The error in agricultural systems model prediction depends on the variable being predicted

Environmental Modelling and Software

Volumn 62, Issue , 2014, Pages 487-494

  Wallach, Daniel ^a   Thorburn, Peter J ^b  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b CSIRO   (Australia)

Author keywords

APSIM; Error; GHG emissions; Irrigation; Maize; Nitrous oxide; Uncertainty

Indexed keywords

FORECASTING; GREENHOUSE GASES; IRRIGATION; NITROGEN OXIDES;

APSIM; GHG EMISSION; MAIZE; NITROUS OXIDE; UNCERTAINTY;

ERRORS;

AGRICULTURAL EMISSION; AGRICULTURAL MODELING; ERROR ANALYSIS; FARMING SYSTEM; GREENHOUSE GAS; IRRIGATION SYSTEM; MODEL TEST; NITROUS OXIDE; PREDICTION;

ZEA MAYS;

EID: 85027923389     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2014.08.001     Document Type: Article

References (42)

1. L.R. Ahuja, L. Ma (Eds.). 2011, Methods of Introducing System Models into Agricultural Research. Advances in Agricultural Systems Modeling, vol. 2. American Society of Agronomy, Inc., Madison, Wisconsin, USA.
2. Allen D., Kingston G., Rennenberg H., Dalal R., Schmidt S. Effect of nitrogen fertiliser management and waterlogging on nitrous oxide emission from subtropical sugarcane soils. Agric. Ecosyst. Environ. 2010, 136:209-217.
3. Asseng S., Ewert F., Rosenzweig C., Jones J.W., Hatfield J.L., Ruane A.C., Boote K.J., Thorburn P.J., Rötter R.P., Cammarano D., Brisson N., Basso B., Martre P., Aggarwal P.K., Angulo C., Bertuzzi P., Biernath C., Challinor A.J., Doltra J., Gayler S., Goldberg R., Grant R., Heng L., Hooker J., Hunt L.A., Ingwersen J., Izaurralde R.C., Kersebaum K.C., Müller C., Naresh Kumar S., Nendel C., O'Leary G., Olesen J.E., Osborne T.M., Palosuo T., Priesack E., Ripoche D., Semenov M.A., Shcherbak I., Steduto P., Stöckle C., Stratonovitch P., Streck T., Supit I., Tao F., Travasso M., Waha K., Wallach D., White J.W., Williams J.R., Wolf J. Uncertainty in simulating wheat yields under climate change. Nat. Clim. Change 2013, 3:827-832.
4. Bennett N.D., Croke B.F.W., Guariso G., Guillaume J.H.A., Hamilton S.H., Jakeman A.J., Marsili-Libelli S., Newham L.T.H., Norton J.P., Perrin C., Pierce S.A., Robson B., Seppelt R., Voinov A.A., Fath B.D., Andreassian V. Characterising performance of environmental models. Environ. Model. Softw. 2013, 40:1-20.
5. Biggs J.S., Thorburn P.J., Crimp S.J., Masters B., Attard S.J. Interactions between climate change and sugarcane management systems for improving water quality leaving farms in the Mackay-Whitsunday region, Australia. Agric. Ecosyst. Environ. 2013, 180:79-89.
6. Carberry P.S., Liang W., Twomlow S., Holzworth D.P., Dimes J.P., McClelland T., Huth N.I., Chen F., Hochman Z., Keating B.A. Scope for improved eco-efficiency varies among diverse cropping systems. Proc. Natl. Acad. Sci. U.S.A. 2013, 110:8381-8386.
7. Carroll C., Waters D., Vardy S., Silburn D.M., Attard S., Thorburn P.J., Davis A.M., Schmidt M., Wilson B., Clark A. Apaddock to reef monitoring and modelling framework for the Great Barrier Reef: paddock and catchment component. Mar. Pollut. Bull. 2012, 65:136-149.
8. Cichota R., Snow V.O., Vogeler I. Modelling nitrogen leaching from overlapping urine patches. Environ. Model. Softw. 2013, 41:15-26.
9. Confalonieri R., Bregaglio S., Acutis M. Aproposal of an indicator for quantifying model robustness based on the relationship between variability of errors and of explored conditions. Ecol. Modell. 2010, 221:960-964.
10. Cvetkovski Z. Inequalities. Theorems, Techniques and Selected Problems 2010, Springer, Heidelberg.
11. 2O data from irrigated rotations in Colorado. J.Environ. Qual. 2008, 37:1383-1389.
12. Denmead O.T., Macdonald B.C.T., Bryant G., Naylor T., Wilson S., Griffith D.W.T., Wang W.J., Salter B., White I., Moody P.W. Emissions of methane and nitrous oxide from Australian sugarcane soils. Agric. For. Meteorol. 2010, 150:748-756.
13. Ercin A.E., Mekonnen M.M., Hoekstra A.Y. The Water Footprint of France, Value of Water 2012, Research Report Series No.48, UNESCO-IHE, Delft, the Netherlands.
14. Ferrara R.M., Trevisiol P., Acutis M., Rana G., Richter G.M., Baggaley N. Topographic impacts on wheat yields under climate change: two contrasted case studies in Europe. Appl. Theor. Clim. 2010, 99(1-2):53-65.
15. 2O emissions from soils at three temperate agricultural sites: simulations of year-round measurements by four models. Nutr. Cycl. Agroecosyst. 1998, 52:77-105.
16. Godfray H.C.J., Beddington J.R., Crute I.R., Haddad L., Lawrence D., Muir J.F., Pretty J., Robinson S., Thomas S.M., Toulmin C. Food security: the challenge of feeding 9 billion people. Science 2010, 327:812-818.
17. Hartford A., Davidian M. Consequences of misspecifying assumptions in nonlinear mixed effects models. Comput. Stat. Data Anal. 2000, 34:139-164.
18. Holzworth D.P., Huth N.I., deVoil P.G., Zurcher E.J., Herrmann N.I., McLean G., et al. APSIM - evolution towards a new generation of agricultural systems simulation. Environ. Model. Softw. 2014, 62:327-350.
19. Howden S.M., Soussana J.F., Tubiello F.N., Chhetri N., Dunlop M., Meinke H. Adapting agriculture to climate change. Proc. Natl. Acad. Sci. U.S.A. 2007, 104:19691-19696.
20. Kobayashi K., Salam M.U. Comparing simulated and measured values using mean squared deviation and its components. Agron. J. 2000, 92:345-352.
21. Laniak G.F., Olchin G., Goodall J., Voinov A., Hill M., Glynn P., Whelan G., Geller G., Quinn N., Blind M., Peckham S., Reaney S., Gaber N., Kennedy R., Hughes A. Integrated environmental modeling: a vision and roadmap for the future. Environ. Model. Softw. 2013, 39:3-23.
22. Lindstrom M.J., Bates D.M. Nonlinear mixed effects models for repeated measures data. Biometrics 1990, 46:673-687.
23. R Development Core Team R: a Language and Environment for Statistical Computing 2013, R Foundation for Statistical Computing, Vienna, Austria. http://www.r-project.org.
24. Refsgaard J.C., van der Sluijs J.P., Højberg A.L., Vanrolleghem P.A. Uncertainty in the environmental modelling process - a framework and guidance. Environ. Model. Softw. 2007, 22:1543-1556.
25. Rosenzweig C., Parry M.L. Potential impact of climate change on world food supply. Nature 1994, 367:133-138.
26. Rosenzweig C., Jones J.W., Hatfield J.L., Ruane A.C., Boote K.J., Thorburn P.J., Antle J., Nelson G., Porter C., Janssen S., Asseng S., Winter J.M., Greeley A.P. The agricultural model intercomparison and improvement project (AgMIP): protocols and pilot studies. Agric. For. Meteorol. 2013, 170:166-182.
27. Rötter R.P., Carter T.R., Olesen J.E., Porter J.R. Crop-climate models need an overhaul. Nat. Clim. Change 2011, 1:175-177.
28. Rötter R.P., Palosuo T., Kersebaum K.C., Angulo C., Bindi M., Ewert F., Ferrise R., Hlavinka P., Moriondo M., Nendel C., Olesen J.E., Patil R.H., Ruget F., Takáč J., Trnka M. Simulation of spring barley yield in different climatic zones of Northern and Central Europe: a comparison of 9 crop models. Field Crops Res. 2012, 133:23-36.
29. Saltelli A., Annoni P. How to avoid a perfunctory sensitivity analysis. Environ. Model. Softw. 2010, 25:1508-1517.
30. Smith P., Martino D., Cai Z., Gwary D., Janzen H., Kumar P., McCarl B., Ogle S., O'Mara F., Rice C., Scholes B., Sirotenko O., Howden M., McAllister T., Pan G., Romanenkov V., Schneider U., Towprayoon S., Wattenbach M., Smith J. Greenhouse gas mitigation in agriculture. Philos. Trans. Roy. Soc. B 2008, 363:789-813.
31. Tilman D., Balzer C., Hill J., Befort B.L. Global food demand and the sustainable intensification of agriculture. Proc. Natl. Acad. Sci. U.S.A. 2011, 108:20260-20264.
32. Thorburn P.J., Biggs J.S., Attard S.J., Kemei J. Environmental impacts of irrigated sugarcane production: nitrogen lost through runoff and leaching. Agric. Ecosyst. Environ. 2011, 144:1-12.
33. Thorburn P.J., Biggs J.S., Collins K., Probert M.E. Using the APSIM model to estimate nitrous oxide emissions from diverse Australian sugarcane production systems. Agric. Ecosyst. Environ. 2010, 136:343-350.
34. Thorburn P.J., Biggs J.S., Macdonald B.C.T., Allen D.E., Denmead O.T., Marin F.R. Exploring the wide range of nitrous oxide emissions from sugarcane crops. Proc. Int. Soc. Sugar Cane Technol. 2013, 28. 11 pp.
35. Thorburn P.J., Biggs J.S., Probert M.E., Keating B.A. Opportunities for and potential consequences of reducing nitrous oxide emissions from sugarcane crops. Proc. Int. Soc. Sugar Cane Technol. 2010, 27. 9 pp.
36. Turral H., Burke J., Faurès J.-M. Climate Change, Water and Food Security 2011, FAO Water Reports 36, Food and Agriculture Organization of the United Nations, Rome.
37. Varella H., Guérif M., Buis S. Global sensitivity analysis measures the quality of parameter estimation: the case of soil parameters and a crop model. Environ. Model. Softw. 2010, 25:310-319.
38. Wallach D., Goffinet B., Bergez J.E., Debaeke P., Leenhardt D., Aubertot J.-N. Parameter estimation for crop models: a new approach and application to a corn model. Agron. J. 2001, 93:757-766.
39. Wallach D., Buis S., Lecharpentier P., Bourges J., Clastre P., Launay M., Bergez J.-E., Guerif M., Soudais J., Justes E. Apackage of parameter estimation methods and implementation for the STICS crop-soil model. Environ. Model. Softw. 2011, 26:386-394.
40. Wallach D., Keussayan N., Brun F., Lacroix B., Bergez J.-E. Assessing the uncertainty when using a model to compare irrigation strategies. Agron. J. 2012, 104:1274-1283.
41. Warmink J.J., Janssen J.A.E.B., Booij M.J., Krol M.S. Identification and classification of uncertainties in the application of environmental models. Environ. Model. Softw. 2010, 25:1518-1527.
42. White J.W., Hoogenboom G., Kimball B.A., Wall G.W. Methodologies for simulating impacts of climate change on crop production. Field Crops Res. 2011, 124:357-368.