Abstract
Maize is the dominant irrigated crop in Kansas. In recent years, as a result of declining groundwater levels in the Ogallala aquifer and diminished well capacities, farmers are turning to deficit irrigation strategies. This study demonstrates the potential of model-based optimization for determining adequate soil water depletion levels. CERES-Maize was used as surrogate crop, while the AquaCrop model was used in an optimization procedure that determined the optimal water depletion levels. A multi-objective optimization framework was used to determine several combinations of optimal water depletion levels based on ten years of historical weather, and these combinations were tested using an additional 50 years of historical weather. The results show that, although imperfect modeling and weather fluctuations caused the actual yield to be different from the target yield, the fluctuations around the multi-year averages were not significantly larger when testing the irrigation schedule with the CERES-Maize model than when testing it with the AquaCrop model that had been used to develop the irrigation schedule.
Original language | English |
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Pages (from-to) | 2011-2022 |
Number of pages | 12 |
Journal | Transactions of the ASABE |
Volume | 60 |
Issue number | 6 |
DOIs | |
State | Published - 2017 |
Keywords
- AquaCrop
- CERES-Maize
- Center-pivot irrigation
- Multi-objective optimization
All Science Journal Classification (ASJC) codes
- Forestry
- Food Science
- Agronomy and Crop Science
- Soil Science
- Biomedical Engineering