How evaluation of hydrological models influences results of climate impact assessment—an editorial

Valentina Krysanova (), Fred F. Hattermann and Zbigniew W. Kundzewicz
Additional contact information
Valentina Krysanova: Potsdam Institute for Climate Impact Research
Fred F. Hattermann: Potsdam Institute for Climate Impact Research
Zbigniew W. Kundzewicz: Potsdam Institute for Climate Impact Research

Climatic Change, 2020, vol. 163, issue 3, No 1, 1141 pages

Abstract: Abstract This paper introduces the Special Issue (SI) “How evaluation of hydrological models influences results of climate impact assessment.” The main objectives were as follows: (a) to test a comprehensive model calibration/validation procedure, consisting of five steps, for regional-scale hydrological models; (b) to evaluate performance of global-scale hydrological models; and (c) to reveal whether the calibration/validation methods and the model evaluation results influence climate impacts in terms of the magnitude of the change signal and the uncertainty range. Here, we shortly describe the river basins and large regions used as case studies; the hydrological models, data, and climate scenarios used in the studies; and the applied approaches for model evaluation and for analysis of projections for the future. After that, we summarize the main findings. The following general conclusions could be drawn. After successful comprehensive calibration and validation, the regional-scale models are more robust and their projections for the future differ from those of the model versions after the conventional calibration and validation. Therefore, climate impacts based on the former models are more trustworthy than those simulated by the latter models. Regarding the global-scale models, using only models with satisfactory or good performance on historical data and weighting them based on model evaluation results is a more reliable approach for impact assessment compared to the ensemble mean approach that is commonly used. The former method provides impact results with higher credibility and reduced spreads in comparison to the latter approach. The studies for this SI were performed in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10584-020-02927-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:climat:v:163:y:2020:i:3:d:10.1007_s10584-020-02927-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10584

DOI: 10.1007/s10584-020-02927-8

Access Statistics for this article

Climatic Change is currently edited by M. Oppenheimer and G. Yohe

More articles in Climatic Change from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().