GRASS GIS manual: i.evapo.time

Note: A new GRASS GIS stable version has been released: GRASS GIS 7.6, available here.
Updated manual page: here

NAME

i.evapo.time - Computes temporal integration of satellite ET actual (ETa) following the daily ET reference (ETo) from meteorological station(s).

KEYWORDS

imagery, evapotranspiration

SYNOPSIS

i.evapo.time

i.evapo.time --help

i.evapo.time eta=name[,name,...] eta_doy=name[,name,...] eto=name[,name,...] eto_doy_min=float start_period=float end_period=float output=name [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

--overwrite: Allow output files to overwrite existing files
--help: Print usage summary
--verbose: Verbose module output
--quiet: Quiet module output
--ui: Force launching GUI dialog

Parameters:

eta=name[,name,...] [required]: Names of satellite ETa raster maps [mm/d or cm/d]
eta_doy=name[,name,...] [required]: Names of satellite ETa Day of Year (DOY) raster maps [0-400] [-]
eto=name[,name,...] [required]: Names of meteorological station ETo raster maps [0-400] [mm/d or cm/d]
eto_doy_min=float [required]: Value of DOY for ETo first day
start_period=float [required]: Value of DOY for the first day of the period studied
end_period=float [required]: Value of DOY for the last day of the period studied
output=name [required]: Name for output raster map

DESCRIPTION
NOTES
SEE ALSO
AUTHOR

DESCRIPTION

i.evapo.time (i.evapo.time_integration) integrates ETa in time following a reference ET (typically) from a set of meteorological stations dataset. Inputs:

ETa images
ETa images DOY (Day of Year)
ETo images
ETo DOYmin as a single value

Method:

each ETa pixel is divided by the same day ETo and become ETrF
each ETrF pixel is multiplied by the ETo sum for the representative days
Sum all n temporal [ETrF*ETo_sum] pixels to make a summed(ET) in [DOYmin;DOYmax]

representative days calculation: let assume i belongs to range [DOYmin;DOYmax]

DOYbeforeETa[i] = ( DOYofETa[i] - DOYofETa[i-1] ) / 2
DOYafterETa[i] = ( DOYofETa[i+1] - DOYofETa[i] ) / 2

NOTES

ETo images preparation: If you only have one meteorological station data set, the easiest way is:

n=0
for ETo_val in Eto[1] Eto[2] ...
do
	r.mapcalc "eto$n = $ETo_val" 
	`expr n = n + 1`
done

with Eto[1], Eto[2], etc being a simple copy and paste from your data file of all ETo values separated by an empty space from each other.

If you have several meteorological stations data, then you need to grid them by generating Thiessen polygons or using different interpolation methods for each day.

For multi-year calculations, just continue incrementing DOY values above 366, it will continue working, up to maximum input of 400 satellite images.

AUTHOR

Yann Chemin, International Rice Research Institute, The Philippines

Last changed: $Date: 2014-12-27 14:28:56 -0800 (Sat, 27 Dec 2014) $

SOURCE CODE

Available at: i.evapo.time source code (history)