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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2021

To document

Abstract

Robust projections of changes in the hydrological cycle in a non-stationary climate rely on trustworthy estimates of the water balance elements. Additional drivers than precipitation and temperature, namely wind, radiation, and humidity are known to have a significant influence on processes such as evaporation, snow accumulation, and snow-melt. A gridded version of the rainfall-runoff HBV model is run at a 1 × 1 km scale for mainland Norway for the period 1980–2014, with the following alterations: (i) the implementation of a physically based evaporation scheme; (ii) a net radiation-restricted degree-day factor for snow-melt, and (iii) a diagnostic precipitation phase threshold based on temperature and humidity. The combination of improved forcing data and model alterations allowed for a regional calibration with fewer calibrated parameters. Concurrently, modeled discharge showed equally good or better validation results than previous gridded model versions constructed for the same domain; and discharge trend patterns, snow water equivalent, and potential evaporation compared fairly to observations. Compared with previous studies, lower precipitation and evaporation values for mainland Norway were found. The results suggest that a more robust and more physically based model for climate change studies has been obtained, although additional studies will be needed to further constrain evaporation estimates.

To document

Abstract

The disease pressure from Pyrenophora teres, Rhynchosporium graminicola, and Ramularia collo–cygni varies widely between years and locations, which highlights the need for using risk models to avoid unnecessary use of fungicides. Three disease risk models were tested in thirty–three field trials during two seasons in five countries in order to validate and identify situations favourable for barley leaf blotch diseases in the Nordic–Baltic region. The tested models were: The Crop Protection Online (CPO), which uses number of days with precipitation (>1 mm), cultivar resistance and disease data as basis for risk assessments; the humidity model (HM) which signals a risk warning after 20 continuous hours with high humidity, and the Finnish net blotch model (WisuEnnuste), which calculates a risk based on previous crop, tillage method, cultivar resistance and weather parameters. The risk models mostly gave acceptable control of diseases and yield responses compared with untreated and reference treatments. In the dry season of 2018, the models recommended 88–96% fewer applications than the reference treatments, while in 2019, the number of applications was reduced by 0–76% compared to reference treatments. Based on yield increases, the recommendations were correct in 50–69% of the trials compared to one–treatment references and 69–80% of the trials when references used mainly two treatments.