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These school days are dedicated to give people the taste of what OMS3 is and how to use it with Python lab. For the installation, please refer to the Installation page.
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| Tullio Pericoli, Piccoli lotti, 2013. |
The materials and the presentations of these days are available here.
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| The local (uniTrento) GEOframe crew repeated indefinitely within the screens. From left: Giuseppe , a little in front, Concetta , on the back Riccardo, then Martin and Niccolò. |
GEOframe aims to simulate the whole hydrological cycle. About evaporation and transpiration was already talked about on Day 4 However, several other aspects can be accounted for in GEOframe for obtaining a realistic representation of the hydrological cycle. The scope of this day is to progressively introduce new aspects and features.
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
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.
You can download the material for day first (January 7 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 1 (7 Jan 2021) we will focus on the geomorphological analysis of a river basin. Starting from a digital elevation model we will extract the main river basin and we will split it the hillslope-link structure appropriate for executing the GEOframe models. All the material come with the .zip file, however, for your convenience, the slides are also available separately at the link below.
For the 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
•
Various information from the
AboutHydrology Blog
•
Rigon, R., I. Rodriguez-Iturbe, A. Rinaldo, A. Maritan,
A. Giacometti and D. Tarboton, On Hack’s law, Water Resources Research, 32(11), 3367, 1996
•
R.Rigon, E. Ghesla, C. Tiso and A. Cozzini, The Horton Machine, pg. viii, 136, ISBN 10:88-8443-147-6, University of Trento, 2006
•
W. Abera, A. Antonello, S. Franceschi, G. Formetta, R
Rigon , "The uDig Spatial Toolbox for hydro-geomorphic analysis"
in Geomorphological Techniques, v. 4, n. 1 (2014), p.
1-19
Next Topic (Spatial interpolation of data)
Installation of the 2021 GEOframe environment on Linux
Credits to: Martin Morlot,
martin.morlot@unitn.it
1) Install anaconda & openjdk-8:
check https://docs.anaconda.com/anaconda/install/linux/
and https://openjdk.java.net/install/
for instuctions for your distributions
2) create GeoFrame folder and change
directory to it (in terminal):
mkdir GeoFrame
cd GeoFrame
3) Clone python4GEOframe github repository (in terminal):
git clone
git@github.com:geoframecomponents/python4GEOframe.git
4) Download, oms-console, Ex01 and notebook test using your browser:
https://alm.engr.colostate.edu/cb/wiki/16961
- unzip them inside the Geoframe folder
using your choice of file-extractor for the purpose.
5) Change directory to where you cloned
python4GEOframe, and to anaconda_envs (using previously opened terminal):
cd
python4GEOframe/Anaconda_envs
6)Activate
anaconda in linux (in a terminal):
source /opt/anaconda/bin/activate root
7) Create environment for geoframe:
conda env create -f geoframe_rossano.yaml
(will take some time)
8) activate the environmental created:
conda activate geoframe_rossano
9) set your conda java_home
export
JAVA_HOME=~/.conda/envs/geoframe_rossano/jre/
10) execute console.sh in new terminal:
cd
GeoFrame/oms-3.6.28-console
./console.sh
11) set
/home/$USERNAME/.conda/envs/geoframe_rossano/jre/ while replacing $USERNAME
with your username in the OMS console
java home setting as in the instructions slides (slide 11)
12) run ex_1 as in the instructions slides
that you can find at https://osf.io/xes9y/ (slide 12, 13) to check that it
works.
13) run the notebook excercise: open jupyter
notebook with your preferred jupyter editor (ie. Vscode, spyder) set
interpreter to conda env created python (
~/.conda/envs/geoframe_rossano/bin/python3) then run the notebook as specified
in the instructions (slide 17)
