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内布拉斯加州中西部地区在充分灌溉和亏缺灌溉条件下玉米和大豆的可变灌溉率

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska Under Full and Deficit Irrigation.

作者信息

Barker J Burdette, Bhatti Sandeep, Heeren Derek M, Neale Christopher M U, Rudnick Daran R

机构信息

Natural Resources Consulting Engineers, Fort Collins, CO, United States.

Biological Systems Engineering Department, University of Nebraska-Lincoln, Lincoln, NE, United States.

出版信息

Front Big Data. 2019 Sep 24;2:34. doi: 10.3389/fdata.2019.00034. eCollection 2019.

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 ( < 0.4); however, they correlated better with modeled ET in 2018 ( = 0. 69, VRI-Full; = 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 ( = 0.03, = 0.87 in 2017; = 0.00, = 0.96 for VRI/Uniform and = 0.01, = 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.

摘要

变量灌溉(VRI)可改善中心支轴式灌溉管理,包括亏缺灌溉。利用陆地卫星图像实现了基于遥感的蒸散模型,以管理位于内布拉斯加州中西部的一块配备VRI的中心支轴式灌溉农田的灌溉,该农田在2017年种植玉米,2018年种植大豆。2017年,该研究包括使用该模型的VRI以及使用中子衰减进行充分灌溉且无预期水分胁迫的均匀灌溉(分别为VRI - 充分灌溉和均匀 - 充分灌溉处理)。2018年,增加了两种亏缺灌溉处理(分别为VRI - 亏缺灌溉和均匀 - 亏缺灌溉),并对模型进行了修改,试图减少水平衡漂移;模型性能很有前景,因为整个季节它在没有土壤含水量测量辅助的情况下运行。VRI处方与有效持水量的相关性不佳(<0.4);然而,它们在2018年与模拟的ET相关性更好(VRI - 充分灌溉时r = 0.69;VRI - 亏缺灌溉时r = 0.55)。2017年在总预期毛灌溉深度方面未观察到显著差异(VRI - 充分灌溉 = 351毫米,均匀充分灌溉 = 344毫米)。然而,在2018年,VRI导致规定的平均毛灌溉量低于相应的均匀处理(VRI - 充分灌溉 = 265毫米,均匀充分灌溉 = 282毫米,VRI - 亏缺灌溉 = 234毫米,均匀亏缺灌溉 = 267毫米)。尽管规定灌溉量存在差异(2018年),但VRI并未影响干粒产量,在任何一年的任何处理之间均未发现统计学上的显著差异(2017年p = 0.03,F = 0.87;2018年VRI/均匀处理时p = 0.00,F = 0.96,充分灌溉/亏缺灌溉时p = 0.01,F = 0.93)。同样,灌溉量的任何减少显然并未导致深层渗漏潜力或实际蒸散量的可检测减少。需要进一步开展研究,以进一步验证该模型作为亏缺灌溉管理工具的有效性。建议的模型改进包括水分胁迫的连续函数以及计算作物基础系数的优化程序。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c03/7931860/eec6660a4d3a/fdata-02-00034-g0001.jpg

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