Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Arheimer, Berit; Lindström, Göran

doi:10.5194/hess-19-771-2015

Cited by 130 publications

(115 citation statements)

References 47 publications

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“…Enhanced winter precipitation, which mainly falls as snow, has been reported in the late 1980s and 1990s, whereas snow depth increased until the 1980s, but has since then decreased (Lindström and Bergström, 2004;Holmlund et al, 2005;Callaghan et al, 2013). Similarly, snow duration decreased significantly over the last century (Callaghan et al, 2013;Arheimer and Lindström, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…The spring flood is approximately double the volume of the autumn flood caused by rainfall events (Arheimer and Lindström, 2015). Streamflow in northern Sweden can vary substantially at decadal scales as indicated by both the dry period in the 1970s and the wet period starting in the mid-1990s.…”

Section: Study Areamentioning

confidence: 99%

“…Teutschbein et al, 2011;Arheimer and Lindström, 2015). With the snowmelt floods showing a decreasing trend and the increasing trend in autumn floods a bi-modal flood regime is likely to develop as detected in sub-arctic catchments in Canada (Cunderlik and Ouarda, 2009).…”

Section: Changes In Flood Extremes and Shift In Flow Regimementioning

confidence: 99%

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On the variability of cold region flooding

Matti

Dahlke

Lyon

2016

Journal of Hydrology

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s u m m a r yCold region hydrological systems exhibit complex interactions with both climate and the cryosphere. Improving knowledge on that complexity is essential to determine drivers of extreme events and to predict changes under altered climate conditions. This is particularly true for cold region flooding where independent shifts in both precipitation and temperature can have significant influence on high flows. This study explores changes in the magnitude and the timing of streamflow in 18 Swedish Sub-Arctic catchments over their full record periods available and a common period . The MannKendall trend test was used to estimate changes in several hydrological signatures (e.g. annual maximum daily flow, mean summer flow, snowmelt onset). Further, trends in the flood frequency were determined by fitting an extreme value type I (Gumbel) distribution to test selected flood percentiles for stationarity using a generalized least squares regression approach.Results highlight shifts from snowmelt-dominated to rainfall-dominated flow regimes with all significant trends (at the 5% significance level) pointing toward (1) lower magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest widespread permafrost thawing and are supported by increasing trends in annual minimum daily flows. Trends in selected flood percentiles showed an increase in extreme events over the full periods of record (significant for only four catchments), while trends were variable over the common period of data among the catchments. An uncertainty analysis emphasizes that the observed trends are highly sensitive to the period of record considered. As such, no clear overall regional hydrological response pattern could be determined suggesting that catchment response to regionally consistent changes in climatic drivers is strongly influenced by their physical characteristics.

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Section: Introductionmentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

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On the variability of cold region flooding

Matti

Dahlke

Lyon

2016

Journal of Hydrology

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“…Conventionally hydrological impacts on large river basins have been studied within global or continental impact studies; however large-scale studies entail compromises in model input data and calibration at the local scale (occasionally not being possible) (Donnelly et al 2014;Arheimer and Lindström 2015). Analysing climate change impacts between different regions in individually calibrated models allows for a comparative analysis and a holistic overview of the potential impacts, and can inform on the uncertainties in previous continental/global scale studies (e.g.…”

Section: Introductionmentioning

confidence: 99%

Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions

et al. 2016

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We investigate simulated hydrological extremes (i.e., high and low flows) under the present and future climatic conditions for five river basins worldwide: the Ganges, Lena, Niger, Rhine, and Tagus. Future projections are based on five GCMs and four emission scenarios. We analyse results from the HYPE, mHM, SWIM, VIC and WaterGAP3 hydrological models calibrated and validated to simulate each river. The use of different impact models and future projections allows for an assessment of the uncertainty of future impacts. The analysis of extremes is conducted for four different time horizons: reference (1981-2010), early-century (2006-2035), mid-century (2036-2065) and end-century (2070-2099). In addition, Sen's non-parametric estimator of slope is used to calculate the magnitude of trend in extremes, whose statistical significance is assessed by the Mann-Kendall test. Overall, the impact of climate change is more severe at the end of the century and particularly in dry regions. High flows are generally sensitive to changes in precipitation, however sensitivity varies between the basins. Finally, results show that conclusions in climate change impact Center for Global Change and Water Cycle, Hohai University, Nanjing, China studies can be highly influenced by uncertainty both in the climate and impact models, whilst the sensitivity to climate modelling uncertainty becoming greater than hydrological model uncertainty in the dry regions.

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“…In the conceptualmodelling approach, synthetic runoff series are simulated from meteorological series, and are then used to calculated the runoff of chosen exceedance probability (Seibert, 1999, Arheimer andLindström, 2015). In the frequency-analysis approach, historical yearly time series of runoff are used to evaluate statistical estimators (i.e.…”

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confidence: 99%

The probabilistic hydrological model MARCS (MARkov Chain System): the theoretical basis for the core version 0.2

Shevnina

Silaev

2018

Preprint

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Abstract.A question of environmental risks of social and economic infrastructure has become apparent recently due to an increase in the number of extreme weather events. Extreme runoff events include floods and droughts. In water engineering extreme runoff is described in terms of probability, and uses methods of frequency analysis to evaluate an exceedance probability curve (EPC) of runoff. It is assumed that historical observations of runoff are representative for the future; however trends in observed time series doubt this assumption. The paper describes an Advance Frequency Analysis (AFA) approach to be applied to predict future extreme runoff. The approach combines traditional methods of hydrological modelling and frequency analysis, and results in a probabilistic hydrological model Markov Chain System (MARCS). The MARCS model simulates statistical estimators of a multi-year runoff to perform future runoff projections in probabilistic form. Projected statistics of meteorological variables available in climate scenarios force the MARCS model. This study introduces a new model core (version 0.2), and provides an user guide as well as an example of the model set up for a single case study. In this case study, the model simulates projected exceedance probability curves of annual runoff under three climate scenarios. The scope of applicability and limitations of the model are discussed.

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Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Cited by 130 publications

References 47 publications

On the variability of cold region flooding

On the variability of cold region flooding

Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions

The probabilistic hydrological model MARCS (MARkov Chain System): the theoretical basis for the core version 0.2

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