Discrete wavelet transform coupled with the active subspace method


Authors:
Owners:
Resource type: Model Program Resource
Storage: The size of this resource is 11.8 MB
Created: Aug 05, 2020 at 5:12 a.m.
Last updated: Jun 21, 2021 at 6:40 a.m.
DOI: 10.4211/hs.4901a0d654334c259f4ff9b49dc0a74e
Citation: See how to cite this resource
Sharing Status: Published
Views: 264
Downloads: 130
+1 Votes: Be the first one to 
 this.
Comments: No comments (yet)

Abstract

The provided Python code represents the coupled framework between the discrete wavelet transform and the active subspace method. It has the goal to perform temporal scale dependent model parameter sensitivity analysis. In the provided case, the methodology is coupled to an R code containing the LuKARS model.

The folder named 'as_dwt' contains the entire source code of the methodology as well as the required data
of the Kerschbaum spring case study.

The subfolder uq_tools contains supplementary python scripts that can be used for analyses that go beyond
the methodology proposed in the WRR article.

The subfolder examples contains a folder called 'as_wavelets', in which the relevant python scripts are stored.

The data and the LuKARS model (R. file) can be found from this directory in 'scens/scen_main'.

The LuKARS model is given by the file 'main_exe.R.'

The precipitation and discharge data is stored in 'kerschbaum.txt'.

The monthly mean temperatures (needed for Thornthwaite's ET method) are stored in 'monthly_mean_temp.csv'.

The daily temperature values and snow depths are stored in 'snow_waidhofen.csv'.

Subject Keywords

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Longitude
14.7661°
Latitude
47.9208°

Content

Resource Specific

Software
Programming Language Python
Operating System Windows

References

Sources

Derived From: Teixeira Parente, M., Bittner, D., Mattis, S. A., Chiogna, G., & Wohlmuth, B. (2019). Bayesian calibration and sensitivity analysis for a karst aquifer model using active subspaces. Water Resources Research, 55(8), 7086-7107.

How to Cite

Bittner, D., M. Engel, B. Wohlmuth, D. Labat, G. Chiogna (2020). Discrete wavelet transform coupled with the active subspace method, HydroShare, https://doi.org/10.4211/hs.4901a0d654334c259f4ff9b49dc0a74e

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

Comments

There are currently no comments

New Comment

required