Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.5194/gi-11-75-2022
Lizenz creative commons licence
Titel (primär) Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture
Autor Francke, T.; Heistermann, M.; Köhli, M.; Budach, C.; Schrön, M.; Oswald, S.E.
Quelle Geoscientific Instrumentation, Methods and Data Systems
Erscheinungsjahr 2022
Department MET
Band/Volume 11
Heft 1
Seite von 75
Seite bis 92
Sprache englisch
Topic T5 Future Landscapes
Abstract Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use.
This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution.
Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time.
The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.
dauerhafte UFZ-Verlinkung
Francke, T., Heistermann, M., Köhli, M., Budach, C., Schrön, M., Oswald, S.E. (2022):
Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture
Geosci. Instrum. Method. Data Syst. 11 (1), 75 - 92 10.5194/gi-11-75-2022