What can we learn from comparing glacio-hydrological models?

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dc.identifier.uri http://dx.doi.org/10.15488/10620
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10698
dc.contributor.author Stoll, Elena
dc.contributor.author Hanzer, Florian
dc.contributor.author Oesterle, Felix
dc.contributor.author Nemec, Johanna
dc.contributor.author Schöber, Johannes
dc.contributor.author Huttenlau, Matthias
dc.contributor.author Förster, Kristian
dc.date.accessioned 2021-03-25T06:34:04Z
dc.date.available 2021-03-25T06:34:04Z
dc.date.issued 2020
dc.identifier.citation Stoll, E.; Hanzer, F.; Oesterle, F.; Nemec, J.; Schöber, J. et al.: What can we learn from comparing glacio-hydrological models? In: Atmosphere 11 (2020), Nr. 9, 981. DOI: https://doi.org/10.3390/atmos11090981
dc.description.abstract Glacio-hydrological models combine both glacier and catchment hydrology modeling and are used to assess the hydrological response of high-mountain glacierized catchments to climate change. To capture the uncertainties from these model combinations, it is essential to compare the outcomes of several model entities forced with the same climate projections. For the first time, we compare the results of two completely independent glacio-hydrological models: (i) HQsim-GEM and (ii) AMUNDSEN. In contrast to prevailing studies, we use distinct glacier models and glacier initialization times. At first glance, the results achieved for future glacier states and hydrological characteristics in the Rofenache catchment in ötztal Alps (Austria) appear to be similar and consistent, but a closer look reveals clear differences. What can be learned from this study is that low-complexity models can achieve higher accuracy in the calibration period. This is advantageous especially when data availability is weak, and priority is given to efficient computation time. Furthermore, the time and method of glacier initialization play an important role due to different data requirements. In essence, it is not possible to make conclusions about the model performance outside of the calibration period or more specifically in the future. Hence, similar to climate modeling, we suggest considering different modeling approaches when assessing future catchment discharge or glacier evolution. Especially when transferring the results to stakeholders, it is vital to transparently communicate the bandwidth of future states that come with all model results. © 2020 by the authors. eng
dc.language.iso eng
dc.publisher Basel : Molecular Diversity Preservation International (MDPI)
dc.relation.ispartofseries Atmosphere 11 (2020), Nr. 9
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject catchment hydrology eng
dc.subject climate change eng
dc.subject glacier retreat eng
dc.subject glacierized catchments eng
dc.subject glacio-hydrological models eng
dc.subject model comparison eng
dc.subject modeling future runoff eng
dc.subject snow and ice melt eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title What can we learn from comparing glacio-hydrological models?
dc.type Article
dc.type Text
dc.relation.essn 2073-4433
dc.relation.doi https://doi.org/10.3390/atmos11090981
dc.bibliographicCitation.issue 9
dc.bibliographicCitation.volume 11
dc.bibliographicCitation.firstPage 981
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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