Uncertainty of hydrological modelling in climate change impact studies in a Canadian, snow-dominated river basin

Poulin, Annie; Brissette, François; Leconte, Robert; Arsenault, R.J.; Malo, Jean-Stéphane

doi:10.1016/j.jhydrol.2011.08.057

Cited by 189 publications

(121 citation statements)

References 27 publications

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“…These differences may be (Wilby and Harris 2006, Chen et al 2011, Dobler et al 2012, Bastola et al 2011. Furthermore, Bastola et al (2011) and Velazquez et al (2013) found that hydrological model structure uncertainty in some cases are substantial, while Wilby and Harris (2006) and Poulin et al( 2011) found that model structure uncertainty is more important than parameter uncertainty. The novelty of the Danish studies lies in their focus on geological uncertainty and groundwater, illustrating that the dominating sources of uncertainties are context specific.…”

Section: Hydrological Impact Modellingmentioning

confidence: 99%

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

Refsgaard

Sonnenborg

Butts

et al. 2016

Hydrological Sciences Journal

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Section: Hydrological Impact Modellingmentioning

confidence: 99%

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

Refsgaard

Sonnenborg

Butts

et al. 2016

Hydrological Sciences Journal

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“…The uncertainties associated with climate change impact simulations can be grouped into the following five types based on i) natural climate variability; ii) greenhouse gas emission scenario; iii) general circulation model (GCM) structure; iv) downscaling technique; and v) impact (hydrological) model (Wilby 2005;Poulin et al 2011). In addition, the application of biascorrecting techniques adds to the uncertainty of the climate change signal ).…”

Section: Uncertainties Related To Climate Change Simulations and Hydrmentioning

confidence: 99%

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

Mehdi

Schulz

Ludwig

et al. 2017

Water Resour Manage

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The parameter uncertainty in the eco-hydrological model Soil and Water Assessment Tool (SWAT) was estimated using non-unique parameter sets for the Altmühl watershed (Bavaria, Germany). The Sequential Uncertainty Fitting Algorithm (SUFI-2) was used to calibrate SWAT. The non-unique parameter sets found were subsequently applied to SWAT concurrently with climate change simulations to determine the variables of streamflow, nitrate nitrogen (NO 3 − -N) and total phosphorus (TP). A suite of seven bias corrected climate change simulations provided reference and future climate data. The nonunique behavioural parameter sets that met an objective function of NSE >0.6 during calibration were applied to SWAT with the reference climate and with the future climate simulations. The best parameter set was also propagated through SWAT with each reference and future climate simulation in turn. Combining the non-unique behavioural parameter sets for estimating uncertainty bounds with an ensemble of climate change simulations led to a wider mean monthly spread (difference between maximum and minimum) of simulated NO 3 − -N and TP than using the best run with the future climate simulations. More monthly data was considered using the non-unique approach, resulting in statistical significances for more Water Resour Manage (2018) months of the year and overall lower interquartile ranges. The study quantifies the non-unique behavioural parameter set contributions to the modelling prediction, which assists in making more informed decisions based on available knowledge, with its limitations, of the future simulations. We outline a simple approach that can easily be replicated for similar hydrological modelling studies.

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“…magnitude of error could vary both in space and time), which could be misinformative for management decisions. An increasing interest has therefore been shown to quantify the contribution from each uncertainty source to the total uncertainty (Preston and Jones 2008;Poulin et al 2011;Teutschbein and Seibert 2012).…”

Section: Introductionmentioning

confidence: 99%

“…A clear distinction on the relative effects of hydrological model (HM) uncertainty and climate model (CM) uncertainty to the projected discharge uncertainty has not been concluded; results vary between studies depending on catchment climate and hydrological variable studied (Hagemann et al 2013;Velázquez et al 2013;Vetter et al 2015). However, the impact of HM structural uncertainty on projected discharge changes can be significant due to, for instance, the differences in the representation of evapotranspiration and snow/ice accumulation/melting processes (Poulin et al 2011;Viviroli et al 2011).…”

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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Uncertainty of hydrological modelling in climate change impact studies in a Canadian, snow-dominated river basin

Cited by 189 publications

References 27 publications

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

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

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