Agriculture, Ecosystems and Environment 81 (2000) 5–16 A spatial approach using imprecise soil data for modelling crop yields over vast areas Philippe Lagacherie a,∗ , Durk R. Cazemier a , Roger Martin-Clouaire b , Tom Wassenaar a a INRA Science du Sol, 2 Place Pierre Viala, 34060 Montpellier Cedex, France b INRA, Biométrie et Intelligence Artificielle, BP27, 31326 Castanet-Tolosan Cedex, France Received 25 August 1999; received in revised form 10 December 1999; accepted 28 February 2000 Abstract Estimations of crop yields using process-based crop models are area-limited because quantitative soil data are unavailable over vast areas. The spatial approach proposed in this study incorporates two novel aspects concerning the derivation of soil data feeding the simulation and the modelling of the crop production process. First, the soil parameters required for crop modelling as well as their imprecision were estimated from the qualitative information of a 1:250,000 scale regional soil database by a possibility theory approach, which combines a set of GIS procedures and a constraint satisfaction solver. Second, the initial process-based crop model was made less complex by deriving simple agrotransfer functions from simulations at representative sites located in the studied region. The resulting system estimated the yield expressed as possibility distributions over the region which can be visualised through decision maps. The proposed spatial approach was tested on a hard wheat yield (Triticum durum spp.) estimation in the Hérault-Orb-Libron valley region (Languedoc, France). It proved to provide realistic yet imprecise estimates compared with those obtained for a set of site-crop estimates. The spatial approach allowed the identification of areas in which soil data needed to be improved for obtaining both reliable and informative estimates. These results demonstrated the potential usefulness of the proposed approach for providing reliable soil information for decision making at the regional level. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Soil map; Available water capacity; Regional scale; Crop model; Imprecision; Possibility theory; Constraint satisfaction problem; GIS 1. Introduction Computer simulations of soil water regimes and crop growth are powerful means for quantifying the effects of changing climate conditions or agricultural practices. However, these simulations require a large amount of quantitative soil data which limits their spa- tial application to areas where a dense spatial sampling ∗ Corresponding author. Tel.: +33-4-99-61-25-78; fax: +33-4-67-63-26-14. can be undertaken. A spatial approach is needed for extending the simulations to vast areas such as Euro- pean regions. The common practice for doing this consists in linking crop models to quantitative information pro- vided by soil maps and soil databases (Dumanski et al., 1993; Smaling and Fresco, 1993; Akinremi et al., 1997; Bornand et al., 1998). This type of informa- tion consists in measured soil data from detailed soil profile observations that are assumed to be represen- tative for the delineated mapping units. Crop yield 0167-8809/00/$ – see front matter © 2000 Elsevier Science B.V. All rights reserved. PII:S0167-8809(00)00164-X