[Qgis-us-user] Standard precipitation index interpolation

karsten karsten at terragis.net
Sat Sep 5 13:15:55 PDT 2020

Hi Dani,
>>>  like you said, if i focus on the month of july ( for example)  can i
take the average SPI values for  all the 30 years to denote/represent a
I assume you meant using the July value for each of the 30 years i.e.
averaging 30 values for each individual point.
You could do that but it would average out many differences over the
timeline of 30 years - which likely (with assumed climate change) would show
smaller differences among location points as a result. That still might work
- depending what you are trying to do ...
But you could also average always a decade of data for each point to get 3
SPI averaged values and determine if that gives you any different results
than the first approach. 
Also you need to consider that the SPI already is a summarized value which
shows deviations itself for a long term precipitation series.... So overall
you might be better off to calculate the standard precipitation index
yourself from a given time series of precipitation values. That way you can
calculate for your preferred time period and get only one value , instead of
averaging out already averaged statistical values.... 
You can also take a look at these RASTER data source
/www.chc.ucsb.edu/data/chirps <https://www.chc.ucsb.edu/data/chirps> 
I used those for areas in Africa to determine dry vs. wet years (calculated
in R)


On Thu, Sep 3, 2020 at 9:26 PM karsten <karsten at terragis.net> wrote:

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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