Material for day second (January 8 2021) - Spatial interpolation and kriging

 

You can download the material for day second (January 8 2021) from this link.

 

 

After unzipping the folder you can see the typical structure of a OMS project. This is better explained in this previous blogpost. If you are reading this in advance, please take a little time to understand what OMS is and why it is like this.

 

During day 2 (8 Jan 2021) we will move to the "classical" interpolation problem: kriging algorithm will be explained and applied for interpolating measured rainfall and air temperature to each hillslope of the main river basin. All the material come with the .zip file, however, for your convenience, the slides are also available separately at the link below.

 

The theoretical part of the class in subdivided in three parts:

•    The spatial interpolation problem and the kriging algorithm: the concept 

•    The kriging algorithm: the equations 

Data Analysis with Pithon, Jupyter and Pandas

• The experimental and theoretical variogram

• The leave-one-out (LOO)

Exercises

In the OMS3 project distribute you will find:

•    data, a folder containing the model input

•    simulations, a folder containing the scripts for executing the models.

•    doc containing the pdf of the lectures

•    Jupyter containing a group of notebooks which illustrate the inputs and outputs of the simulations

What the other folders contain is explained in the OMS3 related post (see The OMS working environment).

Further information on the tools used and reference to the material of the previous Winter Schools can be found here.

 

References

•    Bancheri, M., Serafin, F., Bottazzi, M., Abera, W., Formetta, G., and Rigon, R.: The design, deployment, and testing of kriging models in GEOframe with SIK-0.9.8, Geosci. Model Dev., 11, 2189–2207, https://doi.org/10.5194/gmd-11-2189-2018, 2018

•    Kitanidis, P. K. (1997). Introduction to geostatistics: applications in hydrogeology. Cambridge university press.