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Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change

Smith, Pascalle ; Heinrich, Georg ; Suklitsch, Martin ; Gobiet, Andreas ; Stoffel, Markus ; Fuhrer, Jürg

In: Climatic Change, 2014, vol. 127, no. 3-4, p. 521-534

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    Title
    • Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change
    Author
    • Smith, Pascalle. Agroscope, Air pollution/Climate Group, Reckenholzstrasse 191, 8046, Zürich, Switzerland
    • Heinrich, Georg. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010, Graz, Austria
    • Suklitsch, Martin. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010, Graz, Austria
    • Gobiet, Andreas. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010, Graz, Austria
    • Stoffel, Markus. Institute for Environmental Sciences, University of Geneva, 7 route de Drize, 1227, Carouge, Switzerland
    • Fuhrer, Jürg. Agroscope, Air pollution/Climate Group, Reckenholzstrasse 191, 8046, Zürich, Switzerland
    Document Type
    • Postprint
    Classification
    • Earth sciences
    OAI-PMH Identifier
    • oai:doc.rero.ch:326376
    Summary
    Irrigation water requirements (IWR) are expected to be influenced by changes in the climate variables driving water availability in the soil-plant system. Most of the agricultural surface areas of the heterogeneous Swiss Rhone catchment are already exposed to drought. Aiming at investigating future pressures on the water resources to fill the growing gap between rain-fed and optimum water supply for cultivation, we downscaled and bias corrected 16 regional climate scenarios from the ENSEMBLES dataset for the period 1951-2050 using a Quantile Mapping methodology calibrated with daily observations from 5 contrasting weather stations. The data reveal an increased evaporative demand over the growing season for almost all stations and scenarios (2021-2049 vs. 1981-2009). The picture is less clear for precipitation, with a projected decrease or increase depending on the scenario, station and month. The main results indicate that bias correction of climate scenarios not only reduces the remaining error between baseline and observations but also enhances the change signal in seasonal IWR estimates. This is due to a higher and more realistic sensitivity of IWR to the atmospheric water budget, the slope of this relationship being steeper in the observations than in the uncorrected data. The seasonal cycle of the IWR change signal shows different sensitivities and climate drivers across crops (grassland and maize) and stations, but a consistent trend towards an increase despite uncertainty. This increased water demand will have to be reconciled with possibly decreased or shifted future water availability from glacier and snow melt.