Provides mapping functionality required for developing flood forecast models • mappER

The mappER library is part of the flode collection of tools. It provides all the mapping functionality required for developing flood forecast models.

Installation

You can install the development version of mappER from GitHub with:

# install.packages("devtools")
devtools::install_github("JonPayne88/mappER")

Example 1 - Collating spatial data

Datasets of class HydroImport or HydroAggs derived from the riskyData can be compiled into a shapefile.

library(mappER)
library(riskyData)
data(crowle); data(bickley); data(barnhurst); data(hollies); data(ledbury);
data(bettwsYCrwyn)
gcs <- getCoords(crowle,
                 bickley,
                 barnhurst,
                 hollies,
                 ledbury,
                 bettwsYCrwyn)
gcs
#> Simple feature collection with 6 features and 4 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -3.172591 ymin: 52.0317 xmax: -2.097173 ymax: 52.7993
#> Geodetic CRS:  WGS 84
#>      stationName  WISKI Easting Northing                   geometry
#> 1         Crowle 457592  393455   255757     POINT (-2.097173 52.2)
#> 2        Bickley 445031  363130   271330 POINT (-2.542565 52.33879)
#> 3      Barnhurst 091266  389910   301620  POINT (-2.15044 52.61225)
#> 4        Hollies 091862  381586   322452  POINT (-2.274545 52.7993)
#> 5        Ledbury 459793  370233   237123  POINT (-2.435301 52.0317)
#> 6 Bettws-Y-Crwyn 441011  320360   281360  POINT (-3.172591 52.4244)

These can be integrated into interactive plots with leaflet.

Example 2 - Thiessen polygons and calculate catchment Proportions

# Import catchment polygon
data("bewdCatch")

# Calculate Voronoi/Thiessen polygon
bewdTeeSun <- teeSun(gaugeCoords = gcs, catchment = bewdCatch)

Intersect the catchment polygon with the Thiessen polygons;

int <- intersectPoly(coords = gcs,
                     voronoi = bewdTeeSun,
                     catchment = bewdCatch)
plot(int, max.plot = 1, main = "Intersected catchment polygon")

From this we can calculate the gauge proportions with the gaugeProp() function;

gaugeProp(gcs, bewdCatch)
#>             Gauge  WISKI    Area Proportion
#> 1: Bettws-Y-Crwyn 441011 2465.18  57.127827
#> 2:        Hollies 091862 1050.89  24.353217
#> 3:        Bickley 445031  632.26  14.651928
#> 4:      Barnhurst 091266  166.87   3.867028

These can then be inserted into rain gauge catchment averaging equations.