Sensitivity analysis and calibration of CN-SIM to simulate the mineralisation of liquid dairy manures

Soil Biology and Biochemistry

Volumn 43, Issue 6, 2011, Pages 1207-1219

  Cavalli, Daniele ^a   Bechini, Luca ^a  

^a UNIVERSITY OF MILAN   (Italy)

Author keywords

Carbon; Manure; Model calibration; Nitrogen; Sensitivity analysis; Simulation model

Indexed keywords

ANIMAL MANURE; C AND N DYNAMICS; CARBON AND NITROGEN; DAIRY MANURES; DOWNHILL SIMPLEX METHOD; DYNAMIC SIMULATION MODELS; EXPERIMENTAL DATA; HETEROGENEOUS MATERIALS; IMMOBILISATION; LONG TERM SIMULATION; MICROBIAL BIOMASS; MINERALISATION; MODEL CALIBRATION; MODEL PARAMETERS; OPTIMISATIONS; PARAMETER OPTIMISATION; REMINERALISATION; SCIENTIFIC KNOWLEDGE; SIMULATION MODEL; SOIL MINERAL NITROGEN; SOIL ORGANIC MATTERS; SOIL PARAMETERS;

AMMONIUM COMPOUNDS; CALIBRATION; FERTILIZERS; GEOLOGIC MODELS; LAKES; LIQUIDS; MANURES; NITROGEN; OPTIMIZATION; SENSITIVITY ANALYSIS; SOILS;

COMPUTER SIMULATION;

BIOMASS; CALIBRATION; DECOMPOSITION; MANURE; MICROBIAL COMMUNITY; NUMERICAL MODEL; OPTIMIZATION; REMINERALIZATION; SENSITIVITY ANALYSIS; SOIL NITROGEN; SOIL ORGANIC MATTER;

ANIMALIA;

EID: 79954580532     PISSN: 00380717     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.soilbio.2011.02.010     Document Type: Article

References (36)

1. Acutis M., Confalonieri R. Optimization algorithms for calibrating cropping systems simulation models. A case study with simplex-derived methods integrated in the WARM simulation environment. Ital. J. Agromet. 2006, 11:26-34.
2. Bechini L., Marino P. Short-term nitrogen fertilizing value of liquid dairy manures is mainly due to ammonium. Soil Sci. Soc. Am. J. 2009, 73:2159-2169.
3. Bellocchi G., Rivington M., Donatelli M., Matthews K. Validation of biophysical models: issues and methodologies. A review. Agron. Sustain. Dev. 2009, 30:109-130.
4. Calderon F.J., McCarty G.W., Van Kessel J.A.S., Reeves J.B. Carbon and nitrogen dynamics during incubation of manured soil. Soil Sci. Soc. Am. J. 2004, 68:1592-1599.
5. Campolongo F., Cariboni J., Saltelli A. An effective screening design for sensitivity analysis of large models. Environ. Modell. Softw. 2007, 22:1509-1518.
6. Cariboni J., Gatelli D., Liska R., Saltelli A. The role of sensitivity analysis in ecological modelling. Ecol. Model. 2007, 203:167-182.
7. Causarano H.J., Shaw J.N., Franzluebbers A.J., Reeves D.W., Raper R.L., Balkcom K.S., Norfleet M.L., Izaurralde R.C. Simulating field-scale soil organic carbon dynamics using EPIC. Soil Sci. Soc. Am. J. 2007, 71:1174-1185.
8. Chan K., Saltelli A., Tarantola S. Sensitivity analysis of model output: variance-based methods make the difference. In the Proceedings of the 1997 Winter Simulation Conference. Atlanta, Georgia, United States 1997, 261-268. S. Andradottir, K.J. Healy, H. Withers, B.L. Nelson (Eds.).
9. 15N. Soil Sci. Soc. Am. J. 2004, 68:637-643.
10. 2O emission from grasslands. Biogeochemistry 2005, 76:395-419.
11. Confalonieri R. Monte Carlo based sensitivity analysis of two crop simulators and considerations on model balance. Eur. J. Agron. 2010, 33:89-93.
12. Heinen M. Simplified denitrification models: overview and properties. Geoderma 2006, 133:444-463.
13. Homma T., Saltelli A. Importance measures in global sensitivity analysis of model output. Reliab. Eng. Syst. Safe 1996, 52:1-17.
14. Loague K., Green R.E. Statistical and graphical methods for evaluating solute transport models: overview and application. J. Contam. Hydrol. 1991, 7:51-73.
15. Maes F., Vandermeulen D., Suetens P. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information. Med. Image Anal. 1999, 3:373-386.
16. Manzoni S., Porporato A. Soil carbon and nitrogen mineralization: theory and models across scales. Soil Biol. Biochem. 2009, 41:1355-1379.
17. Marino P., De Ferrari G., Bechini L. Description of a sample of liquid dairy manures and relationship between analytical variables. Biosyst. Eng. 2008, 100:256-265.
18. Masse D., Cambier C., Brauman A., Sall S., Assigbetse K., Chotte J. MIOR: an individual-based model for simulating the spatial patterns of soil organic matter microbial decomposition. Eur. J. Soil Sci. 2007, 58:1127-1135.
19. Morris M.D. Factorial sampling plans for preliminary computational experiments. Technometrics 1991, 33:161-174.
20. National Statistical Institute Fifth agricultural census. Farm structure (in Italian) 2000, Available at: http://www.census.istat.it/censimenti/agricoltura/fascicolo_Italia_ediz_2_finale.pdf (verified 02-03-2011), ISTAT, Rome, Italy.
21. National Statistical Institute Farm structure and production, 2007 (in Italian) 2008, Available at: http://www.istat.it/salastampa/comunicati/non_calendario/20081203_00/testointegrale20081203.pdf (verified 02-03-2011), ISTAT, Rome, Italy.
22. Nelder J.A., Mead R. A simplex method for function minimization. Computer J. 1965, 7:308-313.
23. Petersen B.M., Berntsen S., Hansen S., Jensen L.S. CN-SIM-a model for the turnover of soil organic matter. I. Long-term carbon and radiocarbon development. Soil Biol. Biochem. 2005, 37:359-374.
24. Petersen B.M., Jensen L.S., Hansen S., Pedersen A., Henriksen T.M., Sørensen P., Trinsoutrot-Gattin I., Berntsen S. CN-SIM: a model for the turnover of soil organic matter. II. Short-term carbon and nitrogen development. Soil Biol. Biochem. 2005, 37:375-393.
25. Probert M.E., Delve R.J., Kimani S.K., Dimes J.P. Modelling nitrogen mineralization from manures: representing quality aspects by varying C: N ratio of sub-pools. Soil Biol. Biochem. 2005, 37:279-287.
26. Richter G., Acutis M., Trevisiol P., Latiri K., Confalonieri R. Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. Eur. J. Agron. 2010, 32:127-136.
27. Saltelli A. Sensitivity analysis for importance assessment. Risk Anal. 2002, 22:579-590.
28. Saltelli A., Tarantola S., Campolongo F., Ratto M. Sensitivity Analysis in Practice. A Guide to Assessing Scientific Models 2004, John Wiley & Sons.
29. SIMLAB Version 2.2. Simulation Environment for Uncertainty and Sensitivity Analysis 2004, Software Developed by the Joint Research Centre of the European Commission, Varese, Italy. http://simlab.jrc.ec.europa.eu/.
30. Sobol' I.M. Sensitivity estimates for nonlinear mathematical models. Math. Model. Comput. Exp. 1993, 1:407-414.
31. Sobol' I.M., Kucherenko S.S. Global sensitivity indices for nonlinear mathematical models. Wilmott Magazine 2005, 2:2-7. Review.
32. Sørensen P. Effects of storage time and straw content of cattle slurry on the mineralization of nitrogen and carbon in soil. Biol. Fert. Soils 1998, 27:85-91.
33. Sørensen P. Carbon mineralization, nitrogen immobilization and pH change in soil after adding volatile fatty acids. Eur. J. Soil Sci. 1998, 49:457-462.
34. Sørensen P. Immobilisation, remineralisation and residual effects in subsequent crops of dairy cattle slurry nitrogen compared to mineral fertiliser nitrogen. Plant Soil 2004, 267:285-296.
35. Thomsen I.K., Olesen J.E. C and N mineralization of composted and anaerobically stored ruminant manure in differently textured soils. J. Agric. Sci. Camb. 2000, 135:151-159.
36. Van Kessel J.S., Reeves J.B., Meisinger J.J. Nitrogen and carbon mineralisation of potential manure compounds. J. Environ. Qual. 2000, 29:1669-1677.