ROSETTA.centroids | R Documentation |
Average soil hydraulic parameters generated by the first stage predictions of the ROSETTA model by USDA soil texture class. These data were extracted from ROSETTA documentation and re-formatted for ease of use.
data(ROSETTA.centroids)
A data frame:
soil texture class, ordered from low to high available water holding capacity
average saturated water content
average residual water content
average value, related to the inverse of the air entry suction, log10-transformed values with units of cm
average value, index of pore size distribution, log10-transformed values with units of 1/cm
1 standard deviation of theta_r
1 standard deviation of theta_s
1 standard deviation of alpha
1 standard deviation of npar
approximate volumetric water content at which soil material is saturated
approximate volumetric water content at which matrix potential = -33kPa
approximate volumetric water content at which matrix potential = -1500kPa
approximate available water holding capacity: VWC(-33kPa)
VWC(-1500kPa)
Theoretical water-retention parameters for uniform soil material of each texture class have been estimated via van Genuchten model.
ROSETTA Class Average Hydraulic Parameters
van Genuchten, M.Th. (1980). "A closed-form equation for predicting the hydraulic conductivity of unsaturated soils". Soil Science Society of America Journal. 44 (5): 892-898.
Schaap, M.G., F.J. Leij, and M.Th. van Genuchten. 2001. ROSETTA: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Journal of Hydrology 251(3–4): 163-176.
## Not run:
library(aqp)
library(soilDB)
library(latticeExtra)
data("ROSETTA.centroids")
# iterate over horizons and generate VG model curve
res <- lapply(1:nrow(ROSETTA.centroids), function(i) {
m <- KSSL_VG_model(VG_params = ROSETTA.centroids[i, ], phi_min = 10^-3, phi_max=10^6)$VG_curve
# copy generalized hz label
m$hz <- ROSETTA.centroids$hz[i]
# copy ID
m$texture_class <- ROSETTA.centroids$texture[i]
return(m)
})
# copy over lab sample number as ID
res <- do.call('rbind', res)
# check: OK
str(res)
# visual check: OK
xyplot(
phi ~ theta | texture_class, data=res,
type=c('l', 'g'),
scales=list(alternating=3, x=list(tick.number=10), y=list(log=10, tick.number=10)),
yscale.components=yscale.components.logpower,
ylab=expression(Suction~~(kPa)),
xlab=expression(Volumetric~Water~Content~~(cm^3/cm^3)),
par.settings = list(superpose.line=list(col='RoyalBlue', lwd=2)),
strip=strip.custom(bg=grey(0.85)),
as.table=TRUE
)
## End(Not run)
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