Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5605-2022
© Author(s) 2022. 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-26-5605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Nov 2022
Research article |
| 09 Nov 2022
| 09 Nov 2022
Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies
Eva Sebok
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Ernesto Pastén-Zapata
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, Finland
Peter Berg
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Guillaume Thirel
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Anthony Lemoine
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Andrea Lira-Loarca
Andalusian Earth Sciences Institute, University of Granada, Granada, Spain
Christiana Photiadou
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
European Environment Agency, Copenhagen, Denmark
Rafael Pimentel
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
for Earth System Research (IISTA), University of Córdoba, Córdoba, Spain
Department of Agronomy, María de Maeztu Unit of Excellence
(DAUCO), University of Córdoba, Córdoba, Spain
Paul Royer-Gaspard
HYCAR Research Unit, Université Paris-Saclay, INRAE, Antony,
France
Erik Kjellström
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Jens Hesselbjerg Christensen
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of
Copenhagen, Copenhagen, Denmark
Bjerknes Centre for Climate
Research, NORCE Norwegian Research Centre, Bergen, Norway
Danish Meteorological Institute, Copenhagen, Denmark
Jean Philippe Vidal
RiverLy Research Unit, INRAE, Villeurbanne CEDEX, France
Philippe Lucas-Picher
Groupe de Météorologie de Grande Échelle et Climat,
Centre National de Recherches Météorologiques, Météo-France,
Toulouse, France
Département des sciences de la Terre et de l'atmosphère,
Université du Québec à Montréal, Montréal, Quebec,
Canada
Markus G. Donat
Barcelona Supercomputing Center, Barcelona, Spain
ICREA, Pg. Lluís Companys 23, Barcelona, Spain
Giovanni Besio
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
María José Polo
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
for Earth System Research (IISTA), University of Córdoba, Córdoba, Spain
Department of Agronomy, María de Maeztu Unit of Excellence
(DAUCO), University of Córdoba, Córdoba, Spain
Simon Stisen
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Yvan Caballero
BRGM, University of Montpellier, Montpellier, France
Ilias G. Pechlivanidis
Swedish Meteorological and Hydrological Institute, Norrköping,
Sweden
Lars Troldborg
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Jens Christian Refsgaard
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
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Cited
3 citations as recorded by crossref.
- On the visual detection of non-natural records in streamflow time series: challenges and impacts L. Strohmenger et al. 10.5194/hess-27-3375-2023
- Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model L. Mimeau et al. 10.5194/hess-28-851-2024
- How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
3 citations as recorded by crossref.
- On the visual detection of non-natural records in streamflow time series: challenges and impacts L. Strohmenger et al. 10.5194/hess-27-3375-2023
- Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model L. Mimeau et al. 10.5194/hess-28-851-2024
- How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
Latest update: 19 Apr 2024
Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus,...
