Download Global HBV Parameter Maps — hbv_get

This function download Global HBV Parameter Maps created by Beck et al. (2020) and crop it to the shapefile boundaries. See GloH2O website for details.

Usage

hbv_get_parameters(
  AOI,
  folds = 1:10,
  mean = FALSE,
  warp = TRUE,
  version = "v0.9"
)

Arguments

AOI: SpatVector. A polygon layer with area of interest.
folds: Numeric. A numeric vector from 1 to 10 indicating the folds numbers to process.
mean: Logical. If TRUE, return mean zonal statistics, calculated using global method from terra package
warp: Logical. If TRUE, reproject the HBV rasters to AOI projection
version: Character. Can be used to determine the dataset version. Must be one of "v0.8" (original release from February 5, 2020) or "v0.9" (revised version from May 5, 2020). See details.

Value

List

Details

Version history (according to GloH2O website):

V0.9 (May 5, 2022): To avoid local minima, the authors reduced the number of predictors to three and increased the number of generations to 2000. A selection was made based on which predictors individually provided the best training score: snowfall fraction of precipitation (FSNOW), mean topographic slope (SLOPE), and soil clay content (CLAY). Increasing the number of generations to 2000 allowed the algorithm to find the true optimum, while lowering the spatial resolution from 0.05° to 0.1° reduced computational requirements.
V0.8 (February 5, 2020): Original release corresponding to Beck et al. (2020).

References

Beck HE, Pan M, Lin P, Seibert J, van Dijk AIJM, Wood EF. 2020. Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments. Journal of Geophysical Research: Atmospheres 125 : e2019JD031485. DOI: 10.1029/2019JD031485

Examples


# Load shapefile
f <- system.file("ex/lux.shp", package="terra")
v <- vect(f)

# Get zonal statisitcs
fold1_mean <- hbv_get_parameters(v, folds = 1, mean = TRUE, warp = FALSE)
#> Downloading rasters...
#> Loading required namespace: pbapply
#> Cropping rasters...
fold1_mean
#> $fold_0
#>                mean
#> BETA     3.59133975
#> CET      0.00000000
#> CFMAX    4.76274042
#> CFR      0.02329523
#> CWH      0.03688424
#> FC     557.79513737
#> K0       0.11312447
#> K1       0.22010622
#> K2       0.14379373
#> LP       0.78630368
#> MAXBAS   1.80986611
#> PCORR    1.00000000
#> PERC     3.55778855
#> SFCF     1.00000000
#> TT      -0.06733536
#> UZL     56.14696222
#> 

# Get rasters
fold1_raster <- hbv_get_parameters(v, folds = 1, mean = FALSE, warp = FALSE)
#> Downloading rasters...
#> Cropping rasters...
plot(fold1_raster[[1]])