SBIR Phase I: Orchard Transpiration Irrigation

这个小型企业创新研究(SBIR)第一阶段项目的更广泛的影响/商业潜力是改善农业作业中的用水。由于缺乏自然降雨和地下水位枯竭，水资源日益匮乏，维护农业水井和农业生产的必要性非常大。拟议的地下灌溉技术将比滴灌减少50%的灌溉用水量。这可以大大减少用水量，使地下水位得以恢复，并在干旱年份作为蓄水池发挥作用。它可能会提高农场产量，改善有机农民的杂草控制，并促进更好地吸收化肥--从而将地下含水层的污染降至最低。建议的技术还可以降低能源成本，并提高调度电力使用的灵活性。在系统层面上，它为有弹性和可持续的灌溉提供了一个新的范例。拟议的研究重点是开发一种易于使用的湿度羽流模拟计算器，使农民能够自我分析他们的土壤类型在安装虚拟地下水位灌溉系统时会如何反应。后者旨在消除地表蒸发和深层渗流造成的水分损失。所采取的研究方法是一种跨学科合作，以足够准确的有效方式对液体如何从地下给水管道通过渗透土壤传输到植物根部的物理模型进行数学建模。这些预测将与更全面的行业标准水文模型预测进行比较，也将与从野外实验收集的湿度数据进行比较。技术风险在于确定非科学家农民收集的基本土壤属性是否足以作为输入，以生成对许多土壤类型的水分羽流剖面的准确预测。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the water usage in agricultural operations. With growing water scarcity from the lack of natural rainfall and depleted groundwater tables, the need to maintain agricultural wells and agricultural production is dramatic. The proposed subsurface irrigation technology will reduce irrigated water by 50% over drip irrigation. This could enable significant reduction in water use and allow the groundwater tables to recover and perform as water reservoirs during drought years. It potentially can raise farm yields, improve weed control for organic farmers, and promote better uptake of fertilizers - thereby minimizing the pollution of underground aquifers. The proposed technology also can lead to energy cost reductions and increased flexibility in scheduling power usage. At a systems level, it offers a new paradigm for a resilient and sustainable irrigation. The proposed research is focused on the development of an easy-to-use moisture plume simulation calculator that enables farmers to self-analyze how their soil type will react when installing a virtual water table irrigation system. The latter is designed to eliminate water lost by surface evaporation and deep percolation. The research approach taken is an interdisciplinary collaboration to mathematically model the physics of how liquid transports from the subsurface feed pipes through the porous soil to the roots of the plants in an efficient manner with adequate accuracy. The predictions will be compared with more comprehensive industry-standard hydrological model predictions and also with the experimentally collected moisture data from the field. The technical risks lie in determining whether the basic soil properties collected by the non-scientist farmers would be adequate as inputs to generate an accurate prediction of moisture plume profile across many soil types.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.