Soil properties estimation by inversion of a crop model and observations on crops improves the prediction of agro-environmental variables

European Journal of Agronomy

Volumn 33, Issue 2, 2010, Pages 139-147

  Varella, Hubert ^a   Guérif, Martine ^a   Buis, Samuel ^a   Beaudoin, Nicolas ^b  

^a UAPV   (France)

^b Inst Natl de la Rech Agronomique   (France)

Author keywords

Bayesian estimation; Dynamic crop model STICS; Importance Sampling; Prediction of agro environmental variables; Soil parameters

Indexed keywords

AGRICULTURAL MODELING; AGROECOLOGY; BAYESIAN ANALYSIS; CROP PRODUCTION; CROP YIELD; DATA SET; ESTIMATION METHOD; SAMPLING; SOIL DEPTH; SOIL WATER; SUGAR BEET; WATER CONTENT; WATER STRESS; WHEAT;

BETA VULGARIS SUBSP. VULGARIS; TRITICUM AESTIVUM;

EID: 77955587893     PISSN: 11610301     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eja.2010.04.005     Document Type: Article

References (38)

1. Baret F., Houlès V., Guérif M. Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management. Symposium on Imaging Techniques for Understanding Plant Reponses to Stress held at the Society for Experimental Biology Meeting 2006, 869-880.
2. Bastet G., Bruand A., Quétin P., Cousin I. Estimation des propriétés de rétention en eau des sols à l'aide de fonctions de pédotransfert (FTP): Une analyse bibliographique. Etude et Gestion des Sols 1998, 5:7-28.
3. Beaudoin N., Launay M., Sauboua E., Ponsardin G., Mary B. Evaluation of the soil crop model STICS over 8 years against the " on farm" database of Bruyeres catchment. European Journal of Agronomy 2008, 29:46-57.
4. Blackmore S., Moore M. Remedial correction of yield map data. Precision Agriculture 1999, 1:53-56.
5. Bourennane H., King D., Couturier A., Nicoullaud B., Mary B., Richard G. Uncertainty assessment of soil water content spatial patterns using geostatistical simulations: An empirical comparison of a simulation accounting for single attribute and a simulation accounting for secondary information. Ecological Modelling 2007, 205:323-335.
6. Braga R.P., Jones J.W. Using optimization to estimate soil inputs of crop models for use in site-specific management. Transactions of the ASAE 2004, 47:1821-1831.
7. Brisson N., Ruget F., Gate P., Lorgeou J., Nicoullaud B., Tayot X., Plenet D., Jeuffroy M.H., Bouthier A., Ripoche D., Mary B., Juste E. STICS: a generic model for simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize. Agronomie 2002, 22:69-92.
8. Calmon M.A., Jones J.W., Shinde D., Specht J.E. Estimating parameters for soil water balance model using adaptative simulated annealing. Applied Engineering in Agriculture 1999, 15:703-7013.
9. Debaeke P. Scenario analysis for cereal management in water-limited conditions by the means of a crop simulation model (STICS). Agronomie 2004, 24:315-326.
10. Ferreyra R.A., Jones J.W., Graham W.D. Parameterizing spatial crop models with inverse modeling: sources of error and unexpected results. Transactions of the ASABE 2006, 49:1547-1561.
11. Flénet F., Villon P., Ruget F.O. Methodology of adaptation of the STICS model to a new crop: spring linseed (Linum usitatissimum, L.). STICS Workshop 2003, 367-381.
12. Gabrielle B., Roche R., Angas P., Cantero-Martinez C., Cosentino L., Mantineo M., Langensiepen M., Henault C., Laville P., Nicoullaud B., Gosse G. A priori parameterisation of the CERES soil-crop models and tests against several European data sets. Agronomie 2002, 22:119-132.
13. Gaucherel C., Campillo F., Misson L., Guiot J., Boreux J.-J. Parameterization of a process-based tree-growth model: comparison of optimization. MCMC and Particle Filering algorithms. Environmental Modelling & Software 2008, 23:1280-1288.
14. Gras, R., Erhwein, J., Hermant, G., Hebert, J., 1961. Carte des sols du département de l'Aisne. Laon n 5-6, Chambre d'agriculture de l'Aine.
15. Guérif M., Beaudoin N., Durr C., Machet J.M., Mary B., Michot D., Moulin D., Nicoullaud B., Richard G. Designing a field experiment for assessing soil and crop spatial variability and defining site specific management strategies. Proceedings 3rd European Conference on Precision Agriculture 2001, 677-682.
16. Guérif M., Houlès V., Makowski D., Lauvernet C. Data assimilation and parameter estimation for precision agriculture using the crop model STICS. Working with Dynamic Crop Models, 2006, 395-401. Elsevier. D. Wallach, D. Makowski, J.W. Jones (Eds.).
17. Houborg R., Boegh E. Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data. Remote Sensing of Environment 2008, 112:186-202.
18. Houlès V., Mary B., Guérif M., Makowski D., Justes E. Evaluation of the crop model STICS to recommend nitrogen fertilization rates according to agro-environmental criteria. Agronomie 2004, 24:1-9.
19. Irmak A., Jones J.W., Batchelor W.D., Paz J.O. Estimating spatially variable soil properties for application of crop models in precision farming. Transactions of the ASAE 2001, 44:1343-1353.
20. King D., Daroussin J., Tavernier R. Development of a soil geographic database from the soil map of the European communities. Catena 1994, 21:37-56.
21. Lagacherie P., Baret F., Feret J.B., Netto J.M., Robbez-Masson J.M. Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements. Remote Sensing of Environment 2008, 112:825-835.
22. Launay M., Guérif M. Ability for a model to predict crop production variability at the regional scale: an evaluation for sugar beet. Agronomie 2003, 23:135-146.
23. Launay M., Graux A.-I., Brisson N., Guérif M. Carbohydrate remobilization from storage root to leaves after a stress release in sugar beet (Beta vulgaris L.): experimental and modelling approach. Journal of Agricultural Science 2009, 147:669-682.
24. Lawless C., Semenov M.A., Jamieson P.D. Quantifying the effect of uncertainty in soil moisture characteristics on plant growth using a crop simulation model. Field Crops Research 2008, 106:138-147.
25. Liu J.S. Monte Carlo Strategies in Scientific Computing 2001, Springer, New York.
26. Machet J.M., Couturier A., Beaudoin N. Cartographie du rendement du blé et des caractéristiques qualitatives des grains. Agriculture de précision 2007, 131-144. Quae, Versailles. M. Guérif, D. King (Eds.).
27. Makowski D., Wallach D., Tremblay M. Using a Bayesian approach to parameter estimation; comparison of the GLUE and MCMC methods. Agronomie 2002, 22:191-203.
28. Makowski D., Hillier J., Wallach D., Andrieu B., Jeuffroy M.-H. Parameter estimation for crop models. Working with Dynamic Crop Models 2006, vol. 101:151. Elsevier.
29. Miller A. Subset Selection in Regression 2002, Chapman & Hall.
30. Moulin S., Zurita R.M., Guérif M. Estimation de variables biophysiques du couvert par ajustement de modèles de transfert radiatif sur des réflectances. Agriculture de précision 2007, 97-113. Quae, Versailles. M. Guérif, D. King (Eds.).
31. Murphy B., Geeves G., Miller M., Summerell G., Southwell P., Rankin M. The application of pedotransfer functions with existing soil maps to predict soil hydraulic properties for catchment-scale hydrologic and salinity modelling. International Congress on Modelling and Simulation 2003, 502-507.
32. Pachepsky Y., Acock B. Stochastic imaging of soil parameters to assess variability and uncertainty of crop yield estimates. Geoderma 1997, 85:213-229.
33. Robert C.P., Casella G. Monte Carlo Statistical Methods 2004, Springer, New York.
34. Timlin D., Pachepsky Y., Walthall C., Loechel S. The use of a water budget model and yield maps to characterize water availability in a landscape. Soil & Tillage Research 2001, 58:219-231.
35. Tremblay M., Wallach D. Comparison of parameter estimation methods for crop models. Agronomie 2004, 24:351-365.
36. Varella H., Guérif M., Buis S. Global sensitivity analysis (GSA) measures the quality of parameter estimation: the case of soil parameters and a crop model. Environmental Modelling & Software 2010, 25:310-319.
37. Varella, H., 2009. Inversion d'un modèle de culture pour estimer spatialement les propriétés des sols et améliorer la prédiction de variables agro-environnementales. PhD thesis, Université d'Avignon, 205
38. Weiss M., Baret F. Evaluation of canopy biophysical variable retrieval performances from the accumulation of large swath satellite data. Remote Sensing of Environment 1999, 70:293-306.