Comparison of Wheat Yield Simulated Using Three N Cycling Options in the SWAT Model
- 1 Texas AgriLife Research and Extension Center, Texas A & M University, Temple, USA
- 2 USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, USA
- 3 USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, USA
- 4 USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, USA
Abstract
The Soil and Water Assessment Tool (SWAT) model has been successfully used to predict alterations in streamflow, evapotranspiration and soil water; however, it is not clear how effective or accurate SWAT is at predicting crop growth. Previous research suggests that while the hydrologic balance in each watershed is accurately simulated with SWAT, the SWAT model over or under predicts crop yield relative to fertilizer inputs. The SWAT model now has three alternative N simulation options: 1) SWAT model with an added flush of N (SWAT-flush); 2) N routines derived from the CENTURY model (SWAT-C); and 3) a one-pool C and N model (SWAT-One). The objective of this study was to evaluate the performance of SWAT-flush, SWAT-C, and SWAT-One as they affect wheat yield prediction. Simulated yields were compared to wheat yields in a 28-year fertilizer/wheat yield study in Lahoma, OK. Simulated yields were correlated with actual 28-year mean yield; however, none of the available N cycling models predicted yearly yields. SWAT-C simulated average yields were closer than other N sub-models to average actual yield. Annually there was a stronger correlation between SWAT-flush and actual yields than the other submodels. However, none of the N-cycling routines were able to accurately predict annual variability in yield at any fertilizer rate. We found that SWAT-C or SWAT-flush are the most viable choices for accurately simulating long-term average wheat yields although annual variations in yield prediction should be taken into consideration. Further research is needed to determine the effectiveness of SWAT-C and SWAT-flush in determining average and annual yield in various farming regions and with numerous agronomic crops.
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