Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments
2018
Tao, Fulu | Rotter, Reimund P. | Palosuo, Taru | Gregorio Hernández Díaz-Ambrona, Carlos | Minguez, M. Ines | Semenov, Mikhail A. | Kersebaum, Kurt Christian | Nendel, Claas | Specka, Xenia | Hoffmann, Holger | Ewert, Frank | Dambreville, Anaëlle | Martre, Pierre | Rodríguez, Lucía | Ruiz-Ramos, Margarita | Gaiser, Thomas | Höhn, Jukka G. | Salo, Tapio | Ferrise, Roberto | Bindi, Marco | Cammarano, Davide | Schulman, Alan H. | Natural Resources Institute Finland (LUKE) | Georg-August-University of Göttingen = Georg-August-Universität Göttingen | Centre for Biodiversity and Sustainable Land Use (CBL) ; Georg-August-University of Göttingen = Georg-August-Universität Göttingen | University of Madrid | Biotechnology and Biological Sciences Research Council (BBSRC) | Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF) | Crop Science Group, INRES ; Rheinische Friedrich-Wilhelms-Universität Bonn | Écophysiologie des Plantes sous Stress environnementaux (LEPSE) ; Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Department of Agri-Food Production and Environmental Sciences ; Università degli Studi di Firenze = University of Florence = Université de Florence (UniFI) | The James Hutton Institute | Helsingin yliopisto = Helsingfors universitet = University of Helsinki | FACCE-JPI, the FACCE-MACSUR, Grant/Award Number: 031A103B; Finland Ministry of Agriculture and Forestry, FACCE-MACSUR; Academy of Finland, the NORFASYS, Grant/Award Number: 268277, 292944; PLUMES, Grant/Award Number: 277403, 292836; German Federal Ministry of Education and Research, Grant/Award Number: 01LL1304A, 031A351A; Spanish Ministry of Economy, Industry and Competitiveness, the MULCLIVAR, Grant/Award Number: CGL2012-38923- C02-02; German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), Grant/Award Number: 2851ERA01J; German Ministry of Education and Research BMBF), Grant/Award Number: 031B0039C; French National Institute for Agricultural Research, Grant/Award Number: 031A103B; Italian Ministry for Agricultural, Food, and Forestry Policies; Biotechnology and Biological Sciences Research Council (BBSRC), Grant/Award Number: BB/P016855/1 | European Project: 613556,EC:FP7:KBBE,FP7-KBBE-2013-7-single-stage,WHEALBI(2014)
International audience
اظهر المزيد [+] اقل [-]إنجليزي. Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was −4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل Institut national de la recherche agronomique