[Qgis-us-user] Standard precipitation index interpolation

karsten karsten at terragis.net
Thu Sep 3 12:25:59 PDT 2020

Hi Dani.
well generally for each point in time you would need run the kriging process
separately (each monthly data set for all points counts as one), so that
would be 30*12 = 360 times ...
So a lot of runs ...  if you really wanted to do that best would be to run
that as a batch process or script it in python for the processing toolbox...
Another good tool to look at for such things is the R Program
https://www.r-project.org/ and possibly using Raster instead of vector data
to create stacks of precipitation time series...
However, if I where you, I might step back first and determine what results
you would like to get or which comparisons you would want to make....  
I don't know what you are after - but for example would it make more sense
to look at the differences of one month over the 30 years time sequence to
detect changes in precipitation? 
This would make sense if you where to find dry versus wet years e.g. for the
growing season of crops or the like ? 
Let's say if July was interesting for you then you could run the
interpolations for July of each year and that way get a time sequences you
can look at to dervive your conclusions from....
Karsten Vennemann

2119 Boyer Ave E 
Seattle, WA  98112
 <http://www.terragis.net/> www.terragis.net

Phone ++1 206 905 1711
Fax      ++1 925 905 1711


From: Qgis-us-user [mailto:qgis-us-user-bounces at lists.osgeo.org] On Behalf
Of Dani Varghese
Sent: Thursday, September 03, 2020 03:14
To: qgis-us-user at lists.osgeo.org
Subject: [Qgis-us-user] Standard precipitation index interpolation

Dear All 

I  had SPI (Standard precipitation index) values for 1000 stations (30 years
monthly data for each station) . I needed to perform the interpolation
method ( kriging). What confuses me is that each station/point has 30 years
of monthly data ranging from +2 to -2, Can anyone suggest to me how to
interpolate these values, thanks  in advance.


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