A dynamic knowledge model for water management in maize

Abstract

Farmland irrigation management and model establishment are always core and difficult contents in crop simulation. This research was focused on exerting the establishment theory of knowledge model, and applying the systematic analysis method and mathematic modeling technology to knowledge expression system of maize water management. Based on soil water balance, a dynamic knowledge model with systematic and wide-application characteristics for maize water management was developed, after periodically quantifying the relationship of irrigation ration between cultivars  characteristics and environmental factors. Cases were studied on the knowledge model with the data sets of normal year in different eco-sites and those of different rain years in the same eco-sites. The results showed that there was no difference in water saving in normal years under different eco-sites, irrigation schedule changes with eco-sites greatly; but a more obvious difference in different rain years of the same eco-sites existing, with 8.6% and 31.9% of water saving in both more rainfall and normal rainfall years, respectively. Additionally, irrigation in the seedling stage did not change with year types, but it did in Knurling and filling stages. This can be concluded that the irrigation regime designed by the model is well coherent to the actual planting system, which indicated that the model had good decision-making and applicability.