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| Created: | Jul 22, 2020 at 11:46 a.m. | |
| Last updated: | Feb 18, 2021 at 5:36 p.m. | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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| Views: | 1181 |
| Downloads: | 383 |
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Abstract
Models that mimic an original model might have a different model structure that affects model output. This study assesses model structure differences and their impact on output by comparing 7 model implementations that carry the name HBV. We explained and quantified output differences with individual model structure components at both the numerical and mathematical level. It was found that none of the numerical and mathematical formulations of the mimicking models were (originally) the same as the benchmark, HBV-light. This led to small but distinct output differences for numerical implementations, and major output differences due to mathematical differences, although differences decreased after calibration. We argue that the lack of systematic model naming has led to a diverging concept of the HBV-model, diminishing the concept of model mimicry. Development of a systematic model naming framework, open accessible model code and more elaborate model descriptions are suggested to enhance model mimicry.
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Readme.txt
This folder contains all the scripts used in the thesis study "Model mimicry: what's in a name?" It's written by Koen Jansen and supervised by Lieke Melsen and Ryan Teuling, Wageningen University. For further question send a mail to koenatleet@hotmail.com or lieke.melsen@wur.nl. The script in the main folder are the main developments of this study and run all the models for the different parts of the study. The scripts that communicate between a model variant and the main script are: -EDU -EDU2 -Lightmodel -MAC (complemented by MAC_calibration and MAC_sample) -Marrmot -Marrmot2 -Raven -Superflex -TUWmodelk The study uses the main scripts: -running_models_v2.1.6 -parameter_limited_sampling_1.2.5 and parameter_sampling_1.2.7 -calibration_1.2 They correspond with the 2nd till 4th part of the study with the third part being split up in two scripts. The _plot is used to process the data to figures. Besides, the KGE script calculate the objective criteria Kling_Gupta efficiency. Other scripts are: -determine_spinup_1.3 to test several spinup and recession periods which is briefly discussed in the appendix in the paper. -sensitivityv1.1 was used for the parameter prioritisation in the local sensitivity study. The folders contain the original models and their input files that are adjusted by the R_scripts. All those folders have a Readme file included to reference the author and the license that comes with the model.
Related Resources
| The content of this resource is derived from | https://tuspace.ca/~rmetcalfe/MACHBV.html |
| The content of this resource is derived from | http://amir.eng.uci.edu/software.php |
| The content of this resource is derived from | http//raven.uwaterloo.ca/Downloads.html |
| The content of this resource is derived from | https://www.geo.uzh.ch/en/units/h2k/Services/HBV-Model/HBV-Download.html |
| The content of this resource is derived from | https://github.com/cran/TUWmodel/blob/master/src/hbvmodel.f |
| The content of this resource is derived from | https://github.com/dalmo1991/superflexPy/tree/master/superflexpy |
| The content of this resource is derived from | https://github.com/wknoben/MARRMoT |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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