PlotStationsNorway

R package for plotting caharcetristics of streamflow stations on a map of Norway

Installation

Download the *.R files into your own directory and 'source' them:

setwd('C:/Users/koe/Documents/PlotStationsNorway/PlotStationsNorway')
source('PlotMap.R')

You will need the RNetCDF package:

install('maptools')
install('RColorBrewer')

The data used here is available upon request Shape file with catchment boundaries for NVE gauging stations might be downloaded from http://nedlasting.nve.no/gis/, and you should select the GIS dataset HYDROLOGISKE DATA->Totalnedbørfelt til målestasjon

Shape file with location of gauging stations might be downloaded from http://nedlasting.nve.no/gis/, and you should select the GIS dataset HYDROLOGISKE DATA->Målseserier

Preprosessing: Loading the GIS-data into the working environment

The shape-files with catchments boundaries are loaded into teh base environment, this includes:

• Norge : A shape file with outline of Norway. Loaded as a SpatialPolygonsDataFrame
• Mycatchments A shape file with ploygons for all gauged catchments in Norway. Loaded as a SpatialPolygonsDataFrame
• MyStations A shape file with points for all hydrological measurement locations in Norway. Loaded as a SpatialPointsDataFrame
• forecasting_c A shape file with ploygons for the flood forecasting catchments. Loaded as a SpatialPolygonsDataFrame
• forecasting_s A shape file with points for the flood forecasting catchments. Loaded as a SpatialPointsDataFrame
• spar A table with the catchment characteristics

Arguments: GiSfolder is the folder where the shape-files are stored ccfile is a text-file with catchment characteristics. If ccfile is NA, the array mnumbers has to be specified. mnumbers is an array with station numbers specified as regine_nr*10000+main_nr. If mnumbers is NA, the file with catchment characteristics has to be specified.

GisFolder<-'inst/GISDATA/'
ccfile<-"inst/feltparametre_flomstasjoner145.txt"
load_data_covers(GisFolder,ccfile=ccfile)

load_data_covers(GisFolder,mnumbers=slist)

Loading example data to be plotted:

corr_all<-read.table('inst/correlations.txt')
Reff_all<-read.table('inst/Reff.txt')
crpss_all<-read.table('inst/crpss.txt')
bss_all<-read.table('inst/bss.txt')
csi_all<-read.table('inst/csi.txt')
roc_all<-read.table('inst/roc.txt')

Plotting values on a map

• cvalues is a matrix where each row represent a station and the row name is the station ID given as regine number dot main number (e.g."2.11").
• mappoints is a a SpatialPointsDataFrame with the station points
• mapBorders is a a SpatialPolygonsDataFrame with the outline of Norway.
• pname is the name of the palette as defined by 'RColorBrewer' package.
• pinv is TRUE if the colors should be inverted.
• v_index is the index of the colomn to be plotted.
• c_index is a possible colomn with the minimum significant value
• p_index is a possible coloumn with p-values
• cbins is used for binning the data in v_index. Each bin gets its own color
• legtitle is the title of the legend

Some examples are given below:

# A plot where v_index and c_index is specified. The insignificant points is colored grey. 
plot_map_points(cvalues=corr_all,mappoints=forecasting_s,mapborders=Norge,pname='Spectral',pinv=TRUE,v_index=8,c_index=10,cbins=c(-1.0,0.3,0.4,0.5,0.6,0.7,0.8,0.9),legtitle="Correlation")

# A plot where only v_index is specified. Assumes a small number of unique values, each value gets its own color. 
plot_map_points(cvalues=corr_all,mappoints=forecasting_s,mapborders=Norge,pname='Spectral',pinv=TRUE,v_index=9,legtitle="Month")

# A plot where v_index and cbins is specified. In this case values lower than the lowest bin are colored grey
plot_map_points(cvalues=Reff_all,mappoints=forecasting_s,mapborders=Norge,pname='Spectral',pinv=TRUE,v_index=8,cbins=c(0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7),legtitle="Reff")

# a plot where v_index and p-values are specified. Insignificant points are grey
plot_map_points(cvalues=roc_all,mappoints=forecasting_s,mapborders=Norge,pname='Spectral',pinv=TRUE,v_index=8,p_index=17,cbins=c(0.5,0.6,0.65,0.7,0.75,0.8,0.85,0.9,0.95,1.0),legtitle="ROC-area")