Hydrological Change – Climate Change Impact Simulations for Sweden

Andreasson, Johan; Bergström, Sten; Carlsson, Bengt; Graham, L. Phil; Lindström, Göran

doi:10.1639/0044-7447(2004)033[0228:hcccis]2.0.co;2

Cited by 91 publications

(139 citation statements)

References 32 publications

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“…Evapotranspiration was therefore modified in the future climate hydrological simulations so that the annual percent change matched the RCM simulations. More detail on delta procedures is found in Andréasson et al (2004).…”

Section: Hbv Applicationmentioning

confidence: 99%

On interpreting hydrological change from regional climate models

et al. 2007

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Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling.

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Section: Hbv Applicationmentioning

confidence: 99%

On interpreting hydrological change from regional climate models

et al. 2007

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“…Therefore the meteorological data of near surface temperature and precipitation for the future climate were corrected with a method similar to the "delta change approach" (e.g. Andréasson et al 2004) so that they could be used directly by the LPJ-GUESS model. For temperature the climatological annual cycle for the time-slice 1979-2000 of the CCC run and the baseline run were calculated.…”

Section: Model Descriptionmentioning

confidence: 99%

“…This was done to avoid spurious high values in the future. The advantage of this method is that the changes in extremes and the variability are conserved compared to the method of Andréasson et al (2004), but the disadvantage of this procedure is the same change factors for different temperature values. The correction of temperature and precipitation also influence the snow pack.…”

Section: Model Descriptionmentioning

confidence: 99%

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

et al. 2007

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In the context of the EU-Project BALANCE (http://balance-eu.info) the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect.

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“…Therefore, changes in water resources and the underlying driving forces due to climate changes have become research focuses (Andréasson et al, 2004;Christensen and Lettenmaier, 2007;Frederick and Major, 1997;Gül et al, 2010;Lins and Slack, 1999;Liu and Cui, 2009;Null et al, 2010;Piao et al, 2007;Thodsen, 2007;Vörösmarty et al, 2000;Xu et al, 2010;Zhang et al, 2001). Andréasson et al (2004) discussed the impacts of climate change on streamflow under three anthropogenic CO 2 emission scenarios with a hydrology model (HBV) and concluded that the influences of climate change based on hydrology cycle varied geographically. Lins and Slack (1999) applied the nonparametric Mann-Kendall test to study temporal trends of streamflow at 395 gauging stations across the USA and suggested that streamflow increased in most regions, except for the northwest and the southeast Pacific.…”

Section: S L Sun Et Al: Past and Future Changes Of Streamflow In Pmentioning

confidence: 99%

Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

Sun

Chen

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract.To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan) within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961-2000. The increases in streamflow by 4.80 m 3 s −1 yr −1 and 1.29 m 3 s −1 yr −1 at Meigang and Gaosha, respectively, are statistically significant at the 5 % level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m 3 s −1 yr −1 ), Gaosha (1.12 m 3 s −1 yr −1 ), and Xiashan (1.34 m 3 s −1 yr −1 ), while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m 3 s −1 yr −1 ). In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds.For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3) under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1) for the period of 2061-2100. When the future changes in the soil water storage changes are assumed ignorable, the streamflow shows an uptrend with the projected increases in both precipitation and evapotranspiration (except for the SRESB1 scenario in Xiashan watershed) relative to the observed mean during 1961-2000. Furthermore, the largest increase in the streamflow is found at Meigang (+4.31 %) and Xiashan (+3.84 %) under the SRESA1B scenario, while the increases will occur at Saitang (+6.87 %) and Gaosha (+5.15 %) under the SRESB1 scenario.

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Hydrological Change – Climate Change Impact Simulations for Sweden

Cited by 91 publications

References 32 publications

On interpreting hydrological change from regional climate models

On interpreting hydrological change from regional climate models

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

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