From 1 - 1 / 1
  • Categories  

    The Australian cosmic-ray soil moisture monitoring network was first established in 2010 to provide Australian and global researchers with spatially distributed intermediate scale soil moisture observations. A cosmic-ray sensor (CRS) provides continuous estimates of soil moisture over an area of approximately 30 hectares by measuring naturally generated fast neutrons (energy 10–1000 eV) that are produced by cosmic rays passing through the Earth’s atmosphere. The neutron intensity above the land surface is inversely correlated with soil moisture as it responds to the hydrogen contained in the soil and to a lesser degree to plant and soil carbon compounds. The cosmic-ray technique is also passive, non-contact, and is largely insensitive to bulk density, surface roughness, the physical state of water, and soil texture. The scale of CRS measurements fills the void between point scale sensor measurements and large scale satellite observations. The depth of measurements varies with the moisture content of the soil but is typically between 10-30 cm. The depth of observations is reported as ‘effective depth’. The CosmOz network is expanding as new sensors are added over time. The initial network was funded by CSIRO Land and Water but more recently TERN has funded work to maintain the network add new sensors and deliver data more efficiently. The standard CRS installation includes; a cosmic-ray neutron tube, a rain gauge (2m high), temperature and humidity sensors, and an atmospheric pressure sensor. Measures of all parameters are reported at an hourly interval. Each CRS requires an in-field calibration across the footprint of measurements to convert neutron counts to soil moisture content. The calibration includes collection of soil samples for bulk density, lattice water content and soil organic carbon. The extent of the network and available data can be seen at the CosmOz network web page: https://cosmoz.csiro.au/ The calibration and correction procedures used by the network are described by Hawdon et al. 2014.