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  • 1.
    Ameli, Ali A.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Saskatchewan, Global Inst Water Secur, Saskatoon, SK, Canada.;Western Univ, Dept Biol, London, ON, Canada..
    Controls on subsurface transport of sorbing contaminant2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 5, p. 1226-1239Article in journal (Refereed)
    Abstract [en]

    Subsurface transport of a sorbing contaminant is poorly understood and characterized. Here, a new semi-analytical saturated-unsaturated flow and transport model is coupled to a kinetic sorption algorithm to assess the impact of changes in the subsurface permeability architecture and flow rate on sorption characteristics. The model outputs reveal the pronounced effect of the rate of vertical decline in K-s on the frequency of occurrence and spatial distribution of subsurface sorption as well as the timing and rate of sorbing contaminants discharged into stream. Sorption potential is weakened with infiltration rate. The impact of infiltration rate on the decline in sorption potential becomes more accentuated as the degree of subsurface vertical heterogeneity in saturated hydraulic conductivity increases. Porosity pattern also impacts sorption characteristics; but its effects highly depend upon the degree of vertical heterogeneity in Ks. The results and methodology presented in this paper have potential implications for assessing water quality in integrated groundwater-surface water systems as well as designing remediation systems.

  • 2. Johansson, Cecilia
    et al.
    Ingvander, Susanne
    Stockholms universitet, Institutionen för naturgeografi och kvartärgeologi (INK).
    A model for the snow water equivalent derived from stratigraphy observations in northern Sweden2015In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 46, no 6, p. 984-995Article in journal (Refereed)
    Abstract [en]

    A new parameterization of snow water equivalent (SWE) based on snow depth (HS) has been developed from observations made in northern Sweden. When applying previous SWE parameterization from the Alps on observations from northern Sweden, the SWE values are systematically 20% lower. The new SWE parameterization is derived from a snow layer density regression model using snow layer hardness and snow particle size. The model was evaluated with a detailed field reference dataset, and then applied to the long-term Abisko Scientific Research Station stratigraphic snowpack dataset The model enables a regional adjustment of snow layer density values for northern Swedish conditions. The snow layer density model provides an accurate estimation of snow bulk density used to derive the SWE parameterization based solely on HS. Snow depth observations are made on a daily basis; by applying our new parameterization, daily values of SWE can be obtained for northern Scandinavian conditions, which can be used, for example, for hydropower production planning and risk assessments.

  • 3.
    Lam, Norris
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Kean, Jason W.
    Lyon, Steve W.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 4, p. 981-996Article in journal (Refereed)
    Abstract [en]

    The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.

  • 4.
    Okoli, Kenechukwu
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences. Uppsala University.
    A systematic comparison of statistical and hydrological methods for design flood estimation2019In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955Article in journal (Refereed)
    Abstract [en]

    We compare statistical and hydrological methods to estimate design floods by proposing a framework based on virtual reality. To illustrate the framework, we used probability model selection and model averaging as statistical methods, while continuous simulations made with a simple or a perfect rainfall-runoff model are used as hydrological methods. The results of our numerical exercise show that design floods estimated by using a simple rainfall-runoff model have small parameter uncertainty and limited errors, even for high return periods. Statistical methods perform better than the linear reservoir model in terms of median errors for high return periods, but their uncertainty (i.e. variance of the error) is larger. Moreover, selecting the best fitting probability distribution is associated with numerous outliers. On the contrary, using multiple probability distributions, regardless of their capability in fitting the data, leads to significantly less outliers, while keeping a similar accuracy. Thus, we find that, among the statistical methods, model averaging is a better option than model selection. Our results also show the relevance of the precautionary principle in design flood estimation, and thus help develop general recommendations for practitioners and experts involved in flood risk reduction.

  • 5.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    McIntyre, N.
    Wheater, H. S.
    The significance of spatial variability of rainfall on simulated runoff: an evaluation based on the Upper Lee catchment, UK2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 4, p. 1118-1130Article in journal (Refereed)
  • 6. Raty, Olle
    et al.
    Virta, Hanna
    Bosshard, Thomas
    SMHI, Research Department, Hydrology.
    Donnelly, Chantal
    SMHI, Research Department, Hydrology.
    Regional climate model and model output statistics method uncertainties and the effect of temperature and precipitation on future river discharges in Scandinavia2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 5, p. 1363-1377Article in journal (Refereed)
  • 7.
    Wang, L.
    et al.
    Univ Zurich, Dept Geog, Winterthurerstr 190, CH-8057 Zurich, Switzerland..
    van Meerveld, H. J.
    Univ Zurich, Dept Geog, Winterthurerstr 190, CH-8057 Zurich, Switzerland..
    Seibert, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Zurich, Dept Geog, Zurich, Switzerland..
    When should stream water be sampled to be most informative for event-based, multi-criteria model calibration?2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 6, p. 1566-1584Article in journal (Refereed)
    Abstract [en]

    Isotope data from streamflow samples taken during rainfall or snowmelt events can be useful for model calibration, particularly to improve model consistency and to reduce parameter uncertainty. To reduce the costs associated with stream water sampling, it is important to choose sampling times with a high information content. We used the Birkenes model and synthetic rainfall, streamflow and isotope data to explore how many samples are needed to obtain a certain model fit and which sampling times are most informative for model calibration. Our results for nine model parameterizations and three events, representing different streamflow behaviours (e.g., fast and slow response, with and without overflow), show that the simulation performance of models calibrated with isotope data from two selected samples was comparable to simulations based on isotope data for all 100 time steps. Generally, samples taken on the falling limb were most informative for model calibration, although the exact timing of the most informative samples was dependent on the runoff response. Samples taken on the rising limb and at peakflow were less informative than expected. These model results highlight the value of a limited number of stream water samples and provide guidance for cost-effective event-based sampling strategies for model calibration.

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