Monitoring soil moisture & snow water equivalent with cosmic-ray neutrons across scales

Cosmic-ray albedo neutron sensing (CRNS) is a modern technology that can be used to continuously measure the average water content in the environment (i.e., in soil, snow, or vegetation). The sensor footprint encompasses an area of 10-15 hectares and extends to 20-50 decimeters deep into the soil. Thereby it can capture relevant root-zone soil moisture for drought analysis while being insensitive to small-scale heterogeneity. The method can be an alternative to conventional in-situ sensors or to expensive sampling of soil or snow. It also has the potential to bridge the scale gap between point-scale measurements and remote-sensing data in both, the horizontal and the vertical domain.

Currently, more than 200 sensors are operated in the growing networks of national and continental observatories across the globe. CRNS stations are continuously monitoring the local water dynamics at various sites worldwide. They require almost no maintenance over the years due to a solar module, battery and telemetry. Since the method works non-invasively, the soil is left undisturbed. The passive sensing technique measures natural cosmogenic background radiation which interacts with hydrogen in the ground independent of temperature, frost, or wind effects. CRNS can also be used on mobile platforms for on-demand soil moisture mapping at the field-, regional, or even national scales. The sensors are rapidly operational on any ground- or airborne vehicle.

In this presentation we will demonstrate how stationary and mobile CRNS can help to quantify the temporal as well as spatial distribution of water in soil or snow for various sites in Germany, Europe, and beyond. We will also discuss applications of long-term monitoring networks in combination with hydrological modeling and remote sensing. The data can be particularly useful to study hydrological extreme events, droughts, heatwaves, floods, snow melt/accumulation, and it can be applied as a lower boundary condition in atmospheric models, in hydrological models, in agricultural irrigation management, or for drought impact analysis.