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  • 1. Archfield, Stacey A.
    et al.
    Clark, Martyn
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Hay, Lauren E.
    McMillan, Hilary
    Kiang, Julie E.
    Seibert, Jan
    Hakala, Kirsti
    Bock, Andrew
    Wagener, Thorsten
    Farmer, William H.
    Andreassian, Vazken
    Attinger, Sabine
    Viglione, Alberto
    Knight, Rodney
    Markstrom, Steven
    Over, Thomas
    Accelerating advances in continental domain hydrologic modeling2015In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 51, no 12, p. 10078-10091Article in journal (Refereed)
    Abstract [en]

    In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

  • 2. Dahlke, Helen E.
    et al.
    Behrens, Thorsten
    Seibert, Jan
    Andersson, Lotta
    SMHI, Core Services.
    Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques2009In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 23, no 21, p. 3017-3029Article in journal (Refereed)
    Abstract [en]

    Hydrological modelling depends highly on the accuracy and uncertainty of model input parameters such as soil properties. Since most of these data are field Surveyed, geostatistical techniques Such as kriging, classification and regression trees or more sophisticated soil-landscape models need to be applied to interpolate point information to the area. Most of the existing interpolation techniques require a random or regular distribution of points Within the study area but are not adequate to satisfactorily interpolate soil catena or transect data. The soil landscape model presented in this study is predicting soil information from transect or catena point data using a statistical mean (arithmetic, geometric and harmonic mean) to calculate the soil information based on class means of merged spatial explanatory variables. A data set of 226 soil depth measurements covering a range of 0-6.5 m was used to test the model. The point data were sampled along four transects in the Stubbetorp catchment, SE-Sweden. We overlaid a geomorphology map (8 classes) with digital elevation model-derived topographic index maps (2-9 classes) to estimate the range of error the model produces with changing sample size and input maps. The accuracy of the soil depth predictions was estimated with the root mean square error (RMSE) based oil a testing and training data set. RMSE ranged generally between 0.73 and 0.83 m +/- 0.013 m depending on the amount of classes the merged layers had, but were smallest for a map combination with a low number of classes predicted with the harmonic mean (RMSE = 0.46 m). The results show that the prediction accuracy of this method depends oil the number of point values in the sample, the value range of the measured attribute and the initial correlations between point values and explanatory variables, but suggests that the model approach is in general scale invariant. Copyright (C) 2009 John Wiley & Sons, Ltd.

  • 3. Halldin, S
    et al.
    Bergstrom, H
    Gustafsson, D
    Dahlgren, L
    SMHI.
    Hjelm, P
    Lundin, L C
    Mellander, P E
    Nord, T
    Jansson, P E
    Seibert, J
    Stahli, M
    Kishne, A S
    Smedman, A S
    Continuous long-term measurements of soil-plant-atmosphere variables at an agricultural site1999In: Agricultural and Forest Meteorology, ISSN 0168-1923, E-ISSN 1873-2240, Vol. 98-9, p. 75-102Article in journal (Refereed)
    Abstract [en]

    It is a major challenge in modem science to decrease the uncertainty in predictions of global climate change. One of the largest uncertainties in present-day global climate models resides with the understanding of processes in the soil-vegetation-atmosphere-transfer (SVAT) system. Continuous, long-term data are needed to correctly quantify balances of water, energy and CO2 in this system and to correctly model them. It is the objective of this paper to demonstrate how a combined system of existing sensor, computer, and network technologies could be set up to provide continuous and reliable long-term SVAT-process data from an agricultural site under almost all weather conditions. A long-term climate-monitoring system within the framework of NOPEX was set up in 1993-1994 at the Marsta Meteorological Observatory (MMO). It is situated in a flat agricultural area where annual crops are cultivated on a heavy clay soil. It has successfully monitored relevant states and fluxes in the system, such as atmospheric fluxes of momentum, heat, water vapour and CO2, atmospheric profiles of wind speed, direction, and temperature, short- and long-wave radiation, soil temperature, soil-water contents, groundwater levels, and rainfall and snow depth. System uptime has been more than 90% for most of its components during the first 5 years of operation. Results from the first 5 years of operation has proven MMO to be an ideal site for intercomparison and intercalibration of radiometers and fast turbulence sensors, and for evaluation of other sensors, e.g., rain gauges. The long time series of radiation data have been valuable to establish numerical limits for a set of quality-control flags. MMO has served as a boundary-layer research station and results from NOPEX campaigns show how the dimensionless wind gradient depends not only on the traditional stability parameter z/L but also on the height of the convective boundary layer. Measurements at the observatory grounds and a neighbouring field show a considerable variability in surface properties, which must be accounted for when assessing budgets of heat and other scalars. Questions concerning long-term calibration plans, maintenance of sensors and data-collection system, and continuous development of the computer network to keep it up to date are, however, only partly of interest as a research project in itself. It is thus difficult to get it funded from usual research-funding agencies. The full value of data generated by the: MMO system can best be appreciated after a decade or more of continuous operation. Main uses of the data would be to evaluate how SVAT models handle the natural variability of climate conditions, quantification of water, carbon and energy budgets during various weather conditions, and development of new parameterisation schemes in global and regional climate models. (C) 1999 Elsevier Science B.V. All rights reserved.

  • 4. Lyon, Steve W.
    et al.
    Nathanson, Marcus
    Spans, Andre
    Grabs, Thomas
    Laudon, Hjalmar
    Temnerud, Johan
    SMHI, Research Department, Hydrology.
    Bishop, Kevin H.
    Seibert, Jan
    Specific discharge variability in a boreal landscape2012In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 48, article id W08506Article in journal (Refereed)
    Abstract [en]

    Specific discharge variations within a mesoscale catchment were studied on the basis of three synoptic sampling campaigns. These were conducted during stable flow conditions within the Krycklan catchment study area in northern Sweden. During each campaign, about 80 individual locations were measured for discharge draining from catchment areas ranging between 0.12 and 67 km(2). These discharge samplings allowed for the comparison between years within a given season (September 2005 versus September 2008) and between seasons within a given year (May 2008 versus September 2008) of specific discharge across this boreal landscape. There was considerable variability in specific discharge across this landscape. The ratio of the interquartile range (IQR) defined as the difference between the 75th and 25th percentiles of the specific discharges to the median of the specific discharges ranged from 37% to 43%. Factor analysis was used to explore potential relations between landscape characteristics and the specific discharge observed for 55 of the individual locations that were measured in all three synoptic sampling campaigns. Percentage wet area (i.e., wetlands, mires, and lakes) and elevation were found to be directly related to the specific discharge during the drier September 2008 sampling while potential annual evaporation was found to be inversely related. There was less of a relationship determined during the wetter post spring flood May 2008 sampling and the late summer rewetted September 2005 sampling. These results indicate the ability of forests to "dry out" parts of the catchment over the summer months while wetlands "keep wet" other parts. To demonstrate the biogeochemical implications of such spatiotemporal variations in specific discharge, we estimate dissolved organic carbon (DOC) exports with available data for the May 2008 and September 2008 samplings using both the spatially variable observed specific discharges and the spatially constant catchment average values. The average absolute difference in DOC export for the various subcatchments between using a variable and using a constant specific discharge was 28% for the May 2008 sampling and 20% for the September 2008 sampling.

  • 5. Teutschbein, Claudia
    et al.
    Wetterhall, Fredrik
    SMHI, Research Department, Hydrology.
    Seibert, Jan
    Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale2011In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 37, no 9-10, p. 2087-2105Article in journal (Refereed)
    Abstract [en]

    Hydrological modeling for climate-change impact assessment implies using meteorological variables simulated by global climate models (GCMs). Due to mismatching scales, coarse-resolution GCM output cannot be used directly for hydrological impact studies but rather needs to be downscaled. In this study, we investigated the variability of seasonal streamflow and flood-peak projections caused by the use of three statistical approaches to downscale precipitation from two GCMs for a meso-scale catchment in southeastern Sweden: (1) an analog method (AM), (2) a multi-objective fuzzy-rule-based classification (MOFRBC) and (3) the Statistical DownScaling Model (SDSM). The obtained higher-resolution precipitation values were then used to simulate daily streamflow for a control period (1961-1990) and for two future emission scenarios (2071-2100) with the precipitation-streamflow model HBV. The choice of downscaled precipitation time series had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approaches to reproduce observed precipitation. Although SDSM was considered to be most suitable for downscaling precipitation in the studied river basin, we highlighted the importance of an ensemble approach. The climate and streamflow change signals indicated that the current flow regime with a snowmelt-driven spring flood in April will likely change to a flow regime that is rather dominated by large winter streamflows. Spring flood events are expected to decrease considerably and occur earlier, whereas autumn flood peaks are projected to increase slightly. The simulations demonstrated that projections of future streamflow regimes are highly variable and can even partly point towards different directions.

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