Large Area Distributed Real Time Soil (DiRTS) Monitoring

大面积分布式实时土壤 (DiRTS) 监测

• 批准号: NE/T012323/1
• 负责人: Sami Ullah
• 金额: $ 43.77万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FT012323%2F1
• 关键词: Large; Area; Distributed; Real; Time

Advancing our understanding of the soil ecosystem, especially the dynamics of nitrogen species, is critical for improving soil fertility, increasing crop productivity, managing greenhouse gas fluxes, and protecting environmental quality. This project presents convergent research to develop the next generation, integrated sensing system for large area, in situ, high resolution spatio-temporal monitoring of dynamic nitrogen species, specifically ammonium and nitrate, as well as soil moisture, potassium and salinity. The wireless Distributed Real Time Soil (DiRTS) monitoring network is comprised of (1) soil-penetrable sensor motes with advanced microfluidics mimicking plant root-like water intake, (2) robust electrochemical sensors for ammonium, nitrate, potassium and salinity utilizing ultra-low power circuit architectures for readout and digitization, (3) long range wireless data communication using emerging standards, and (4) advanced algorithms for geospatial mapping of soil mineral nitrogen, potassium, salinity and moisture. The platform will address fundamental weaknesses in our understanding and control of nitrogen species in both unmanaged (e.g. forest) and managed (e.g. agriculture) soils. Beyond the technical impact, the proposed research effort will offer educational and training opportunities for undergraduate and graduate students through innovative curriculum and for farmers and other soil management practitioners through publicly available training modules on design and deployment of the wireless Distributed Real Time Soil (DiRTS) monitoring platform.The DiRTS platform will make several notable scientific contributions: (1) Continuous capillary-driven sampling of the target soil nutrients mimicking the natural water intake by roots and transpiration through aboveground plant parts; (2) Ion sensitive electrodes utilizing embedded desalination to improve selectivity, and utilizing redundancy and Bayesian calibration to improve sensitivity; (3) Circuits for readout and digitization operating below 0.5V power supply and nanowatt level power dissipation; (4) Event-driven sampling and wireless communication using probabilistic sensor scheduling based on available power and data importance; and (5) State of the art statistical machine learning based approaches for generating high resolution spatio-temporal chemical maps from irregularly sampled data. All technology will be validated using actual, in-situ measurements of the target variable using the sensing mote and DET/DGT sensors in an experimental forest-BIFoR-FACE of the Birmingham Institute of Forest Research. Following validation, the sensing mote will then be fitted inside greenhouse gas auto-chambers in the FACE facility for concomittant sensing of dynamic nitrogen species and N2O fluxes to be monitored using a PICARO greenhouse gas analyzer and mapped using DiRTS sensor network. This proposal brings together experts in engineering, biogeosciences and chemistry from the US and UK, with strong backgrounds and expertise in relevant areas of sensing, electronics, microfluidics, biogeochemistry, soil science, signal processing and sensor networks, for successful execution of this project.

提高我们对土壤生态系统的理解，特别是氮素形态的动态，对于改善土壤肥力，提高作物产量，管理温室气体通量和保护环境质量至关重要。该项目提出了集中研究，以开发下一代综合传感系统，用于大面积、原位、高分辨率的动态氮物种时空监测，特别是铵和硝酸盐，以及土壤水分、钾和盐度。无线分布式真实的时间土壤（DiRTS）监测网络包括（1）具有模拟植物根状水摄入的先进微流体的土壤可穿透传感器微粒，（2）利用用于读出和数字化的超低功率电路架构的用于铵、硝酸盐、钾和盐度的鲁棒电化学传感器，（3）使用新兴标准的远程无线数据通信，（4）土壤矿质氮、钾、盐分和水分地理空间制图的先进算法。该平台将解决我们在理解和控制非管理（例如森林）和管理（例如农业）土壤中氮物种方面的根本弱点。除了技术影响之外，拟议的研究工作将通过创新课程为本科生和研究生提供教育和培训机会，并通过关于无线分布式真实的时间土壤（DiRTS）监测平台设计和部署的公开培训模块为农民和其他土壤管理从业者提供教育和培训机会。DiRTS平台将做出几项显著的科学贡献：（1）对目标土壤养分的连续毛细管驱动采样，模拟根系的自然吸水和植物地上部分的蒸腾作用;（2）离子敏感电极，利用嵌入式脱盐提高选择性，并利用冗余和贝叶斯校准提高灵敏度;（3）用于在0.5V电源和高功率级功耗下操作的读出和数字化电路;（4）基于可用功率和数据重要性使用概率传感器调度的事件驱动采样和无线通信;以及（5）用于从不规则采样数据生成高分辨率时空化学图的基于统计机器学习的方法的现有技术。所有的技术都将通过在伯明翰森林研究所的实验森林BIFoR-FACE中使用感测微粒和DET/DGT传感器对目标变量进行实际原位测量来验证。验证后，传感微粒将安装在FACE设施的温室气体自动室中，用于使用PICARO温室气体分析仪监测动态氮物种和N2 O通量的伴随传感，并使用DiRTS传感器网络进行映射。该提案汇集了来自美国和英国的工程、地球科学和化学专家，他们在传感、电子、微流体、地球化学、土壤科学、信号处理和传感器网络等相关领域具有强大的背景和专业知识，以成功执行该项目。

项目成果

Ammonia emissions from nitrogen fertilised agricultural soils: controlling factors and solutions for emission reduction

施氮农业土壤氨排放：控制因素及减排方案

• DOI: 10.1071/en23010
• 发表时间: 2023
• 期刊: Environmental Chemistry
• 影响因子: 4.3
• 作者: Rathbone C

Spartina alterniflora has the highest methane emissions in a St. Lawrence estuary salt marsh

• DOI: 10.1088/2752-664x/ac706a
• 发表时间: 2022-05
• 期刊: Environmental Research: Ecology
• 作者: S. Comer-Warner;Sami Ullah;Wendy Ampuero Reyes;S. Krause;G. Chmura

Elevated temperature and nutrients lead to increased N2O emissions from salt marsh soils from cold and warm climates

• DOI: 10.1007/s10533-023-01104-0
• 发表时间: 2023-12
• 期刊: Biogeochemistry
• 影响因子: 4
• 作者: S. Comer-Warner;Sami Ullah;Arunabha Dey;Camille L. Stagg;Tracy Elsey-Quirk;C. Swarzenski;F. Sgouridis;Stefan Krause;Gail L. Chmura

Real-time soil nutrients monitoring

实时土壤养分监测

• DOI: 10.5194/egusphere-egu22-8543
• 发表时间: 2022
• 作者: Saiz E

Towards enhanced sensitivity of the 15N Gas Flux method for quantifying denitrification in soil

提高 15N 气体通量方法量化土壤反硝化的灵敏度

• DOI: 10.5194/egusphere-egu22-585
• 发表时间: 2022
• 作者: Micucci G