Author
Listed:
- Singh, Anmol
- Taghvaeian, Saleh
- Ge, Yufeng
- Heeren, Derek
- Bai, Frank
Abstract
Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) for two dominant soils in eastern Nebraska under three irrigation levels (rainfed, deficit irrigation, and full irrigation). The largest average simulated yields were obtained under full irrigation and had similar ranges of 3.93–4.51 Mg ha⁻¹ for both soils, with an average yield of 4.22 Mg ha−1. The rainfed treatment had the lowest yields with a mean of 3.6 Mg ha−1, especially during dry years and for the coarser-texture soil. Across all 15 years, the implemented deficit irrigation approach resulted in water application reductions of zero to 100% (0–135 mm) compared to the full irrigation treatment, while yield reductions were always less than 11%. The results indicate that the deficit irrigation implemented here has the potential to conserve water without significantly reducing soybean yield in years with average and above precipitation amounts. AquaCrop is a valuable tool for evaluating various soybean irrigation strategies in eastern Nebraska.
Suggested Citation
Singh, Anmol & Taghvaeian, Saleh & Ge, Yufeng & Heeren, Derek & Bai, Frank, 2026.
"Assessment of soybean response to irrigation variability in eastern Nebraska using the AquaCrop model,"
Agricultural Water Management, Elsevier, vol. 330(C).
Handle:
RePEc:eee:agiwat:v:330:y:2026:i:c:s0378377426002489
DOI: 10.1016/j.agwat.2026.110367
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