HBV.IANIGLA (version 0.2.6)

Precip_model: Altitude gradient based precipitation models

Description

Extrapolate precipitation gauge measurements to another heights. In this package version you can use the classical linear gradient model or a modified version which sets a threshold altitude for precipitation increment (avoiding unreliable estimations).

Usage

Precip_model(
       model,
       inputData,
       zmeteo,
       ztopo,
       param
)

Value

Numeric vector with the extrapolated precipitation series.

Arguments

model

numeric value with model option:

• 1: linear precipitation gradient (LP).

• 2: linear precipitation gradient with an upper threshold (LPM).

inputData

numeric vector with precipitation gauge series \([mm/\Delta t]\).

zmeteo

numeric value indicating the altitude of the precipitation gauge \([masl]\).

ztopo

numeric value with the target height \([masl]\).

param

numeric vector with the following parameters:

LP

• 1: precipitation gradient (gradP) [%/100m].

LPM

• 1: precipitation gradient (gradP) [%/100m].

• 2: threshold height. Precipitation does not increase when the altitude (ztopo) is higher than this parameter \([masl]\).

References

For some interesting work on precipitation gradients at catchment and synoptic scale see:

Immerzeel, W.W., Petersen, L., Ragettli, S., Pellicciotti, F., 2014. The importance of observed gradients of air temperature and precipitation for modeling runoff from a glacierized watershed in the Nepalese Himalayas. Water Resour. Res. 50, 2212–2226. https://doi.org/10.1002/2013WR014506

Viale, M., Nuñez, M.N., 2010. Climatology of Winter Orographic Precipitation over the Subtropical Central Andes and Associated Synoptic and Regional Characteristics. J. Hydrometeorol. 12, 481–507. https://doi.org/10.1175/2010JHM1284.1

Examples

# The following is a toy example. I strongly recommend to see
# the package vignettes in order to improve your skills on HBV.IANIGLA

## LP case
set.seed(369)

precLP <- Precip_model(model = 1, inputData = runif(n = 365, max = 30, min = 0),
                        zmeteo = 3000, ztopo = 4700, param = c(5))

## LPM case
set.seed(369)

precLPM <- Precip_model(model = 2, inputData = runif(n = 365, max = 30, min = 0),
                        zmeteo = 3000, ztopo = 4700, param = c(5, 4500))