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Climate change alters low flows in Europe under global warming of 1.5, 2, and 3°C

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3°C
Climate change alters low flows in Europe under global warming of 1.5, 2, and 3°C

There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90% of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from -12% under 1.5K, compared to the baseline period 1971-2000, to -35% under global warming of 3K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5K) to +45% (3K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

1027-5606
1017-1032
Marx, Andreas
a01c049b-b443-4a7d-9afe-873cfe03ee4c
Kumar, Rohini
b0ac1bbd-dfd8-4dcc-8bd5-6ffe11519b1a
Thober, Stephan
9f97d904-8cf8-4555-b836-e213013cdabb
Rakovec, Oldrich
1e14032e-8e6c-4359-975c-e5db95107d71
Wanders, Niko
5db872d0-14a1-41b7-8a15-8923fed069f3
Zink, Matthias
fe187f40-5690-40df-8c47-cce864e23e71
Wood, Eric F.
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Pan, Ming
9f6dfdc0-e281-4985-8e4d-0ce9537bd39f
Sheffield, Justin
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Samaniego, Luis
c1966ab3-ef68-4490-ba2a-0eaa85267365
Marx, Andreas
a01c049b-b443-4a7d-9afe-873cfe03ee4c
Kumar, Rohini
b0ac1bbd-dfd8-4dcc-8bd5-6ffe11519b1a
Thober, Stephan
9f97d904-8cf8-4555-b836-e213013cdabb
Rakovec, Oldrich
1e14032e-8e6c-4359-975c-e5db95107d71
Wanders, Niko
5db872d0-14a1-41b7-8a15-8923fed069f3
Zink, Matthias
fe187f40-5690-40df-8c47-cce864e23e71
Wood, Eric F.
0929fcf4-b795-4e99-9f98-371932bef995
Pan, Ming
9f6dfdc0-e281-4985-8e4d-0ce9537bd39f
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Samaniego, Luis
c1966ab3-ef68-4490-ba2a-0eaa85267365

Marx, Andreas, Kumar, Rohini, Thober, Stephan, Rakovec, Oldrich, Wanders, Niko, Zink, Matthias, Wood, Eric F., Pan, Ming, Sheffield, Justin and Samaniego, Luis (2018) Climate change alters low flows in Europe under global warming of 1.5, 2, and 3°C. Hydrology and Earth System Sciences, 22 (2), 1017-1032. (doi:10.5194/hess-22-1017-2018).

Record type: Article

Abstract

There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90% of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from -12% under 1.5K, compared to the baseline period 1971-2000, to -35% under global warming of 3K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5K) to +45% (3K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

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Accepted/In Press date: 20 December 2017
e-pub ahead of print date: 7 February 2018

Identifiers

Local EPrints ID: 418033
URI: http://eprints.soton.ac.uk/id/eprint/418033
ISSN: 1027-5606
PURE UUID: fd2d1154-79ea-4435-8fb6-438b071ff1d5
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

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Date deposited: 21 Feb 2018 17:30
Last modified: 09 Nov 2022 02:48

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Contributors

Author: Andreas Marx
Author: Rohini Kumar
Author: Stephan Thober
Author: Oldrich Rakovec
Author: Niko Wanders
Author: Matthias Zink
Author: Eric F. Wood
Author: Ming Pan
Author: Luis Samaniego

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