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Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology. Uppsala Universitet, Sverige.ORCID iD: 0000-0002-3344-2468
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology. Uppsala Universitet, Sverige.
2011 (English)In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 37, no 9-10, 2087-2105 p.Article in journal (Refereed) Published
Abstract [en]

Hydrological modeling for climate-change impact assessment implies using meteorological variables simulated by global climate models (GCMs). Due to mismatching scales, coarse-resolution GCM output cannot be used directly for hydrological impact studies but rather needs to be downscaled. In this study, we investigated the variability of seasonal streamflow and flood-peak projections caused by the use of three statistical approaches to downscale precipitation from two GCMs for a meso-scale catchment in southeastern Sweden: (1) an analog method (AM), (2) a multi-objective fuzzy-rule-based classification (MOFRBC) and (3) the Statistical DownScaling Model (SDSM). The obtained higher-resolution precipitation values were then used to simulate daily streamflow for a control period (1961-1990) and for two future emission scenarios (2071-2100) with the precipitation-streamflow model HBV. The choice of downscaled precipitation time series had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approaches to reproduce observed precipitation. Although SDSM was considered to be most suitable for downscaling precipitation in the studied river basin, we highlighted the importance of an ensemble approach. The climate and streamflow change signals indicated that the current flow regime with a snowmelt-driven spring flood in April will likely change to a flow regime that is rather dominated by large winter streamflows. Spring flood events are expected to decrease considerably and occur earlier, whereas autumn flood peaks are projected to increase slightly. The simulations demonstrated that projections of future streamflow regimes are highly variable and can even partly point towards different directions.

Place, publisher, year, edition, pages
2011. Vol. 37, no 9-10, 2087-2105 p.
Keyword [en]
gcm, statistical downscaling, hydrological impact modeling, precipitation, temperature, streamflow, hbv, climate change, sweden, atmospheric circulation patterns, change scenarios, central sweden, daily precipitation, analog method, runoff model, gcm output, uncertainty, predictions, calibration
National Category
Oceanography, Hydrology, Water Resources Climate Research
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-67695DOI: 10.1007/s00382-010-0979-8ISI: 000296476600023OAI: oai:DiVA.org:su-67695DiVA: diva2:470869
Funder
Formas, 2007-1433
Note

840XY Times Cited:1 Cited References Count:61

Available from: 2011-12-30 Created: 2011-12-30 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Hydrological Modeling for Climate Change Impact Assessment: Transferring Large-Scale Information from Global Climate Models to the Catchment Scale
Open this publication in new window or tab >>Hydrological Modeling for Climate Change Impact Assessment: Transferring Large-Scale Information from Global Climate Models to the Catchment Scale
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A changing climate can severely perturb regional hydrology and thereby affect human societies and life in general. To assess and simulate such potential hydrological climate change impacts, hydrological models require reliable meteorological variables for current and future climate conditions. Global climate models (GCMs) provide such information, but their spatial scale is too coarse for regional impact studies. Thus, GCM output needs to be downscaled to a finer scale either through statistical downscaling or through dynamic regional climate models (RCMs). However, even downscaled meteorological variables are often considerably biased and therefore not directly suitable for hydrological impact modeling. This doctoral thesis discusses biases and other challenges related to incorporating climate model output into hydrological studies and evaluates possible strategies to address them. An analysis of possible sources of uncertainty stressed the need for full ensembles approaches, which should become standard practice to obtain robust and meaningful hydrological projections under changing climate conditions. Furthermore, it was shown that substantial biases in current RCM simulations exist and that correcting them is an essential prerequisite for any subsequent impact simulation. Bias correction algorithms considerably improved RCM output and subsequent streamflow simulations under current conditions. In addition, differential split-sample testing was highlighted as a powerful tool for evaluating the transferability of bias correction algorithms to changed conditions. Finally, meaningful projections of future streamflow regimes could be realized by combining a full ensemble approach with bias correction of RCM output: Current flow regimes in Sweden with a snowmelt-driven spring flood in April will likely change to rather damped flow regimes that are dominated by large winter streamflows.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography and Quaternary Geology, Stockholm University, 2013. 44 p.
Series
Dissertations from the Department of Physical Geography and Quaternary Geology, ISSN 1653-7211 ; 34
Keyword
Bias Correction, Climate Change, Climate Models, Ensembles, GCM, HBV, Hydrological Modeling, Precipitation, RCM, Split Sample Test, Streamflow, Sweden, Temperature, Uncertainty
National Category
Oceanography, Hydrology, Water Resources Climate Research
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-84197 (URN)978-91-7447-622-4 (ISBN)
Public defence
2013-02-15, Nordenskiöldsalen, Geovetenskapens hus, Svante Arrhenius väg 12, Stockholm, 13:00 (English)
Opponent
Supervisors
Funder
Formas, 2007-1433
Available from: 2013-01-24 Created: 2012-12-18 Last updated: 2014-01-31Bibliographically approved

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