Neutron monitor based incoming flux correction for cosmic-ray neutron sensing of environmental water - Hertle, Lasse; Zacharias, Steffen; Larsen, Nicholas; Rasche, Daniel; McJannet, David; Schrön, Martin (Water resources research, 2025)
Monitoring of near-surface water content with cosmic-ray neutrons is strongly dependent on heliospheric and geomagnetic conditions. Neutron monitor (NM) stations are commonly used as a reference for the incoming cosmic radiation to correct the hydrological neutron signal. This paper discusses the various approaches to perform this correction, their derivation, and inherent assumptions. To overcome limitations of the existing methods, we present two alternative approaches: (a) an improved correction method that takes into account the temporal dynamics of geomagnetic variations, and (b) a globally robust approach based on the PHITS-based Analytical Radiation Model in the Atmosphere (PARMA) model. Further, a method to overcome diurnal effects is also presented, which is applicable to all correction methods. The performances of all correction methods have been evaluated on long-term NM data, and their impact has been assessed using artificial cosmic-ray neutron sensor data. We found that our new method showed slightly better performance than McJannet and Desilets (2023, https://doi.org/10.1029/2022wr033889) for capturing the temporal variability. Both methods outperformed the conventional correction approaches by Zreda et al. (2012, https://doi.org/10.5194/hess-16-4079-2012) and Hawdon et al. (2014, https://doi.org/10.1002/2013wr015138). Globally, the PARMA model provides the most robust results with gap-free correction data that is less prone to local effects, but slightly increased errors compared to the optimal approach for individual sites. The choice of the incoming correction method can lead to deviations in the soil moisture product of up to 30%, which shows the relevance of these results for hydrological applications.
Online veröffentlicht: 28. August 2025
Gesehen am 12.01.2026