Abstract

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, soil moisture prediction models are normally used to predict the evolution of soil moisture, but these models are based on sparse measurements of soil hydraulic parameter information or typical values. Therefore, more accurate and detailed soil hydraulic parameter data is vital if regional or global soil moisture predictions are to be made with the required accuracy. To overcome this limitation, it is hypothesised by this thesis that the soil hydraulic properties, e.g. hydraulic conductivity, porosity, field capacity, and wilting point, may be derived through model calibration to remotely sensed near-surface soil moisture observation. To test this hypothesis, the work presented in this thesis is conducted in three distinct steps. The Joint UK Land Environment Simulator (JULES) was used for this purpose, as it was identified as a suitable soil moisture prediction model for the proposed work. The soil hydraulic parameters most sensitive to soil moisture prediction were determined and were thus the focus of this research. In the first step, the proposed methodology was tested via a one-dimensional synthetic twin-experiment. The intent was to identify the most suitable meteorologic conditions for soil property retrieval, and hence make the most efficient use of computational resources when applying the methodology at large scales. The methodology was also tested for four different soil types including a homogeneous column of sand, a homogeneous column of clay, a duplex column of clay over sand, and a duplex column of silty sand over clay. In the second step, field measurements of soil moisture from the OzNet Soil Hydrological Monitoring Network over the Murrumbidgee Catchment have been utilized. The purpose being to determine the feasibility and the level of accuracy that can be expected for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The soil hydraulic parameters retrieved from near-surface soil moisture measurements were validated against field and laboratory measured data. The derived root zone soil moisture predictions using the retrieved parameters were also validated against field observations from the same network. The last step of this thesis was to apply the methodology to a larger area, the size of a Soil Moisture and Ocean Salinity (SMOS) satellite footprint. However, rather than using a single soil moisture value for the entire demonstration area, a downscaled soil moisture product, Disaggregation based on Physical And Theoretical scale Change (DisPATCh), was used in the retrieval of soil hydraulic parameters. Spatial maps for the parameters, including surface and root zone, were obtained for the focus area.

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