Integrating spatial soil organization data with a regional agricultural management simulation model : a case study in northern Tunisia

Cropping system models are typically used to simulate crop growth and development at the field scale. Spatial extension of the results to larger scales needs spatially referenced databases using Geographic Information Systems (GIS). However, GIS generally lack accuracy and pertinence in the soil characteristics and delineations that are required for this purpose. In addition, most soil parameters used in the soil-water models are empirical and are estimated without any reference to soil structure, making it difficult to characterize the hydrostructural functionality of spatial soil mapping units in the GIS. The objective of this article is to present an application of a new approach in soil physics for coupling a soil information (mapping and characterization) system based on the soil organization with an agronomic model, CropSyst, to be used for soil and water management purposes. Accordingly, a GIS based on a map of hierarchical natural units in the irrigated area of Cebalat (northern Tunisia) was used to build a geo-referenced soil information system for the study area. Additional information from the existing GIS of the zone was overlaid to produce "agronomic units," which result from the spatial superposition of the soil information system, farm map units, and land use. The inputs for the model were different sets of soil, crop, and crop management parameters. Simulations were conducted at the field scale for testing the ability of CropSyst to simulate yield, soil water dynamics, soil salinity, nitrogen leached, and at the regional level, yield. At the field scale, the model accurately, without calibration of soil properties, simulated the soil water content and salinity (RRMSE less than 10%). Simulated soil nitrate concentration was not close to observed values (RRMSE of 54%), but the latter were also associated with large variability. At the regional scale, the model offered an overall good integrated performance in simulating yield in the area under evaluation. For rainfed crops, the regression line between simulated and observed yield was close to 1:1; however, the model slightly underestimated simulated yield for the irrigated crops