Performance    of    ensemble    streamflow    forecasts    under    varied    
hydrometeorological conditions

Benninga, Harm-Jan F.; Booij, Martijn J.; Romanowicz, Renata J.; Rientjes, Tom H. M.

doi:10.5194/hess-2016-584

Cited by 2 publications

(2 citation statements)

References 52 publications

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“…The parameter ranges were chosen following the results of deterministic optimization performed earlier and reported by and they include the derived optimal values. The range of parameter variability was chosen following the HBV model sensitivity studies reported by and Benninga (2015). It should be noted that the WHC parameter related to refreezing is very small, indicating that no refreezing process is accounted for.…”

Section: Design Of Numerical Experimentsmentioning

confidence: 99%

The critical role of uncertainty in projections of hydrological extremes

Meresa¹,

Romanowicz²

2017

Hydrol. Earth Syst. Sci.

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Abstract. This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high-and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

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Section: Design Of Numerical Experimentsmentioning

confidence: 99%

The critical role of uncertainty in projections of hydrological extremes

Meresa¹,

Romanowicz²

2017

Hydrol. Earth Syst. Sci.

Self Cite

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“…Other potential reasons are the differences in source stations used for interpolation and gauge under-catch correction methods, although a detailed investigation is outside the scope of this study. On the other hand, Benninga et al (2016) estimated the influence of elevation on precipitation in the Biała catchment as only 3.7%.…”

Section: Hydrological Modelsmentioning

confidence: 96%

What can we learn from the projections of changes of flow patterns? Results from Polish case studies

et al. 2017

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River flow projections for two future time horizons and RCP 8.5 scenario, generated by two projects (CHASE-PL and CHIHE) in the Polish-Norwegian Research Programme, were compared. The projects employed different hydrological models over different spatial domains. The semi-distributed, process-based, SWAT model was used in the CHASE-PL project for the entire Vistula and Odra basins area, whilst the lumped, conceptual, HBV model was used in the CHIHE project for eight Polish catchments, for which the comparison study was made. Climate projections in both studies originated from the common EURO-CORDEX dataset, but they were different, e.g. due to different bias correction approaches. Increases in mean annual and seasonal flows were projected in both studies, yet the magnitudes of changes were largely different, in particular for the lowland catchments in the far future. The HBV-based increases were significantly higher in the latter case than the SWAT-based increases in all seasons except winter. Uncertainty in projections is high and creates a problem for practitioners.

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Performance of ensemble streamflow forecasts under varied hydrometeorological conditions

Cited by 2 publications

References 52 publications

The critical role of uncertainty in projections of hydrological extremes

The critical role of uncertainty in projections of hydrological extremes

What can we learn from the projections of changes of flow patterns? Results from Polish case studies

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