Using Crop Simulation Models and GIS for Regional Productivity Analysis

The scope of applicability of site-specific models can be extended to regional planning and productivity analysis by combining their capabilities with a Geographic Information System (GIS). In this study, regional productivity analyses for three sites in western Puerto Rico were carried out using the DSSAT-BEANGRO V1.01, the dry bean (Phaseolus vulgaris L.) model and AEGIS. DSSAT is an integrated decision support system that contains several crop models with standardized input and output. AEGIS is a regional planning decision support system that uses DSSAT capabilities within a GIS for regional productivity analysis. The analysis indicated that a considerable soil and weather variability exists within the three study sites. The optimum management factors such as cultivar selection, planting date and irrigation strategy would significantly differ from one site to another. For the Mayaguez and Isabela areas, the long season cultivar Porrillo Sintetico would always be a better choice. It would consistently out perform the short season cultivar Cuarentena. On the other hand, in the semiarid environment of Magueyes, Porrillo Sintetico would perform better than Cuarentena in good rainfall years, and the reverse would happen in bad rainfall years. However, in the long run, Porrillo Sintetico would out yield, Cuarentena by 20% even in this area. The simulated best planting dates for rainfed condition matched fairly well with the recommended best dates for two study sites. However, for the third site (Mayaguez), these dates varied considerably for both rainfed and irrigated conditions. The cumulative probability distribution analysis for these dates showed that the simulated best dates would produce higher yields for all simulated years. The environmental diversity (soil and weather) of the study sites makes the results of this study indicative of several other locations in the Caribbean basin and other tropical regions of the world.