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  • 1.
    Brunner, Manuela Irene
    et al.
    Univ Zurich, Dept Geog, Zurich, Switzerland.;Univ Grenoble Alpes, IGE, Grenoble INP, Grenoble, France..
    Sikorska, Anna E.
    Univ Zurich, Dept Geog, Zurich, Switzerland.;Warsaw Univ Life Sci SGGW, Dept Hydraul Engn, Warsaw, Poland..
    Seibert, J.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Zurich, Dept Geog, Zurich, Switzerland.
    Bivariate analysis of floods in climate impact assessments2018In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 616-617, p. 1392-1403Article in journal (Refereed)
    Abstract [en]

    Climate impact studies regarding floods usually focus on peak discharges and a bivariate assessment of peak discharges and hydrograph volumes is not commonly included. A joint consideration of peak discharges and hydrograph volumes, however, is crucial when assessing flood risks for current and future climate conditions. Here, we present a methodology to develop synthetic design hydrographs for future climate conditions that jointly consider peak discharges and hydrograph volumes. First, change factors are derived based on a regional climate model and are applied to observed precipitation and temperature time series. Second, the modified time series are fed into a calibrated hydrological model to simulate runoff time series for future conditions. Third, these time series are used to construct synthetic design hydrographs. The bivariate flood frequency analysis used in the construction of synthetic design hydrographs takes into account the dependence between peak discharges and hydrograph volumes, and represents the shape of the hydrograph. The latter is modeled using a probability density function while the dependence between the design variables peak discharge and hydrograph volume is modeled using a copula. We applied this approach to a set of eight mountainous catchments in Switzerland to construct catchment-specific and season-specific design hydrographs for a control and three scenario climates. Our work demonstrates that projected climate changes have an impact not only on peak discharges but also on hydrograph volumes and on hydrograph shapes both at an annual and at a seasonal scale. These changes are not necessarily proportional which implies that climate impact assessments on future floods should consider more flood characteristics than just flood peaks.

  • 2. Kiang, Julie E.
    et al.
    Gazoorian, Chris
    McMillan, Hilary
    Coxon, Gemma
    Le Coz, Jérôme
    Westerberg, Ida K.
    Belleville, Arnaud
    Sevrez, Damien
    Sikorska, Anna E.
    Petersen-Øverleir, Asgeir
    Reitan, Trond
    Freer, Jim
    Renard, Benjamin
    Mansanarez, Valentin
    Stockholm University, Faculty of Science, Department of Physical Geography. Hydrology-Hydraulics, IRSTEA, France.
    Mason, Robert
    A Comparison of Methods for Streamflow Uncertainty Estimation2018In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 54, no 10, p. 7149-7176Article in journal (Refereed)
    Abstract [en]

    Streamflow time series are commonly derived from stage-discharge rating curves, but the uncertainty of the rating curve and resulting streamflow series are poorly understood. While different methods to quantify uncertainty in the stage-discharge relationship exist, there is limited understanding of how uncertainty estimates differ between methods due to different assumptions and methodological choices. We compared uncertainty estimates and stage-discharge rating curves from seven methods at three river locations of varying hydraulic complexity. Comparison of the estimated uncertainties revealed a wide range of estimates, particularly for high and low flows. At the simplest site on the Is&e River (France), full width 95% uncertainties for the different methods ranged from 3 to 17% for median flows. In contrast, uncertainties were much higher and ranged from 41 to 200% for high flows in an extrapolated section of the rating curve at the Mahurangi River (New Zealand) and 28 to 101% for low flows at the Taf River (United Kingdom), where the hydraulic control is unstable at low flows. Differences between methods result from differences in the sources of uncertainty considered, differences in the handling of the time-varying nature of rating curves, differences in the extent of hydraulic knowledge assumed, and differences in assumptions when extrapolating rating curves above or below the observed gaugings. Ultimately, the selection of an uncertainty method requires a match between user requirements and the assumptions made by the uncertainty method. Given the significant differences in uncertainty estimates between methods, we suggest that a clear statement of uncertainty assumptions be presented alongside streamflow uncertainty estimates. Plain Language Summary Knowledge of the uncertainty in streamflow discharge measured at gauging stations is important for water management applications and scientific analysis. This paper shows that uncertainty estimates vary widely (typically up to a factor of 4) when comparing seven recently introduced estimation methods. A clear understanding of the assumptions underpinning different uncertainty estimation methods and the sources of uncertainty included in their calculations is needed when selecting a method and using and presenting its uncertainty estimates.

  • 3.
    Sikorska, Anna E.
    et al.
    Univ Zurich, Dept Geog, Zurich, Switzerland.;Warsaw Univ Life Sci SGGW, Dept Hydraul Engn, Warsaw, Poland..
    Seibert, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Zurich, Dept Geog, Zurich, Switzerland.
    Appropriate temporal resolution of precipitation data for discharge modelling in pre-alpine catchments2018In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 63, no 1, p. 1-16Article in journal (Refereed)
    Abstract [en]

    Precipitation time series with high temporal resolution are desired for hydrological modelling and flood studies. Yet the choice of an appropriate resolution is not straightforward because the use of too high a temporal resolution increases the data requirements, computational costs and, presumably, associated uncertainty, while performance improvement may be indiscernible. In this study, the effect of averaging hourly precipitation on model performance and associated uncertainty is investigated using two data sources: station network precipitation (SNP) and radar-based precipitation (RBP). From these datasets, time series of different temporal resolutions were generated, and runoff was simulated for 13 pre-alpine catchments with a bucket-type model. Our results revealed that different temporal resolutions were required for an acceptable model performance depending on the catchment size and data source. These were 1-12h for small (16-59km(2)), 3-21h for medium (60-200km(2)), and 24h for large (200-939km(2)) catchments.

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