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


imagery, evapotranspiration


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]

Allow output files to overwrite existing files

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog

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


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

1 each ETa pixel is divided by the same day ETo and become ETrF

2 each ETrF pixel is multiplied by the ETo sum for the representative days

3 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


ETo images preparation: If you only have one meteorological station data set, the easiest
way is:
for ETo_val in Eto[1] Eto[2] ...
r.mapcalc "eto$n = $ETo_val"
`expr n = n + 1`
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.

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