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https://doi.org/10.5194/hess-2020-6
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-6
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Jan 2020
| 28 Jan 2020
Status: this preprint has been withdrawn by the authors.
The HOOPLA toolbox: a HydrOlOgical Prediction LAboratory to explore ensemble rainfall-runoff modeling
Abstract. This technical report introduces the HydrOlOgical Prediction LAboratory (HOOPLA) developed at Université Lavalfor ensemble lumped hydrological modelling. HOOPLA includes functionalities to perform calibration, simulation, and forecast for multiple hydrological models and various time steps. It includes a range of hydrometeorological tools such as calibration algorithms, data assimilation techniques, potential evapotranspiration formulas and a snow accounting routine. HOOPLA is a flexible framework coded in MATLAB that allows easy integration of user-defined hydrometeorological tools. This report also illustrates HOOPLA's functionalities using a set of 31 Canadian catchments.
This preprint has been withdrawn.
How to cite. Thiboult, A., Seiller, G., Poncelet, C., and Anctil, F.: The HOOPLA toolbox: a HydrOlOgical Prediction LAboratory to explore ensemble rainfall-runoff modeling, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-6, 2020.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
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RC1: 'Review of “The HOOPLA toolbox: a HydrOlOgical Prediction LAboratory to explore ensemble rainfall-runoff modeling” by Thiboult et al., 2020', Shervan Gharari, 08 Mar 2020
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AC1: 'Response to Shervan Gharari', Antoine Thiboult, 17 Apr 2020
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AC1: 'Response to Shervan Gharari', Antoine Thiboult, 17 Apr 2020
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RC2: 'Review', Anonymous Referee #2, 16 Mar 2020
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AC2: 'Response to referee #2', Antoine Thiboult, 17 Apr 2020
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AC2: 'Response to referee #2', Antoine Thiboult, 17 Apr 2020
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
-
RC1: 'Review of “The HOOPLA toolbox: a HydrOlOgical Prediction LAboratory to explore ensemble rainfall-runoff modeling” by Thiboult et al., 2020', Shervan Gharari, 08 Mar 2020
-
AC1: 'Response to Shervan Gharari', Antoine Thiboult, 17 Apr 2020
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AC1: 'Response to Shervan Gharari', Antoine Thiboult, 17 Apr 2020
-
RC2: 'Review', Anonymous Referee #2, 16 Mar 2020
-
AC2: 'Response to referee #2', Antoine Thiboult, 17 Apr 2020
-
AC2: 'Response to referee #2', Antoine Thiboult, 17 Apr 2020
Model code and software
HOOPLA A. Thiboult, G. Seiller, and F. Anctil https://doi.org/10.5281/zenodo.2653969
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Cited
2 citations as recorded by crossref.
- Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II J. Xu et al. 10.5194/hess-26-1001-2022
- Sensitivity analysis of the hyperparameters of an ensemble Kalman filter application on a semi-distributed hydrological model for streamflow forecasting B. Sabzipour et al. 10.1016/j.jhydrol.2023.130251
Latest update: 13 Dec 2024
Antoine Thiboult
Dept. of Civil and Water Engineering, Université Laval, Québec, Canada
Gregory Seiller
DHI, Nantes, France
formerly at: Université Laval, Québec, Canada
Carine Poncelet
Crédit Agricole Sud Rhône Alpes, Grenoble, France
formerly at: Université Laval, Québec, Canada
François Anctil
Dept. of Civil and Water Engineering, Université Laval, Québec, Canada
Short summary
HOOPLA, the HydrOlOgical Prediction LAboratory, is a toolbox that converts precipitation into river runoff. It relies on numerical models to compute snow accumulation and melting, water loss to the atmosphere, and the main on-land water cycle processes. HOOPLA includes several techniques to handle forecast uncertainty. In particular, it adopts a probabilistic approach to describe the model structure, the initial condition, and the meteorological uncertainties.
HOOPLA, the HydrOlOgical Prediction LAboratory, is a toolbox that converts precipitation into...