(), startdate="20180101",enddate="20200101") ## End(Not run)
Import a SILO file
SILOImport(station, path, startdate, enddate)SILOImport(station, path, startdate, enddate)
station |
Station number (e.g. "24001") to import. The function expects the file to be called "24001.txt". |
path |
Location where the file is located. Use "/" or "\\" for folders. Defaults to getwd() if not specified. |
startdate |
Start date of data to load, in format "YYYY-MM-DD". Defaults to start of the file if not provided |
enddate |
End date of data to load, in format "YYYY-MM-DD". Defaults to end of the file if not provided |
a list of data from the file, with members:
the raw data as a daily zoo object
the name of the site
the station number
Longitude
Latitude
the first date with good quality rainfall data
the last date with good quality rainfall data
the percentage of good quality coded rainfall data between start and end
Import multiple SILO files
SILOLoad(sites, path = getwd(), startdate, enddate)SILOLoad(sites, path = getwd(), startdate, enddate)
sites |
a vector of Station numbers (e.g. c("24001","24002","24003")) to import. The function expects the file to be called "24001.txt". |
path |
Location where the file is located. Use "/" or "\\" for folders. Defaults to getwd() if not specified. |
startdate |
Start date of data to load, in format "YYYY-MM-DD". Defaults to start of the file if not provided |
enddate |
End date of data to load, in format "YYYY-MM-DD". Defaults to end of the file if not provided |
a list of data from the file, with members:
the raw data as a daily zoo object
the name of the site
the station number
Longitude
Latitude
the first date with good quality rainfall data
the last date with good quality rainfall data
the percentage of good quality coded rainfall data between start and end
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") ## End(Not run)
Plot a map of the SILO station locations
SILOMap(SILO, filename = NULL)SILOMap(SILO, filename = NULL)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
optional, filename to write the plot to, including extension. Filename can include full path or sub folders. |
a google map of the SILO station locations
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMap(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMap(X) ## End(Not run)
Plot a boxplot of monthly rainfall with mean monthly evaporation
SILOMonthlyRainfall( SILO, evapcol = "Mwet", filename = NULL, cols = pkg.env$cols )SILOMonthlyRainfall( SILO, evapcol = "Mwet", filename = NULL, cols = pkg.env$cols )
SILO |
a list of sites with SILO data, as created by SILOLoad() |
evapcol |
name of an evaporation column to plot, defaults to "MWet". |
filename |
optional, filename to write the plot to, including extension. Filename can include full path or sub folders. |
cols |
optional, a vector of colours to use for the plotting |
a ggplot of the monthly rainfall and evaporation.
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMonthlyRainfall(X,"Span",cols=c("black","red","#124734")) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMonthlyRainfall(X,"Span",cols=c("black","red","#124734")) ## End(Not run)
Produces a tile plot displaying the quality codes for variables that are input to the calculation of Morton's evaporation equations, being maximum and minimum temperature, solar radiation and vapor pressure (derived from wet bulb temperature). Evaporation is also plotted, if the site has pan observations.
SILOMortonQualityCodes(SILO, filename = NULL)SILOMortonQualityCodes(SILO, filename = NULL)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
optional, filename to write a plot of the rainfall quality codes to, including extension (e.g. png). Filename can include full path or sub folders. |
a ggplot geom_tile plot of the rainfall quality codes
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMortonQualityCodes(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOMortonQualityCodes(X) ## End(Not run)
Plot the quality codes of the SILO rainfall data
SILOQualityCodes(SILO, filename = NULL)SILOQualityCodes(SILO, filename = NULL)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
optional, filename to save a plot of the rainfall quality codes to, including extension (e.g. .png). Filename can include full path or sub folders. |
a ggplot geom_tile plot of the rainfall quality codes
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOQualityCodes(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOQualityCodes(X) ## End(Not run)
Write SILO data report to word document. The report includes output from SILOSiteSummary(), SILOQualityCodes(), SILOMortonQualityCodes(). SILOMap(), SILOMonthlyRainfall(), SILOCumulativeDeviation() and SILODoubleMass().
SILOReport(SILO, filename, path = getwd(), cols = pkg.env$cols)SILOReport(SILO, filename, path = getwd(), cols = pkg.env$cols)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
filename |
filename to write the report to. |
path |
Optional. Folder to save the report to, defaults to current working directory |
cols |
Optional. vector of colours to use for the monthly rainfall and cumulative deviation plots. Must be at least as long as the number of sites in the SILO list. |
Nothing to the environment. A word document report is written to "filename".
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOReport(X,"MyReport.docx") #requires pandoc installed ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOReport(X,"MyReport.docx") #requires pandoc installed ## End(Not run)
Find SILO sites within a polygon
SILOSitesfromPolygon(shpFile, ssl = FALSE, buffer = 0)SILOSitesfromPolygon(shpFile, ssl = FALSE, buffer = 0)
shpFile |
location to a shapefile to search within for SILO sites |
ssl |
See SILODownload, if true if true sets ssl_cipher_list="RC4-SHA" for httr::GET() |
buffer |
distance in km to buffer the shapefile to look for sites outside the catchment The buffer distance is approximate for a couple of reasons: the shapefile is projected to match SILO site coordinates, WGS84 and sf::st_buffer does not correctly buffer longitude/latitude data. sdaf Also the input distance in km is converted to degrees using the conversion at the equator of 0.008. |
a table of site information including site numbers found within the polygon
## Not run: Sites=SILOSitesfromPolygon("path/to/shapefile.shp") SILODownload(Sites$Number, path=tempdir(), startdate="20180101",enddate="20200101") X<-SILOLoad(Sites$Number,path=tempdir()) ## End(Not run)## Not run: Sites=SILOSitesfromPolygon("path/to/shapefile.shp") SILODownload(Sites$Number, path=tempdir(), startdate="20180101",enddate="20200101") X<-SILOLoad(Sites$Number,path=tempdir()) ## End(Not run)
Produce a table summarising SILO sites
SILOSiteSummary(SILO)SILOSiteSummary(SILO)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
a dataframe with the following columns
site name
station number
date of the first good quality rainfall data
date of the last good quality rainfall data
percentage of days that do not have good quality code between StartDate and EndDate
Mean annual rainfall in mm
Latitude
Longitude
Elevation
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") d<-SILOSiteSummary(X) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") d<-SILOSiteSummary(X) ## End(Not run)
Function to generate Thiessen polygons from SILO sites
SILOThiessenShp(SILOdata, path, shpname, boundary = NULL)SILOThiessenShp(SILOdata, path, shpname, boundary = NULL)
SILOdata |
|
path |
|
shpname |
|
boundary |
|
A simple feature geometry (sf::sfc object) of the polgyons created. Shape file saved to path \ shpname
If boundary is specified weights are written to the attribute table of the polygon return, which can be extracted with
st_drop_geometry(returnedfeature[c("Station","weights")])
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOThiessenShp(X,tempdir(),"Theissens") a<-SILOSiteSummary(X) ggplot(p)+geom_sf(aes(fill=AnnualRainfall))+ geom_point(data=a,aes(Longitude,Latitude))+ geom_text(data=a,aes(Longitude,Latitude,label=Site),nudge_y = 0.02) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") p<-SILOThiessenShp(X,tempdir(),"Theissens") a<-SILOSiteSummary(X) ggplot(p)+geom_sf(aes(fill=AnnualRainfall))+ geom_point(data=a,aes(Longitude,Latitude))+ geom_text(data=a,aes(Longitude,Latitude,label=Site),nudge_y = 0.02) ## End(Not run)
Write a SILO time series to a csv file in the format expected by eWater Source
SILOWriteforSource(SILO, col, filename, scalefactor = 1)SILOWriteforSource(SILO, col, filename, scalefactor = 1)
SILO |
a list of sites with SILO data, as created by SILOLoad() |
col |
Name of a column in a silo file to write out, e.g. Rain |
filename |
file to write to. |
scalefactor |
factor to scale the data by. Defaults to 1. Useful for Pan evap or rainfall scaling. Could also be a vector, with a value for each station in SILO |
Nothing to the R environment. SILO data is written to "filename".
## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOWriteforSource(X,"Rain",tempfile("Rainfall",fileext=".csv")) ## End(Not run)## Not run: X<-SILOLoad(c("24001","24002","24003"),path="./SWTools/extdata") SILOWriteforSource(X,"Rain",tempfile("Rainfall",fileext=".csv")) ## End(Not run)
Function to bulk create functions for SILO data in Source.
SILOWriteFunctionsforSource( X, boundary, shpColumn, functionsfile, RRfile, RainfallDatasourcesFolder, PETDatasourcesFolder, RainfallDatafile, PETDatafile, fus )SILOWriteFunctionsforSource( X, boundary, shpColumn, functionsfile, RRfile, RainfallDatasourcesFolder, PETDatasourcesFolder, RainfallDatafile, PETDatafile, fus )
X |
List of SILO station data, loaded into R using SILOLoad. |
boundary |
path to a subcatchment shapefile containing the subcatchments in the Source catchment model |
shpColumn |
column in the shapefile attribute table that corresponds to the catchment numbering. |
functionsfile |
filename to create with functions to import into Source |
RRfile |
filename to create to be imported into the Source Rainfall Runoff feature table |
RainfallDatasourcesFolder |
Name to use when creating a folder in the Source function editor for the rainfall functions and time series variables |
PETDatasourcesFolder |
Name to use when creating a folder in the Source function editor for the PET functions and time series variables |
RainfallDatafile |
Filename of data source loaded in Source for rainfall, in formatting used by Source (e.g. for a file called Rain.csv from a relative folder called TimeseriesData is TimeSeriesData_Rain_csv). |
PETDatafile |
Filename of data source loaded in Source for PET, in formatting used by Source |
fus |
character vector of function unit names in the model. It is assumed that the Source rainfall-runoff scenario was created using the Geographic wizard, using the 'draw network' method (as opposed to DEM based)
This allows a raster to be loaded into Source, with an integer in each cell representing the different subcatchments.
This function will create two files:
|
Nothing to the R environment. Files functionsfile and RRfile are created.
## Not run: X<-SILOLoad(sites) shpColumn<-"OBJECTID" functionsfile<-"functions.csv" RRfile<-"RRFile.csv" RainfallDatasourcesFolder<-"Rainfall" PETDatasourcesFolder<-"PET" RainfallDatafile<-"TimeSeriesData_Rain_csv" PETDatafile<-"TimeSeriesData_MWet_csv" fus<-c("regolith","igneous","carbonate","sedimentary") SILOWriteFunctionsforSource(X,boundary,shpColumn,functionsfile,RRfile, RainfallDatasourcesFolder,PETDatasourcesFolder, RainfallDatafile,PETDatafile,fus) ## End(Not run)## Not run: X<-SILOLoad(sites) shpColumn<-"OBJECTID" functionsfile<-"functions.csv" RRfile<-"RRFile.csv" RainfallDatasourcesFolder<-"Rainfall" PETDatasourcesFolder<-"PET" RainfallDatafile<-"TimeSeriesData_Rain_csv" PETDatafile<-"TimeSeriesData_MWet_csv" fus<-c("regolith","igneous","carbonate","sedimentary") SILOWriteFunctionsforSource(X,boundary,shpColumn,functionsfile,RRfile, RainfallDatasourcesFolder,PETDatasourcesFolder, RainfallDatafile,PETDatafile,fus) ## End(Not run)
Get vector of InputSets
VeneerGetInputSets(baseURL = "http://localhost:9876")VeneerGetInputSets(baseURL = "http://localhost:9876")
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
vector containing info on Input Sets in the model
## Not run: VeneerGetInputSets() ## End(Not run)## Not run: VeneerGetInputSets() ## End(Not run)
Get a vector of node names for a given type
VeneerGetNodesbyType(NodeType, baseURL = "http://localhost:9876")VeneerGetNodesbyType(NodeType, baseURL = "http://localhost:9876")
NodeType |
The node to return the names of. The icon in /network is searched for this name |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
vector of node names matching the specified node type
## Not run: VeneerGetNodesbyType("Weir") ## End(Not run)## Not run: VeneerGetNodesbyType("Weir") ## End(Not run)
Get data from a Source piecewise table using Veneer
VeneerGetPiecewise(pw_table, baseURL = "http://localhost:9876")VeneerGetPiecewise(pw_table, baseURL = "http://localhost:9876")
pw_table |
The name of the piecewise linear variable, without the $ |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
a matrix with the data from the piecewise table.
## Not run: VeneerGetPiecewise(data,"pw_table") ## End(Not run)## Not run: VeneerGetPiecewise(data,"pw_table") ## End(Not run)
Get a time series result from Source using Veneer
VeneerGetTS(TSURL, baseURL = "http://localhost:9876")VeneerGetTS(TSURL, baseURL = "http://localhost:9876")
TSURL |
the URL of the time series to retrieve |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
a zoo time series of the data
The URL of the time series must be specified, by interrogation using a browser or other analysis. By default Source returns SI units. Some conversion is undertaken:
Flow converted to ML/d
Volume converted to ML
Area converted to ha
Spaces are OK, like in the example below (dont need to insert %20 for example).
## Not run: VeneerGetTS("/runs/latest/location/EndofSystem/element/Downstream Flow/variable/Flow") ## End(Not run)## Not run: VeneerGetTS("/runs/latest/location/EndofSystem/element/Downstream Flow/variable/Flow") ## End(Not run)
Get all time series recorded in Source for a given node
VeneerGetTSbyNode(Node, run = "latest", baseURL = "http://localhost:9876")VeneerGetTSbyNode(Node, run = "latest", baseURL = "http://localhost:9876")
Node |
Name of node to retrieve Time Series for |
run |
Which run to retrieve from. Defaults to the latest |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
a zoo time series, with each variable as a column
## Not run: VeneerGetTSbyNode("Storage 1") ## End(Not run)## Not run: VeneerGetTSbyNode("Storage 1") ## End(Not run)
Get all time series recorded in Source of a given variable type
VeneerGetTSbyVariable( variable = "Flow", run = "latest", baseURL = "http://localhost:9876" )VeneerGetTSbyVariable( variable = "Flow", run = "latest", baseURL = "http://localhost:9876" )
variable |
Which variable to retrieve. Defaults to Flow. |
run |
Which run to retrieve from. Defaults to the latest |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
a zoo time series, with each output as a column
## Not run: VeneerGetTSbyVariable() #returns all flow outputs recorded in the latest run VeneerGetTSbyVariable("Water Surface Elevation",1) ## End(Not run)## Not run: VeneerGetTSbyVariable() #returns all flow outputs recorded in the latest run VeneerGetTSbyVariable("Water Surface Elevation",1) ## End(Not run)
Get a vector of the type of time series variables recorded
VeneerGetTSVariables(run = "latest", baseURL = "http://localhost:9876")VeneerGetTSVariables(run = "latest", baseURL = "http://localhost:9876")
run |
Which run to retrieve from. Defaults to the latest |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
a vector of variable types (e.g. Downstream flow, Downstream Flow Concentration, water surface elevation)
## Not run: VeneerGetTSVariables() ## End(Not run)## Not run: VeneerGetTSVariables() ## End(Not run)
Get the number of the latest run
VeneerlatestRunNumber(baseURL = "http://localhost:9876")VeneerlatestRunNumber(baseURL = "http://localhost:9876")
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
integer of the latest run number
## Not run: VeneerlatestRunNumber() ## End(Not run)## Not run: VeneerlatestRunNumber() ## End(Not run)
Run Source using Veneer
VeneerRunSource( StartDate = NULL, EndDate = NULL, InputSet = NULL, baseURL = "http://localhost:9876" )VeneerRunSource( StartDate = NULL, EndDate = NULL, InputSet = NULL, baseURL = "http://localhost:9876" )
StartDate |
Optional. Start date for simulation. Must be dd/mm/yyyy |
EndDate |
Optional. End date for simulation. Must be dd/mm/yyyy |
InputSet |
Optional. Input set to use |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
Nothing to the R environment.
If not set, the configuration parameters (StartDate, EndDate, InputSet), was is specified in the Source configuration in the GUI will be used.
The console will show any errors returned by Veneer.
## Not run: VeneerRunSource() VeneerRunSource("01/07/2017","01/02/2018","NoDams") ## End(Not run)## Not run: VeneerRunSource() VeneerRunSource("01/07/2017","01/02/2018","NoDams") ## End(Not run)
Update a function value or expression. Function must exist before being updated.
VeneerSetFunction(Name, Expression, baseURL = "http://localhost:9876")VeneerSetFunction(Name, Expression, baseURL = "http://localhost:9876")
Name |
Name of the function without the "$", e.g. f_ScaleFactor |
Expression |
Expression to change it to, e.g. 1.2 |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
Nothing to the R environment.
## Not run: VeneerSetFunction("f_ScaleFactor",1.2) VeneerSetFunction("f_TargetLevel","if($m_Flow<1000,3.2,3.5)") ## End(Not run)## Not run: VeneerSetFunction("f_ScaleFactor",1.2) VeneerSetFunction("f_TargetLevel","if($m_Flow<1000,3.2,3.5)") ## End(Not run)
Change a Source piecewise table using Veneer
VeneerSetPiecewise(data, pw_table, baseURL = "http://localhost:9876")VeneerSetPiecewise(data, pw_table, baseURL = "http://localhost:9876")
data |
A 2 column data.frame or matrix with the data to load into the piecewise table. |
pw_table |
The name of the piecewise linear variable, without the "$". |
baseURL |
URL of the Veneer server. Defaults to the veneer default. |
Nothing to the R environment.
## Not run: data<-data.frame(X=seq(1,5),Y=seq(1,5)) VeneerSetPiecewise(data,"pw_table") ## End(Not run)## Not run: data<-data.frame(X=seq(1,5),Y=seq(1,5)) VeneerSetPiecewise(data,"pw_table") ## End(Not run)
Write an input set line for a piecewise lookup table from a csv file
WritepwtoIS(folder, csvfiles, outputfile)WritepwtoIS(folder, csvfiles, outputfile)
folder |
Folder for where are the csv files with the lookup tables |
csvfiles |
vector of files to turn into an input set line. File name should be the name of the pw table in Source, including the folder name if necessary, separated by "." (see example). The first row in the file should be column names, the same as used in Source, i.e. XValue and YValue |
outputfile |
text file to save the lines to |
Nothing to the R environment. Input set lines are written to "outputfile".
## Not run: folder<-"C:/Source/tables" csvfiles<-c("LowerLakesOps.pw_LakeTarget.csv","Operations.pw_NA_Lock5_16p8.csv") outputfile<-"inputset.txt" WritepwtoIS(folder,csvfiles,outputfile) ## End(Not run)## Not run: folder<-"C:/Source/tables" csvfiles<-c("LowerLakesOps.pw_LakeTarget.csv","Operations.pw_NA_Lock5_16p8.csv") outputfile<-"inputset.txt" WritepwtoIS(folder,csvfiles,outputfile) ## End(Not run)