toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
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 (up) 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 CropM; wos; ft=macsur; Approved no  
  Call Number MA @ admin @ Serial 4778  
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 (up) 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 CropM; wos; ft=macsur; wsnotyet; Approved no  
  Call Number MA @ admin @ Serial 4781  
Permanent link to this record
 

 
Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. 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 139 Issue 3-4 Pages 551-564  
  Keywords change projections; elevated CO2; uncertainty; wheat; water; soil; simulations; yield; rice; 21st-century; Model ensembles; Crop models; Climate models; Model weighting; Super ensembles  
  Abstract (up) 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 2017-01-06  
  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 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_MACSUR Approved no  
  Call Number MA @ admin @ Serial 4933  
Permanent link to this record
 

 
Author van Lingen, H.J.; Plugge, C.M.; Fadel, J.G.; Kebreab, E.; Bannink, A.; Dijkstra, J. url  doi
openurl 
  Title Correction: Thermodynamic Driving Force of Hydrogen on Rumen Microbial Metabolism: A Theoretical Investigation Type Miscellaneous
  Year 2016 Publication PLoS One Abbreviated Journal PLoS One  
  Volume 11(12) Issue 12 Pages e0168052  
  Keywords  
  Abstract (up) [This corrects the article DOI: 10.1371/journal.pone.0161362.].  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1932-6203 ISBN Medium  
  Area Expedition Conference  
  Notes LiveM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 5020  
Permanent link to this record
 

 
Author Vitti, C.; Stellacci, A.M.; Leogrande, R.; Mastrangelo, M.; Cazzato, E.; Ventrella, D. url  doi
openurl 
  Title Assessment of organic carbon in soils: a comparison between the Springer–Klee wet digestion and the dry combustion methods in Mediterranean soils (Southern Italy) Type Journal Article
  Year 2016 Publication Catena Abbreviated Journal Catena  
  Volume 137 Issue Pages 113-119  
  Keywords  
  Abstract (up) • Comparison of two methods for soil organic C quantification is presented. • Springer–Klee wet digestion and dry combustion with automated analyser were compared. • Soil samples were collected from three different sites in a Southern Italy area. • Recoveries close to one were observed for whole dataset and for data grouped per site. • The strong agreement between the methods would enable direct comparison of results. Abstract Soil organic carbon (SOC) is the largest carbon pool in the terrestrial biosphere and it is among the most important factors responsible for conservation of soil quality. Automated dry combustion techniques are gradually replacing traditional quantification methods based on wet digestion chemistry. Critical comparison of different methods is fundamental to reevaluate archives of SOC data and accurately assess and model long-term carbon stock variation and should be performed for different soil types and management conditions. Two analytical methods, the Springer–Klee wet digestion and the dry combustion using an automated analyser, were compared for soils typical of a Mediterranean environment in Southern Italy. Soil samples were collected from three sites, at two depths. Soils were fine textured (from clay–loam to clay) with total carbonate ranging from 6.6 to 16.7 g 100 g− 1. SOC content varied from 6.92 to 28.86 g kg− 1 (as average of the two methods), with values and ranges typical of Southern Europe. On average, Springer–Klee method gave slightly higher values and showed greater data variability. This behaviour, in agreement with other studies, can be attributed to the reaction of K2Cr2O7 with other soil constituents and to analytical constraints. Our results suggest high consistency between Springer–Klee and dry combustion techniques and show recoveries close to one both for the whole dataset and for data grouped per experimental site or soil depth. Linear regression equations between the two methods were slightly affected by different soil types (P = 0.0621). The best fitting of the relationship was a linear regression passing through the origin for the whole dataset (Radj2 = 0.965; RPD = 3.41). The strong overall agreement observed between the two methods would enable the direct comparison of new data set with those already existing in Southern Italy for soils with similar characteristics.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0341-8162 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4989  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: