ANALYSIS OF WATER-STRESS EFFECTS CAUSING SPATIAL YIELD VARIABILITY INSOYBEANS

Soybean yields have been shown to be highly variable across fields. Pa st efforts to correlate yield in small sections of fields to soil type , elevation, fertility, and other factors in an attempt to characteriz e yield variability has Clad limited success. In this article, we demo nstrate how a process oriented crop growth model (CROPGRO-Soybean) can be used to characterize spatial yield variability of soybeans, and to test hypotheses related to causes of yield variability In this case, the model was used to test the hypothesis that variability in water st ress corresponds well with final soybean yield variability within a fi eld. Soil parameters in the model related to rooting depth and hydraul ic conductivity were calibrated in each of 224 grids in a 16-ha field in Iowa using three years of yield data. In the best case, water stres s explained 69% of the variability in yield for all grids over three y ears. The root mean square error was 286 kg ha(-1) representing approx imately 12% of the three-year mean measured yield. Results could furth er be improved by including factors that were not measured, such as pl ant population, disease, and accurate computation of surface water run on into grids. Results of this research show that it is important to include measurements of soil moisture holding capacity, and drainage c haracteristics, as well as root depth as data layers that should be co nsidered in arty data collection effort.