Estimating root-zone soil moisture from gamma radiation monitoring data

Root-zone soil moisture (RZSM) information is valuable in a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents RZSM, especially with regard to longer periods and larger spatial scales. For example, active and passive microwave remote sensing observations for soil moisture are limited to the topsoil and can be influenced by land cover type. One option for RZSM observation is terrestrial gamma radiation as it is inversely related with soil moisture. Hence, the near-real-time data of more than 4600 gamma radiation monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) may be a potential source to develop a RZSM product for Europe without extra investments in sensors. The aim of this study was to investigate to what extent the EURDEP data can be used for RZSM estimation. For this, two gamma radiation monitoring stations were equipped with in-situ soil water content sensors to measure reference RZSM. The terrestrial component of gamma radiation was extracted after eliminating the contribution of secondary cosmic radiation. For this, it was assumed that the long-term contribution of secondary cosmic radiation is constant and that the variations are caused by changes in atmospheric pressure and incoming neutrons. In addition, precipitation effects creating a sudden increase in gamma radiation due to atmospheric washout of radon progenies to the ground were eliminated by excluding time periods with precipitation. Finally, multi-year terrestrial gamma radiation measurements were used to estimate weekly RZSM and the results were compared with the reference measurements. It was found that the seasonal variation of RZSM can be reasonably well predicted with an RMSE of 7 – 9 vol.% from gamma radiation measurements. However, the radiation-based RZSM estimates fluctuated with a much greater amplitude compared to the reference data, especially during the winter and spring season. This may be related to unknown or neglected additional sources that affect the gamma radiation signal and this needs to be further investigated. Although the accuracy of radiation-based RZSM estimates is not as good as many other in-situ sensors, this technique is still competitive with satellite-based remote sensing technique to estimate RZSM on the continental scale.