SoilDTS: Using data assimilation to determine in-situ surface and root zone soil moisture from Distributed Temperature Sensing

Soil moisture is a key state variable in surface hydrology and land-atmosphere interactions. In November 2009, ESA will launch the first dedicated soil moisture mission (SMOS). However, the resolution of these data is coarse (50km), so a way must be found to bridge the gap from traditional point-scale observations to footprint scale. Here we discuss SoilDTS, an experimental method of measuring soil moisture based on Distributed Temperature Sensing (DTS), which can yield information on soil moisture variability at high resolution (1-2m) over a large area. In DTS, inexpensive telecommunications fiber-optic cable is used to produce accurate (<0.1K) measurements of temperature at high resolution (1-2m) over long cables. To measure soil moisture, two to four fiber-optic cables, up to several kilometers in length, are plowed into the soil and DTS equipment is used to measure their temperatures every 2m. Temperature changes can be due to the diurnal radiation cycle (‘passive DTS’) or due to a heat pulse transmitted from the metal housing of one of the cables (‘active DTS’). Heat transport between cables depends on the thermal properties of the soil, which are functions of soil moisture. Our previous research has demonstrated that observing temperature dynamics with DTS can therefore provide a way to determine the soil moisture. Results are presented from a new experiment in which dual state-parameter estimation approach was used to infer surface and root zone soil moisture from in-situ temperature observations. Temperature was estimated as a state using the Ensemble Kalman Filter, while soil moisture was estimated as a parameter of the system. By estimating soil moisture at fine resolution over large areas, this method offers a unique opportunity to quantify the temporal and spatial variability in soil moisture at different scales.