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| one publication added to basket [350584] | |
| Effect of climate change on the hydrological regime of navigable water courses in Belgium: sub report 9. The WetSpa model for the iFramework Salvadore, E.; Nossent, J.; Pereira, F.; Mostaert, F. (2021). Effect of climate change on the hydrological regime of navigable water courses in Belgium: sub report 9. The WetSpa model for the iFramework. Version 1.0. FHR reports, 00_130_9. Flanders Hydraulics Research: Antwerp. VII, 17 + 9 app. pp. https://dx.doi.org/10.48607/90
Deel van: FHR reports. Flanders Hydraulics Research: Antwerp, meer
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| Beschikbaar in | Auteurs |
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| Documenttype: Projectrapport | |
| Trefwoorden |
Numerical modelling Water management > Hydrology België [Marine Regions] |
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| Abstract |
The WetSpa model (Water and energy transfer between Soil plant and atmosphere) is a well established GIS-based, spatially-distributed rainfall-runoff model for hydrological simulations at the catchment scale. Recently a process-based Python version of the model has been developed (Salvadore, E. et al., 2012, 2014), this new version is based on a different Python framework (Schmitz, et al. 2013a, 2013b) but facilitates the integration with the iFramework. To perform the integration, we carried out an in-depth comparison of the two framework paradigms to identify the appropriate strategy to bridge the gaps between the two frameworks. Afterwards, we developed new Python codes for the WetSpa model in the iFramework and we modified some parts of the iFramework to allow the integration of the WetSpa model in the toolbox. In this phase, we decided to develop two versions of the WetSpa model: a spatially-distributed and a lumped version. Distributed and lumped WetSpa models share the same Python codes, the main difference is the flow routing approach. Finally, these two versions were verified by means of a theoretical and a real case study. We compared the results generated by the two model versions with the original WetSpa-Python model. In both validation tests, the spatially-distributed model produced nearly identical results to the original model, with only negligible rounding errors. In the lumped model, all the inputs and parameters were averaged over the all catchment. The validation of the lumped model is less straightforward as model parameters partially lose their physical meaning and cannot be directly compared with the distributed ones. However, by modifying a number of parameters we were able to achieve a good match between the lumped model and the original spatially-distributed model, which ensure the correct implementation of the model code. Further tests on the lumped model are however required for a better understanding of the behavior of the model parameters. |
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