Large Area Distributed Real Time Soil (DiRTS) Monitoring

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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.