Neptoon: An open-source and extensible software tool for data processing of cosmic-ray neutron sensors

The highly interdisciplinary method of Cosmic Ray Neutron Sensing (CRNS) has emerged as a key technology for monitoring root-zone soil moisture at the hectare scale. The technique bridges the spatial gap between traditional point-scale measurements and coarser remote sensing products. While CRNS is widely used in agriculture and weather services, processing of its data requires advanced knowledge about cosmic-ray physics. With the increasing adoption of CRNS across research infrastructures and observatories world-wide, standardised, flexible, and easy-to-use processing tools are essential for supporting data integration within these networks. Here we present neptoon, an open-source Python tool for neutron data processing that addresses these highly interdisciplinary challenges. It implements a modular, expandable framework to support both operational deployment of CRNS, as well as methodological innovation. Building from previous CRNS processing tools, we will present the overall architecture of neptoon and how it implements established processing methodologies while maintaining extensibility for emerging approaches. Through an intuitive configuration system and graphical user interface, neptoon streamlines data processing workflows and ensures reproducibility across research sites. As our understanding of the sensor signal continues to improve, the ability for research infrastructures to quickly implement the latest advancements becomes ever more important. We will demonstrate how neptoon facilitates rapid deployment of these latest processing methodologies, supports cross-site harmonisation, whilst also enabling robust testing of experimental correction methods. Through its support of multiple stakeholders, from researchers to sensor owners, the latest advancements can be pushed quickly back to the broader community. By providing a standardised yet flexible processing framework, neptoon aims to accelerate the integration of CRNS measurements into critical zone research and enhance our understanding of soil moisture dynamics across scales.