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Author Wallach, D.; Nissanka, S.P.; Karunaratne, A.S.; Weerakoon, W.M.W.; Thorburn, P.J.; Boote, K.J.; Jones, J.W. url  doi
openurl 
  Title Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice Type Journal Article
  Year 2016 Publication European Journal of Agronomy Abbreviated Journal European Journal of Agronomy  
  Volume Issue Pages  
  Keywords Uncertainty; Phenology; Parameter uncertainty; Multi-model ensemble; Generalized least squares; Rice; Crop model; APSIM; DSSAT  
  Abstract We consider predictions of the impact of climate warming on rice development times in Sri Lanka. The major emphasis is on the uncertainty of the predictions, and in particular on the estimation of mean squared error of prediction. Three contributions to mean squared error are considered. The first is parameter uncertainty that results from model calibration. To take proper account of the complex data structure, generalized least squares is used to estimate the parameters and the variance-covariance matrix of the parameter estimators. The second contribution is model structure uncertainty, which we estimate using two different models. An ANOVA analysis is used to separate the contributions of parameter and model uncertainty to mean squared error. The third contribution is model error, which is estimated using hindcasts. Mean squared error of prediction of time from emergence to maturity, for baseline +2 °C, is estimated as 108 days2, with model error contributing 86 days2, followed by model structure uncertainty which contributes 15 days2 and parameter uncertainty which contributes 7 days2. We also show how prediction uncertainty is reduced if prediction concerns development time averaged over years, or the difference in development time between baseline and warmer temperatures.  
  Address 2016-09-13  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1161-0301 ISBN Medium Article  
  Area CropM Expedition Conference  
  Notes (down) CropM; wos; ftnotmacsur; wsnotyet; Approved no  
  Call Number MA @ admin @ Serial 4777  
Permanent link to this record
 

 
Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. url  doi
openurl 
  Title Lessons from climate modeling on the design and use of ensembles for crop modeling Type Journal Article
  Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change  
  Volume Issue Pages  
  Keywords Model ensembles; Crop models; Climate models; Model weighting; Super ensembles  
  Abstract Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0165-0009 1573-1480 ISBN Medium Review  
  Area CropM Expedition Conference  
  Notes (down) CropM; wos; ft=macsur; wsnotyet; Approved no  
  Call Number MA @ admin @ Serial 4781  
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Author Webber, H.; Gaiser, T.; Oomen, R.; Teixeira, E.; Zhao, G.; Wallach, D.; Zimmermann, A.; Ewert, F. openurl 
  Title Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe Type Journal Article
  Year 2016 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.  
  Volume Issue Pages  
  Keywords crop model; impact assessment; crop water use; evapotranspiration; irrigation; drought; uncertainty  
  Abstract While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2-3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1-2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley-Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced.  
  Address 2016-09-13  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Language Summary Language Newsletter July Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium Article  
  Area CropM Expedition Conference  
  Notes (down) CropM; wos; ft=macsur; Approved no  
  Call Number MA @ admin @ Serial 4778  
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Author Liu, X.; Lehtonen, H.; Purola, T.; Pavlova, Y.; Rötter, R.; Palosuo, T. url  doi
openurl 
  Title Dynamic economic modelling of crop rotations with farm management practices under future pest pressure Type Journal Article
  Year 2016 Publication Agricultural Systems Abbreviated Journal Agricultural Systems  
  Volume 144 Issue Pages 65-76  
  Keywords Farm management; Dynamic optimization; Crop rotation; Risk aversion; Climate change; Prices; climate-change; sequester carbon; changing climate; food security; challenge; Finland; ensembles; systems; europe; tool  
  Abstract Agricultural practice is facing multiple challenges under volatile commodity markets, inevitable climate change, mounting pest pressure and various other environment-related constraints. The objective of this research is to present a dynamic optimization model of crop rotations and farm management and show its suitability for economic analysis over a 30 year time period. In this model, we include management practices such as fertilization, fungicide treatment and liming, and apply it in a region in Southwestern Finland. Results show that (i) growing pest pressure favours the cultivation of wheat-oats and wheat-oilseeds combinations, while (ii) market prices largely determine the crops in the rotation plan and the specific management practices adopted. The flexibility of our model can also be utilized in evaluating the value of other management options such as new cultivars under different projections of future climate and market conditions.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0308521x ISBN Medium Article  
  Area Expedition Conference  
  Notes (down) CropM, TradeM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4719  
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Author Schönhart, M.; Schauppenlehner, T.; Kuttner, M.; Kirchner, M.; Schmid, E. url  doi
openurl 
  Title Climate change impacts on farm production, landscape appearance, and the environment: Policy scenario results from an integrated field-farm-landscape model in Austria Type Journal Article
  Year 2016 Publication Agricultural Systems Abbreviated Journal Agricultural Systems  
  Volume 145 Issue Pages 39-50  
  Keywords Integrated land use modeling; Climate change impacts; Mitigation; Adaptation; Field-farm-landscape; Environment; agricultural landscapes; land-use; netherlands; adaptation; indicators; management; responses  
  Abstract Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0308-521x ISBN Medium Article  
  Area Expedition Conference  
  Notes (down) CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4767  
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