SBIR Phase I: Cosmic Ray Neutron Sensing for Soil Water Measurements at Irrigation Decision Resolution

SBIR 第一阶段：宇宙射线中子传感，用于灌溉决策分辨率下的土壤水测量

• 批准号: 2208754
• 负责人: Andrew Inglis
• 金额: $ 25.57万
• 依托单位: Silverside Detectors Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2023-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2208754&HistoricalAwards=false
• 关键词: SBIR; Phase; Cosmic; Ray; Neutron

The broader impact/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is a touchless, crop agnostic, automatic, always on, non-drifting, and cost-effective way of measuring soil moisture in large fields with data specific to each irrigation zone. The goal is to enable irrigators in water-scarce environments to maximize yields given the water available, and to mitigate the impacts of drought and aquifer reduction by enabling irrigators to calibrate their systems to the precise needs of the plants. The impact of this system is to maximize productivity of irrigation water, reducing waste and costs for crop growers and other irrigators. The commercialization of this product will provide the data needed for precision irrigation to respond to daily ground water needs, broadly reducing water consumption in agriculture and other markets. This technology translates a known methodology for soil moisture monitoring used by researchers and academics into a tool that delivers actionable data to end users that steward the world’s water resources. The goal of the proposed research and development is to verify that data from an arrayed set of smaller Cosmic Ray Neutron Sensing (CRNS) systems, ingested into an interpolation algorithm, can provide a soil moisture heat map with resolution at the level of each irrigation point for water measurements in the field. This project will remove the main technical risks associated with applying the CRNS methodology to a sub-field measurement scale, providing actionable data through granular moisture analysis. This data will be compared with a similar heat map generated by a multi hour, high labor assay using a manual probing system. This comparison seeks to support automated, precision irrigation systems to minimize water usage and correct for overwatering. The main technical hurdles that will be addressed include: the data collection from an array of smaller-form-factor CRNS systems that are placed on the field at the spacing of the desired measurement resolution; integration of neutron count data over the large temporal scales that are necessary to overcome the noise associated with the less efficient detectors; and the ability to provide the necessary temporally-changing information that is relevant to the irrigation manager.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.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业影响是一种非接触式、与作物无关、自动、始终在线、非漂移且经济高效的方法，可测量大田地土壤湿度，并提供特定数据目标是使灌溉者在缺水环境中能够在可用水的情况下最大限度地提高产量，并通过使灌溉者能够根据灌溉者的精确需求来校准其系统来减轻干旱和含水层减少的影响。该系统的作用是最大限度地提高灌溉用水的生产率，减少作物种植者和其他灌溉者的浪费和成本。该产品的商业化将为精确灌溉提供所需的数据，以满足日常地下水需求，从而广泛减少用水。该技术将研究人员和学者使用的已知土壤湿度监测方法转化为一种工具，向管理世界水资源的最终用户提供可操作的数据。拟议的研究和开发的目标是验证。来自一组数组的数据较小的宇宙射线中子传感（CRNS）系统，纳入插值算法，可以提供土壤湿度热图，其分辨率在每个灌溉点的水平上，用于田间水测量。该项目将消除与应用相关的主要技术风险。将 CRNS 方法应用于子现场测量范围，通过颗粒水分分析提供可操作的数据，该数据将与使用手动探测系统进行多小时、高劳动力分析生成的类似热图进行比较。 、精准灌溉减少用水量并纠正过度浇水的系统将要解决的主要技术障碍包括：从一系列较小尺寸的 CRNS 系统收集数据，这些系统以所需的测量分辨率间隔放置在田间；克服与低效探测器相关的噪声所必需的大时间尺度的中子计数数据；以及提供与灌溉管理人员相关的必要的随时间变化的信息的能力。该奖项反映了 NSF 的法定使命，并具有被认为值得支持通过使用基金会的智力优点和更广泛的影响审查标准进行评估。