swe.gu19 {nixmass} | R Documentation |
Statistical SWE modeling based on a quadratic dependance on the day-of-year
Description
This model parameterizes bulk snow density with day-of-the-year as the only input similar to swe.pi16
but adds a quadratic dependance. It was calibrated for the regions of the whole Italian alps, and the subregions South-West, Central and South-East. By setting the cofficients of the empirical regression it can however be used with results from other datasets.
Usage
swe.gu19(data, region.gu19, n0=NA ,n1=NA, n2=NA)
Arguments
data |
A data.frame of daily observations with two columns named date and hs referring to day and snow depth at that day. The date column must be a character string with the format |
region.gu19 |
Must be one of the italian subalpine regions italy, southwest, central or southeast, defined in the original reference (see details), or myregion, in which case the coefficients n0, n1 and n2 have to be set. |
n0 , n1 , n2 |
Values |
Details
swe.gu19
Similar to the model of Pistocchi (2016), this function uses only the day-of-year (DOY) as parameterization for bulk snow density and hence SWE. In contrast to the latter, here, a quadratic term for DOY was added, to reflect non-linearity in the snow bulk density variability. The datums in the input data.frame are converted to DOY as days spent since November 1st. Regression coefficients depend on regions defined in Guyennon et al. (2019), which are italy for the Italian Alps, southwest for the South-western Italian Alps, central for the Central Italian Alpes or southeast for the South-western Italian Alps.
If region.gu19
is set to myregion, the coefficients no
, n1
and n2
must be set to values, obtained from a regression between densities and day-of-year from another dataset. It has to have the form density ~ DOY + DOY^2, where DOY is the day-of-year as defined in the original reference.
Non computable values are returned as NA.
Value
A vector with daily SWE values in mm.
References
Guyennon, N., Valt, M., Salerno, F., Petrangeli, A., Romano, E. (2019) 'Estimating the snow water equivalent from snow depth measurements in the Italian Alps', Cold Regions Science and Technology. Elsevier, 167 (August), p. 102859. doi: 10.1016/j.coldregions.2019.102859.
Pistocchi, A. (2016) 'Simple estimation of snow density in an Alpine region', Journal of Hydrology: Regional Studies. Elsevier B.V., 6 (Supplement C), pp. 82 - 89. doi: 10.1016/j.ejrh.2016.03.004.