Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2019
Forfattere
Knut ØistadSammendrag
Det er ikke registrert sammendrag
Forfattere
Knut ØistadSammendrag
Det er ikke registrert sammendrag
Sammendrag
Bipolar surface EMG (sEMG) signals of the trapezius muscles bilaterally were recorded continuously with a frequency of 800 Hz during full-shift field-work by a four-channel portable data logger. After recordings of 60 forest machine operators in Finland, Norway and Sweden, we discovered erroneous data. In short of any available procedure to handle these data, a method was developed to automatically discard erroneous data in the raw data reading files (Discarding Erroneous EPOchs (DESEPO) method. The DESEPO method automatically identifies, discards and adjusts the use of signal disturbances in order to achieve the best possible data use. An epoch is a 0.1 s period of raw sEMG signals and makes the basis for the RMS calculations. If erroneous signals constitute more than 30% of the epoch signals, this classifies for discharge of the present epoch. Non-valid epochs have been discarded, as well as all the subsequent epochs. The valid data for further analyses using the automatic detection resulted in an increase of acceptable data from an average of 2.15–6.5 h per day. The combination of long-term full-shift recordings and automatic data reduction procedures made it possible to use large amount of data otherwise discarded for further analyses.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Jamal Zaherpour Nick Mount Simon N. Gosling Rutger Dankers Stephanie Eisner Dieter Gerten Xingcai Liu Yoshimitsu Masaki Hannes Müller Schmied Qiuhong Tang Yoshihide WadaSammendrag
This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global catchments. The benchmarked, median performance gain of the MMC solutions is 45% compared to the best performing GHM and exceeds 100% when compared to the ensemble mean (EM). The performance gain offered by MMC suggests that future multi-model applications consider reporting MMCs, alongside the EM and intermodal range, to provide end-users of GHM ensembles with a better contextualised estimate of runoff. Importantly, the study highlights the difficulty of interpreting complex, non-linear MMC solutions in physical terms. This indicates that a pragmatic approach to future MMC studies based on machine learning methods is required, in which the allowable solution complexity is carefully constrained.
Sammendrag
A robust hydrological modeling at a fine spatial resolution is a vital tool for Norway to simulate river discharges and hydrological components for climate adaptation strategies. However, it requires improvements of modelling methods, detailed observational data as input and expensive computational resources. This work aims to set up a distributed version of the HBV model with a physically based evapotranspiration scheme at 1 km resolution for mainland Norway and to calibrate/validate the model for 124 catchments using regionalized parameterizations. The Penman-Monteith equation was implemented in the HBV model and vegetation characteristics were derived from the Norwegian forest inventory combined with multi-source remote sensing data at 16 m spatial resolution. The estimated potential evapotranspiration (Ep) was compared with pan measurements and estimates from the MODerate Resolution Imaging Spectrometer (MOD16) products, the Global Land Evaporation Amsterdam Model (GLEAM) and Variable Infiltration Capacity (VIC) hydrological model. There are 5 climatic zones in Norway classified based on 4 temperature and precipitation indices. For each zone, the model was calibrated separately by optimizing a multi-objective function including the Nash-Sutcliff efficiency (NSE) and biases of selected catchments. In total, there are 85 catchments for calibration and 39 for validation. The Ep estimates showed good agreement with the measurements, GLEAM and VIC outputs. However, the MOD16 product significantly overestimates Ep compared to the other products. The discharge was well reproduced with the median daily NSE of 0.68/0.67, bias of −3%/−1%, Kling-Gupta efficiency (KGE) of 0.70/0.69 and monthly NSE of 0.80/0.78 in the calibration/validation periods. Our results showed a significant improvement compared to the previous HBV application for all catchments, with an increase of 0.08–0.16 in the median values of the daily NSE, KGE and monthly NSE. Both the temporal and spatial transferability of model parameterizations were also enhanced compared to the previous application.
Forfattere
Jan Magnusson Stephanie Eisner Shaochun Huang Cristian Lussana Giulia Mazzotti Richard Essery Tuomo Saloranta Stein BeldringSammendrag
Climate models show that global warming will disproportionately influence high‐latitude regions and indicate drastic changes in, among others, seasonal snow cover. However, current continental and global simulations covering these regions are often run at coarse grid resolutions, potentially introducing large errors in computed fluxes and states. To quantify some of these errors, we have assessed the sensitivity of an energy‐balance snow model to changes in grid resolution using a multiparametrization framework for the spatial domain of mainland Norway. The framework has allowed us to systematically test how different parametrizations, describing a set of processes, influence the discrepancy, here termed the scale error, between the coarser (5 to 50‐km) and finest (1‐km) resolution. The simulations were set up such that liquid and solid precipitation was identical between the different resolutions, and differences between the simulations arise mainly during the ablation period. The analysis presented in this study focuses on evaluating the scale error for several variables relevant for hydrological and land surface modelling, such as snow water equivalent and turbulent heat exchanges. The analysis reveals that the choice of method for routing liquid water through the snowpack influences the scale error most for snow water equivalent, followed by the type of parametrizations used for computing turbulent heat fluxes and albedo. For turbulent heat exchanges, the scale error is mainly influenced by model assumptions related to atmospheric stability. Finally, regions with strong meteorological and topographic variability show larger scale errors than more homogenous regions.
Forfattere
Stephanie EisnerSammendrag
Det er ikke registrert sammendrag
Sammendrag
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Forfattere
Katrin ZimmerSammendrag
Det er ikke registrert sammendrag