Abstract
Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model performance was promising, as it was executed unaided by measurements of soil water content throughout the season. VRI prescriptions did not correlate well with available water capacity (R2 < 0.4); however, they correlated better with modeled ET in 2018 (R2 = 0. 69, VRI-Full; R2 = 0.55, VRI-Deficit). No significant differences were observed in total intended gross irrigation depth in 2017 (VRI-Full = 351 mm, Uniform Full = 344). However, in 2018, VRI resulted in lower mean prescribed gross irrigation than the corresponding uniform treatments (VRI-Full = 265 mm, Uniform Full = 282 mm, VRI-Deficit = 234 mm, and Uniform Deficit = 267 mm). Notwithstanding the differences in prescribed irrigation (in 2018), VRI did not affect dry grain yield, with no statistically significant differences being found between any treatments in either year (F = 0.03, p = 0.87 in 2017; F = 0.00, p = 0.96 for VRI/Uniform and F = 0.01, p = 0.93 for Full/Deficit in 2018). Likewise, any reduction in irrigation application apparently did not result in detectable reductions in deep percolation potential or actual evapotranspiration. Additional research is needed to further vet the model as a deficit irrigation management tool. Suggested model improvements include a continuous function for water stress and an optimization routine in computing the basal crop coefficient.
Highlights
The smallest practical management scale for center pivot irrigation has been the field scale
Model performance was improved in 2018 soybean with modeled θp for the top 1-m having a mean bias error (MBE) < 0.01 m3 m−3 and an root mean squared error (RMSE) ≈ 0.02 m3 m−3. These results represent an improvement over results in the same field in 2017. These results indicate that the water balance model in Spatial EvapoTranspiration Modeling Interface (SETMI) is suitable for irrigation management under these conditions without the periodic incorporation of secondary datasets as was done in 2017
The results support the conclusion that, under our study conditions, Variable rate irrigation (VRI) managed with SETMI resulted in a relatively small, nominal reduction in water withdrawn in 2018 as compared to uniform treatments; no difference was observed in 2017
Summary
The smallest practical management scale for center pivot irrigation has been the field scale. Irrigation applications are typically intended or assumed to be spatially uniform throughout a field. Variable rate irrigation (VRI) technology for center pivots allows for the management scale to be much smaller and application rates to vary within a VRI equipped field. In western Nebraska and other areas of the High Plains, irrigation water withdrawal may be limited in availability, or limited by regulation. In some of these areas (and other areas globally), significant soil variability exists, further complicating irrigation management. One reason that VRI may be of interest in deficit irrigation management is that it may allow for a more spatially uniform managed level of water stress, by accounting for soil, and other variability
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