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.
