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Water 2016, 8(12), 571; doi:10.3390/w8120571

Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat

1
Leibniz Centre for Agricultural Landscape Research (ZALF), D-15374 Müncheberg, Germany
2
Wageningen University & Research—Environmental Research (Alterra), NL-6700 AA Wageningen, The Netherlands
3
Flemish Institute for Technological Research (Vito NV), B-2400 Mol, Belgium
4
National Agricultural and Food Centre, Soil Science and Conservation Research Institute, SK-827 13 Bratislava, Slovakia
5
Institute of Agriculture Systems and Bioclimatology, Mendel University, CZ-613 00 Brno, Czech Republic
6
Global Change Research Institute, The Czech Academy of Sciences, CZ-603 00 Brno, Czech Republic
7
Consiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria, Unità di Ricerca per i Sistemi Colturali degli Ambienti Caldo-Aridi, I-70125 Bari, Italy
8
Department of Agri-Food Production and Environmental Sciences, DISPAA, University of Florence, I-50144 Firenze, Italy
9
Institute of Biometeorology of the National Research Council (CNR-IBIMET), I-50145 Firenze, Italy
10
Climate Change Cluster, University of Technology, Sydney 2007, Australia
11
Institute of Meteorology, University of Natural Resources and Life Sciences, A-1180 Vienna, Austria
12
Thünen Institute of Biodiversity, D-38116 Braunschweig, Germany
13
Tropical Plant Production and Agricultural Systems Modelling, Georg-August-University, D-37077 Göttingen, Germany
14
Earth Science Institute of Slovak Academy of Science, SK-840 05 Bratislava, Slovakia
15
AGES—Austrian Agency for Health and Food Safety Ltd., A-1220 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: Arjen Y. Hoekstra
Received: 18 September 2016 / Revised: 23 November 2016 / Accepted: 28 November 2016 / Published: 5 December 2016
(This article belongs to the Special Issue Water Footprint Assessment)
View Full-Text   |   Download PDF [2690 KB, uploaded 5 December 2016]   |  

Abstract

Crop productivity and water consumption form the basis to calculate the water footprint (WF) of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment) experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration. View Full-Text
Keywords: water footprint; uncertainty; model ensemble; wheat; crop yield water footprint; uncertainty; model ensemble; wheat; crop yield
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kersebaum, K.C.; Kroes, J.; Gobin, A.; Takáč, J.; Hlavinka, P.; Trnka, M.; Ventrella, D.; Giglio, L.; Ferrise, R.; Moriondo, M.; Dalla Marta, A.; Luo, Q.; Eitzinger, J.; Mirschel, W.; Weigel, H.-J.; Manderscheid, R.; Hoffmann, M.; Nejedlik, P.; Iqbal, M.A.; Hösch, J. Assessing Uncertainties of Water Footprints Using an Ensemble of Crop Growth Models on Winter Wheat. Water 2016, 8, 571.

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