Simultaneous monitoring of soil water content and vegetation with cosmic-ray neutron sensors: novel findings and future opportunities

Accurate and continuous monitoring of soil water content (SWC) and plant development provides significant benefits in various contexts, including long-term environmental observatories, the development and validation of environmental models and remote sensing products, as well as practical applications like digital and sustainable agriculture. Cosmic-Ray Neutron Sensors (CRNS) are becoming increasingly popular for continuous and non-invasive monitoring of SWC, and recent advancements have demonstrated their potential for vegetation monitoring. CRNS use a moderated detector to measure epithermal neutron intensity (E_n) and estimate SWC over a radius of approximately 200 m. An additional bare detector measures lower-energy thermal neutron intensity (T_n), which is more sensitive to vegetation biomass than to SWC. However, the benefits of simultaneous monitoring of SWC and vegetation properties with CNRS for monitoring networks such as ICOS and ILTER have not been investigated yet.

In this study, a CRNS that is part of the COSMOS-Europe network measured E_n and T_n over a 10-year period at the ICOS Class 1 ecosystem station in Selhausen, Germany (integrated into the already-present TERENO station in 2019). E_n and T_n were compared to a large dataset of a) SWC obtained from multiple point-scale sensors within 30 m of the CRNS, b) gross primary productivity (GPP) obtained with the eddy covariance (EC) method, and c) manual and drone-based measurements of plant height (PH), leaf area index (LAI), and dry aboveground biomass (AGB).

Discrepancies between the CRNS and the point-scale SWC measurements were observed (RMSE of 0.063 cm³/cm³). These were attributed to the periodic reinstallation of the point-scale sensors that sometimes led to abrupt changes in measured SWC, and to the fact that the CRNS, like the EC station, measures over a much larger area. Thanks to the co-location of the CRNS and EC station, a comparison of T_n and GPP showed a clear co-development during cropping periods and the lower responsiveness of T_n during senescence and desiccation indicated that factors such as plant structure and other hydrogen pools (e.g., below-ground biomass) may affect T_n. Crop-specific or annual models were used to estimate plant traits from T_n. The accuracy of plant traits predicted by the CRNS was relatively lower compared to manual and destructive methods (RMSE of 0.13 m for PH, 1.01 m for LAI, and 0.27 kg/m² for dry AGB). However, the effortless nature of the CRNS outweighs this reduction in accuracy, opening the possibility of generating continuous time series of plant traits with only a few manual measurements.

This study showcases the potential of CRNS for simultaneous field-scale monitoring of SWC and vegetation, which is of great interest for monitoring platforms and environmental modelling. Moreover, the novel findings obtained by comparing T_n and GPP showed that strengthened collaboration between observatories and networks such as COSMOS, TERENO, and ICOS, can provide information that is not only useful for researchers but also for instruments manufacturers. In fact, the possibility to extend the usage of CRNS beyond SWC and toward monitoring of plant traits could increase the interest towards thermal neutron detection and vegetation monitoring.