Note: This document is for an older version of GRASS GIS that has been discontinued. You should upgrade, and read the current manual page.
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
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
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.
This is an example of a temporal integration from a weather station as done by
Chemin and Alexandridis (2004)
Chemin and Alexandridis, 2004. Spatial Resolution Improvement of Seasonal
Evapotranspiration for Irrigated Rice, Zhanghe Irrigation District, Hubei Province, China.
Asian Journal of Geoinformatics, Vol. 5, No. 1, September 2004
(PDF)
i.eb.eta,
i.evapo.mh,
i.evapo.pt,
i.evapo.pm,
r.sun
Yann Chemin, International Rice Research Institute, The Philippines
SOURCE CODE
Available at:
i.evapo.time source code
(history)
Latest change: Wednesday Dec 27 16:18:17 2023 in commit: 2e4507f76058083509a784e64f9325fdd732aa87
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GRASS Development Team,
GRASS GIS 8.3.3dev Reference Manual