Publication Details |
| Category | Text Publication |
| Reference Category | Conference papers |
| DOI | 10.5194/piahs-385-65-2024 |
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| Title (Primary) | Regional multi-objective calibration for distributed hydrological modelling: a decision tree based approach |
| Title (Secondary) | Hydrological Sciences in the Anthropocene. Vol. 2: Variability and change across space, time, extremes, and interfaces - IAHS Scientific Assembly 2022, Montpellier, 29 May-3 June 2022 |
| Author | Pesce, M.; Viglione, A.; von Hardenberg, J.; Tarasova, L.; Basso, S.; Merz, R.; Parajka, J.; Tong, R. |
| Publisher | Cudennec, C.; Grimaldi, S. |
| Source Titel | Proceedings of IAHS |
| Year | 2024 |
| Department | CATHYD |
| Volume | 385 |
| Page From | 65 |
| Page To | 69 |
| Language | englisch |
| Topic | T5 Future Landscapes T4 Coastal System |
| Keywords | UPH 19; distributed hydrological modelling; parameter regionalization |
| Abstract | Large scale modelling is becoming increasingly important in hydrology, particularly to characterize and quantify changes in the hydrological regime, whose drivers are typically large-scale phenomena, up to the global scale (e.g., climate change). This can be done with distributed models by estimating spatially consistent model parameters i.e. parameters having a functional relationship with catchment characteristics. In this study we adopt the newly developed PArameter Set Shuffling (PASS) approach, based on a machine learning decision tree algorithm, for the regional calibration of the TUWmodel over North-Western Italy. The method exploits observed patterns of locally calibrated parameters and catchment (climatic and geomorphological) descriptors, to derive functional relationships between the variables. The calibration procedure is performed by including snow cover information, as captured by MODIS datasets, in the model efficiency function. The results show that the PASS regionalization procedure allows to obtain very good regional model efficiencies, without significant loss of performance when moving from training to test catchments and from calibration to verification period, confirming the robustness of the methodology. We also highlight that using snow information in the calibration procedure is helpful to obtain spatially consistent model parameters for this study area. In the spirit of “obtaining good results for the right reasons”, this should be a preferred approach when performing the regional calibration of distributed hydrologic models over mountainous regions. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29546 |
| Pesce, M., Viglione, A., von Hardenberg, J., Tarasova, L., Basso, S., Merz, R., Parajka, J., Tong, R. (2024): Regional multi-objective calibration for distributed hydrological modelling: a decision tree based approach In: Cudennec, C., Grimaldi, S. (eds.) Hydrological Sciences in the Anthropocene. Vol. 2: Variability and change across space, time, extremes, and interfaces - IAHS Scientific Assembly 2022, Montpellier, 29 May-3 June 2022 Proceedings of IAHS 385 International Association of Hydrological Sciences (IAHS), Wallingford, Oxfordshire, 65 - 69 10.5194/piahs-385-65-2024 |
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