High resolution soil moisture mapping

Soil moisture information is of critical importance to real-world applications such as agriculture, water resource management, flood, fire and landslide prediction, mobility, soil hydraulic parameter estimation etc. Many of these applications require soil moisture information at high resolution. While this may be estimated from land surface models, the predictions are often poor due to inadequate model physics, poor parameter estimates and erroneous atmospheric forcing data. An alternative is remote sensing but most techniques only give a soil moisture estimate for the top few centimetres. Moreover, the sensors that give the most reliable soil moisture estimates (passive microwave) have relatively low spatial resolution from space, being on the order of 50km. Such sensors include the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission launched in Nov 2009, and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission scheduled for launch in Oct 2014. Other high spatial resolution satellite observations such as active microwave, visible and thermal have been shown to contain information on soil moisture, but their data is noisy and/or difficult to interpret. However, it is expected that the low resolution passive microwave data may be downscaled using the noisy high resolution data and/or modeling. For example, SMAP will provide a better than 10km resolution soil moisture product by merging 3km active microwave data with 40km passive microwave data. This paper presents some examples of high resolution soil moisture mapping from ground and airborne techniques, combined active-passive satellite soil moisture retrieval, optical downscaling, and assimilation into a high resolution land surface model. Moreover, this paper discusses the role of land surface models to both downscale the satellite observations and to yield a root-zone (top 1m) soil moisture map, rather than the near-surface (top 5cm) values typically observed. Calibrating land surface models to remotely sensed soil moisture also affords the possibility to retrieve soil hydraulic parameters. 2 GROUND BASED MEASUREMENT 2.1 Hydraprobe Data Acquisition System The Hydraprobe Data Acquisition System (HDAS) is a spatially enabled soil moisture, temperature and salinity measurement platform that logs all relevant information into GIS (Geographic Information System) format using ArcPad ® . It has been developed over the last 5 years by authors of this paper and consists of a Stevens ® Water hydraprobe and a GPS (Global Positioning System) enabled handheld computer running GIS software and a custom script (see Fig. 1). This pocket PC is used to:  display a map of the sampling area and grid;  communicate with the GPS receiver to get the real time position;  display the location on a background map;  communicate with the hydraprobe to take readings of soil moisture, temperature and salinity;  obtain metadata including sample date, time, ID;  input any additional observations as required;  store the metadata, position information and hydraprobe readings in a GIS shape file; and  display the location of the recorded measurements on the map. The hydraprobe determines soil moisture and salinity by making a high frequency (50 MHz) complex dielectric constant measurement. The hydraprobe sensor provides four voltage outputs that can be converted to soil moisture, temperature and salinity using proprietary relationships of Stevens ® Water, according to three pre-defined soil types. Additionally the real and imaginary parts of the soils dielectric constant are derived. Like most soil dielectric sensors, the output is soil temperature dependent, and is thus integrated with a thermocouple. The accuracy of the hydraprobe soil moisture output has been found to be poorer than the stated manufacturer accuracy by several independent field tests; this was observed particularly in clay soils characterised by warm temperatures. Moreover, in clays, the standard output showed highly reduced sensitivity to changes in soil moisture when wetter than 0.3m 3 /m 3 . Therefore the HDAS system uses an advanced soil moisture relationship developed though extensive laboratory analysis, with a demonstrated field accuracy of 0.035m 3 /m 3 over a variety of soil types (Merlin et al. 2007). It is also more reliable with respect to soil temperature variations, particularly in clay soils. The HDAS allows rapid monitoring of top 5cm soil moisture for large areas as shown in Figure 2.