High resolution passive microwave response to landscape controls influencing soil moisture patterns: A case study for the Livingstone Creek Catchment

The 46km Livingstone Creek Catchment in south-eastern Australia was flown with a passive microwave airborne remote sensor (Polarimetric L-band Multibeam Radiometer, PLMR) as part of the National Airborne Field Experiment in 2006 with a spatial resolution of ~ 200m. The catchment was experiencing extreme drought conditions leading up to the experiment and as a result ground cover in the catchment was minimal with many paddocks consisting of sparse dry stubble and grass. The PLMR image captured surface wet soil moisture conditions after a 30mm rainfall event. This paper looks at the conceptualizations of our current understanding of landscape controls that influence the soil moisture patterns in the landscape. Passive microwave is becoming more widely available on various satellite platforms, and will be a valuable data source for catchment water balance and climate change science modelling. Downscaling of passive microwave satellite imagery data is the current challenge. The use of the high resolution PLMR data flown in this study allows for examination of the current data sources that provide surrogate information on terrain, land cover and soil properties that could potentially be used in downscaling procedures. Three indexes were used for a visual comparison. (1) A weathering index (2) Topographic Wetness Index (TWI) and (3) SPOT satellite imagery for land cover. The weathering index matched certain areas of the PLMR data where it was known that the soil properties were driving the soil wetness patterns. The topographic wetness index represented broad areas of hilly landscapes from flat alluvial areas in the PLMR images. The land cover appeared to show localised areas of high contrast in PLMR image however these areas are generally vegetated with trees as the landforms are steep with shallow infertile soils. It is proposed that further studies will look at multi criteria analysis of terrain and land cover indexes to try and find the correct mix of variables needed to represent the PLMR images so that downscaling studies from coarser PLMR data can occur.