ABSTRACT

The GOSSYM cotton (Gossypium hirsutum L.) simulation model has been utilized as a research and management tool across the U.S. cotton belt for the past eight years. Although originally developed for use in the humid Mississippi river valley, its success has led to its use in more arid areas of the U.S. cotton belt. Producers and researchers in these areas, motivated by the need to limit water consumption, have adopted management practices such as alternate furrow irrigation, fertigation, or, in rain-fed situations, 2:1 skip-row planting. They have, consequently, expressed a need that GOSSYM be able to simulate situations where agronomic inputs are either applied asymmetrically about the crop row, as is the case with alternate furrow irrigation, fertigation, and side-dressing of fertilizer, or where the plant itself is located asymmetrically in the simulated soil slab, as would be the case in implementation of a 2:1 skip-row planting scheme. The GOSSYM model has been re-coded to allow independent simulation of furrows to the left and to the right of the crop row. Tests to determine the amended model's ability to duplicate output of the standard model, given symmetrical input, have shown both models to compare favorably in the simulation of soil water movement and Nitrogen fertilizer transport. Simulation of root growth in the amended model suffers from some numerical instability resulting from small value round-off errors in the numerous calculations required for simulation of the entire soil slab. This results in asymmetry in simulated root growth about the crop row, despite symmetrical application of agronomic inputs. Given asymmetric input, the amended model ably simulated 2:1 skip-row planting patterns and alternate furrow irrigation, both, with side-dressed nitrogen fertilizer, and fertigation. As has been the case with all GOSSYM upgrades, this amended model will not be officially released until it has been appropriately tested and validated. Beta testing of the model should be complete by the end of the 1993 growing season. The authors are hopeful that the increase in applicability will result in more widespread utilization of the model.