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  • 1.
    Andersson, Jafet
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Ali, Abdou
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Minoungou, Bernard
    Providing peak river flow statistics and forecasting in the Niger River basin2017Inngår i: Physics and Chemistry of the Earth, ISSN 1474-7065, E-ISSN 1873-5193, Vol. 100, s. 3-12Artikkel i tidsskrift (Fagfellevurdert)
  • 2.
    Andersson, Jafet
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Traore, Farid
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Ali, Abdou
    Process refinements improve a hydrological model concept applied to the Niger River basin2017Inngår i: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 31, nr 25, s. 4540-4554Artikkel i tidsskrift (Fagfellevurdert)
  • 3.
    Andersson, Jafet
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Pechlivanidis, Ilias
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Donnelly, Chantal
    SMHI, Forskningsavdelningen, Hydrologi.
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Key factors for improving large-scale hydrological model performance2015Inngår i: European Water, ISSN 1792-085X, Vol. 49, s. 77-88Artikkel i tidsskrift (Fagfellevurdert)
  • 4.
    Berg, Peter
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Donnelly, Chantal
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Near-real-time adjusted reanalysis forcing data for hydrology2018Inngår i: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 22, nr 2, s. 989-1000Artikkel i tidsskrift (Fagfellevurdert)
  • 5. Gelfan, Alexander
    et al.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Motovilov, Yury
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Kalugin,, Andrey
    Krylenko,, Inna
    Lavrenov, Alexander
    Climate change impact on the water regime of two great Arctic rivers: modeling and uncertainty issues2016Inngår i: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, s. 1-17Artikkel i tidsskrift (Fagfellevurdert)
  • 6. Helmert, Juergen
    et al.
    Lange, Martin
    Dong, Jiarui
    De Rosnay, Patricia
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Churulin, Evgeniy
    Kurzeneva, Ekaterina
    Mueller, Richard
    Trentmann, Joerg
    Souverijns, Niels
    Koch, Roland
    Boehm, Uwe
    Bartik, Martin
    Osuch, Marzena
    Rozinkina, Inna
    Bettems, Jean-Marie
    Samuelsson, Patrick
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Marcucci, Francesca
    Milelli, Massimo
    1st Snow Data Assimilation Workshop in the framework of COST HarmoSnow ESSEM 14042018Inngår i: Meteorologische Zeitschrift, ISSN 0941-2948, E-ISSN 1610-1227, Vol. 27, nr 4, s. 325-333Artikkel i tidsskrift (Fagfellevurdert)
  • 7. Juston, John
    et al.
    Jansson, Per-Erik
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Rating curve uncertainty and change detection in discharge time series: case study with 44-year historic data from the Nyangores River, Kenya2014Inngår i: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 28, nr 4, s. 2509-2523Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The intersection of the developing topic of rating curve and discharge series uncertainty with the topic of hydrological change detection (e.g., in response to land cover or climatic change) has not yet been well studied. The work herein explores this intersection, with consideration of a long-term discharge response (1964-2007) for a similar to 650-km(2) headwater basin of the Mara River in west Kenya, starting with stream rating and daily gauge height data. A rating model was calibrated using Bayesian methods to quantify uncertainty intervals in model parameters and predictions. There was an unknown balance of random and systemic error in rating data scatter (a scenario not likely unique to this basin), which led to an unknown balance of noise and information in the calibrated statistical error model. This had implications on testing for hydrological change. Overall, indications were that shifts in basin's discharge response were rather subtle over the 44-year period. A null hypothesis for change using flow duration curves (FDCs) from four different 8-year data intervals could be either accepted or rejected over much of the net flow domain depending on different applications of the statistical error model (each with precedence in the literature). The only unambiguous indication of change in FDC comparisons appeared to be a reduction in lowest baseflow in recent years (flows with >98% exceedance probability). We defined a subjective uncertainty interval based on an intermediate balance of random and systematic error in the rating model that suggested a possibility of more prevalent impacts. These results have relevance to management in the Mara basin and to future studies that might establish linkages to historic land use and climatic factors. The concern about uncertain uncertainty intervals (uncertainty(2)) extends beyond the Mara and is relevant to testing change where non-random rating errors may be important and subtle responses are investigated. Copyright (c) 2013 John Wiley & Sons, Ltd.

  • 8. MacDonald, Matthew K.
    et al.
    Stadnyk, Tricia A.
    Dery, Stephen J.
    Braun, Marco
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Isberg, Kristina
    SMHI, Forskningsavdelningen, Hydrologi.
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Impacts of 1.5 and 2.0 degrees C Warming on Pan-Arctic River Discharge Into the Hudson Bay Complex Through 20702018Inngår i: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 45, nr 15, s. 7561-7570Artikkel i tidsskrift (Fagfellevurdert)
  • 9. Magnusson, Jan
    et al.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Huesler, Fabia
    Jonas, Tobias
    Assimilation of point SWE data into a distributed snow cover model comparing two contrasting methods2014Inngår i: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 50, nr 10, s. 7816-7835Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In alpine and high-latitude regions, water resource decision making often requires large-scale estimates of snow amounts and melt rates. Such estimates are available through distributed snow models which in some situations can be improved by assimilation of remote sensing observations. However, in regions with frequent cloud cover, complex topography, or large snow amounts satellite observations may feature information of limited quality. In this study, we examine whether assimilation of snow water equivalent (SWE) data from ground observations can improve model simulations in a region largely lacking reliable remote sensing observations. We combine the model output with the point data using three-dimensional sequential data assimilation methods, the ensemble Kalman filter, and statistical interpolation. The filter performance was assessed by comparing the simulation results against observed SWE and snow-covered fraction. We find that a method which assimilates fluxes (snowfall and melt rates computed from SWE) showed higher model performance than a control simulation not utilizing the filter algorithms. However, an alternative approach for updating the model results using the SWE data directly did not show a significantly higher performance than the control simulation. The results show that three-dimensional data assimilation methods can be useful for transferring information from point snow observations to the distributed snow model. Key Points <list id="wrcr21142-list-0001" list-type="bulleted"> <list-item id="wrcr21142-li-0001">Evaluating methods for assimilating snow observations into distributed models <list-item id="wrcr21142-li-0002">Assimilation can improve model skill also at locations without observations <list-item id="wrcr21142-li-0003">Assimilation of fluxes appears more successful than assimilation of states <doi origin="wiley" registered="yes">10.1002/(ISSN)1944-7973</doi

  • 10. Malnes, E.
    et al.
    Buanes, A.
    Nagler, T.
    Bippus, G.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Schiller, C.
    Metsamaki, S.
    Pulliainen, J.
    Luojus, K.
    Larsen, H. E.
    Solberg, R.
    Diamandi, A.
    Wiesmann, A.
    User requirements for the snow and land ice services - CryoLand2015Inngår i: The Cryosphere, ISSN 1994-0416, E-ISSN 1994-0424, Vol. 9, nr 3, s. 1191-1202Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    CryoLand (2011-2015) is a project carried out within the 7th Framework of the European Commission aimed at developing downstream services for monitoring seasonal snow, glaciers and lake/river ice primarily based on satellite remote sensing. The services target private and public users from a wide variety of application areas, and aim to develop sustainable services after the project is completed. The project has performed a thorough user requirement survey in order to derive targeted requirements for the service and provide recommendations for the design and priorities of the service. In this paper we describe the methods used, the major findings in this user survey, and how we used the results to design and specify the CryoLand snow and land ice service. The user requirement analysis shows that a European operational snow and land ice service is required and that there exists developed cryosphere products that can meet the specific needs. The majority of the users were mainly interested not only in the snow services, but also the lake/river ice products and the glacier products were desired.

  • 11. Musselman, Keith N.
    et al.
    Molotch, Noah P.
    Margulis, Steven A.
    Lehning, Michael
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Improved snowmelt simulations with a canopy model forced with photo-derived direct beam canopy transmissivity2012Inngår i: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 48, artikkel-id W10509Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The predictive capacity of a physically based snow model to simulate point-scale, subcanopy snowmelt dynamics is evaluated in a mixed conifer forest, southern Sierra Nevada, California. Three model scenarios each providing varying levels of canopy structure detail were tested. Simulations of three water years initialized at locations of 24 ultrasonic snow depth sensors were evaluated against observations of snow water equivalent (SWE), snow disappearance date, and volumetric soil water content. When canopy model parameters canopy openness and effective leaf area index were obtained from satellite and literature-based sources, respectively, the model was unable to resolve the variable subcanopy snowmelt dynamics. When canopy parameters were obtained from hemispherical photos, the improvements were not statistically significant. However, when the model was modified to accept photo-derived time-varying direct beam canopy transmissivity, the error in the snow disappearance date was reduced by as much as one week and positive and negative biases in melt-season SWE and snow cover duration were significantly reduced. Errors in the timing of soil meltwater fluxes were reduced by 11 days on average. The optimum aggregated temporal model resolution of direct beam canopy transmissivity was determined to be 30 min; hourly averages performed no better than the bulk canopy scenarios and finer time steps did not increase overall model accuracy. The improvements illustrate the important contribution of direct shortwave radiation to subcanopy snowmelt and confirm the known nonlinear melt behavior of snow cover.

  • 12. Nijzink, R.C.
    et al.
    Almeida, S.
    Pechlivanidis, Ilias
    SMHI, Forskningsavdelningen, Hydrologi.
    Capell, Réne
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Parajka, J.
    Freer, J.
    Han, D.
    Wagener, T.
    van Nooijen, R.R.P.
    Savenije, H.H.G.
    Hrachowitz, M.
    Constraining Conceptual Hydrological ModelsWith Multiple Information Sources2018Inngår i: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 54, nr 10, s. 8332-8362Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The calibration of hydrological models without streamflow observations is problematic, and the simultaneous, combined use of remotely sensed products for this purpose has not been exhaustively tested thus far. Our hypothesis is that the combined use of products can (1) reduce the parameter search space and (2) improve the representation of internal model dynamics and hydrological signatures. Five different conceptual hydrological models were applied to 27 catchments across Europe. A parameter selection process, similar to a likelihood weighting procedure, was applied for 1,023 possible combinations of 10 different data sources, ranging from using 1 to all 10 of these products. Distances between the two empirical distributions of model performance metrics with and without using a specific product were determined to assess the added value of a specific product. In a similar way, the performance of the models to reproduce 27 hydrological signatures was evaluated relative to the unconstrained model. Significant reductions in the parameter space were obtained when combinations included Advanced Microwave Scanning Radiometer ‐ Earth Observing System and Advanced Scatterometer soil moisture, Gravity Recovery and Climate Experiment total water storage anomalies, and, in snow‐dominated catchments, the Moderate Resolution Imaging Spectroradiometer snow cover products. The evaporation products of Land Surface Analysis ‐ Satellite Application Facility and MOD16 were less effective for deriving meaningful, well‐constrained posterior parameter distributions. The hydrological signature analysis indicated that most models profited from constraining with an increasing number of data sources. Concluding, constraining models with multiple data sources simultaneously was shown to be valuable for at least four of the five hydrological models to determine model parameters in absence of streamflow.

  • 13.
    Strombäck, Lena
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Lindström, Göran
    SMHI, Forskningsavdelningen, Hydrologi.
    Donnelly, Chantal
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    The Importance of Open Data and Software for Large Scale Hydrological Modelling2013Inngår i: Open water Journal, Vol. 2, nr 1, artikkel-id 32Artikkel i tidsskrift (Fagfellevurdert)
  • 14. Vesakoski, Jenni-Mari
    et al.
    Nylen, Tua
    Arheimer, Berit
    SMHI, Forskningsavdelningen, Hydrologi.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Isberg, Kristina
    SMHI, Forskningsavdelningen, Hydrologi.
    Holopainen, Markus
    Hyyppa, Juha
    Alho, Petteri
    Arctic Mackenzie Delta channel planform evolution during 1983-2013 utilising Landsat data and hydrological time series2017Inngår i: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 31, nr 22, s. 3979-3995Artikkel i tidsskrift (Fagfellevurdert)
  • 15. Zhang, Linus
    et al.
    Gustafsson, David
    SMHI, Forskningsavdelningen, Hydrologi.
    Editorial: 'The Nordic Hydrology Model' - Linking science and practice2016Inngår i: HYDROLOGY RESEARCH, ISSN 1998-9563, Vol. 47, nr 4, s. 671-671Artikkel i tidsskrift (Fagfellevurdert)
1 - 15 of 15
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