Download Global HBV Parameter MapsSource:
SpatVector. A polygon layer with area of interest.
Numeric. A numeric vector from 1 to 10 indicating the folds numbers to process.
Logical. If TRUE, return mean zonal statistics, calculated using
globalmethod from terra package
Logical. If TRUE, reproject the HBV rasters to
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.
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).
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
# 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[])