Timely foreknowledge of soil water content (SWC) and soil organic content (SOC) has the potential to strongly impact watering and sequestration decisions, throughout the growing season. But currently, monitoring, reporting, and verification (MRV) of these is costly and time-consuming. Barriers include high equipment costs, infrastructure installation, and sensing capabilities. Our recent technological breakthrough in aerial robotics, the capability to dig into soil, coupled with advances in sensing technologies gives us the ability to build unmanned aircraft systems (UAS) to largely automate this process. We address the issue of SOC/SWC monitoring, reporting, and verification by building a multi-agent UAS team and accompanying controllers, task planners, and machine-learning classifiers capable of persistent atmospheric monitoring via tethered UAS, and heterogeneous sampling UAS for insertion of key sensor probes, and extraction of soil samples for automated collection. Together the UAS and algorithms provide a mechanism to collect automated, accurate, and high temporal and spatial resolution (e.g., much higher than satellites) SWC and SOC data which we then make available to the public. The data can be easily used to help make timely agricultural, sequestration, and water management decisions by stakeholders.