Modelling land surface–atmosphere interactions over the Australian continent with an emphasis on the role of soil moisture

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Abstract

Soil moisture is a major natural state resistor variable in the global energy cycle as it influences the partitioning of both surface available energy into sensible and latent heat fluxes, and of precipitation into evapotranspiration and runoff. Consequently, physically based models of the biosphere need to simulate land surface conditions by including parameterisations for soil moisture. Soil moisture content is also important for determining the status of agricultural production since water in soil represents the major component of the hydrological cycle that is available to plants. Soil moisture is therefore important in ecological processes, and most biomass production models will include estimates of soil water availability. Given the identified importance of the soil moisture variable, it is perhaps surprising that there is a paucity of reliable long-term measurements, particularly over the major agricultural regions of Australia. Consequently, a diverse range of approaches, such as physically based models, stochastic modelling and remote sensing, have often been required to compensate for a dearth of actual measurements. This paper describes recent advances in soil water content simulation and prediction, utilising a numerical weather prediction model incorporating an improved land surface schema. This schema was developed in collaboration with the University of New South Wales and the Bureau of Resource Sciences. The land surface schema is essentially a surface hydrological model for prediction of evapotranspiration, surface and subsurface runoff and deep soil drainage, by parameterisation and solving the Richards' equation and the temperature diffusion equation for multi-soil layers. Soil moisture simulations obtained from this model for the Australian continent are presented. The model is shown to perform well, and further parameterisation work is progressing to improve the agreement between simulated and observed results.

Introduction

Soil moisture is a major resistor variable in the global energy cycle since it influences the partitioning of both surface available energy into sensible and latent heat fluxes, and of precipitation into evapotranspiration and runoff. Consequently, all of the major physically based models of the biosphere attempt to simulate land surface conditions by including parameterisations for soil moisture. From biophysical and agricultural perspectives, the measurement of soil moisture and the estimation of soil water content (depth-integrated soil moisture) are important activities for determining the status of agricultural production, since water in soil represents the major component of the hydrological cycle that is available to plants. Soil moisture is therefore also important in ecological processes, and most biomass production models will include estimates of soil water availability.

Soil moisture simulation for a continental coverage poses three major challenges. Firstly, soil moisture predictions with land surface schemes will be limited by the empirical or semi-empirical nature of the parameterisations. Opinions differ on how reliable soil moisture predictions with land surface schemes are. An assessment of various schemes for soil moisture simulation, with prescribed atmospheric forcing data and prescribed land surface parameters for soil hydraulic properties, aerodynamic properties and vegetation characteristics for a single point, has been examined in Shao et al. (1994)and related studies (Shao and Henderson-Sellers, 1996). The differences for each of the schemes that was demonstrated in these studies can mainly be attributed to the different treatment of soil hydrological processes in the schemes. Secondly, as soil moisture evolution involves interactions between the atmosphere, soil, and vegetation, land surface schemes are usually complex. The prediction of soil moisture depends critically on the input parameters that describe soil hydrological properties, surface aerodynamic properties and vegetation features (e.g. leaf area index). Finally, the interactions between the land surface and the atmosphere involve complex feedback processes that are not yet well understood, but are known to have a significant impact on climate variability.

In the case of soil moisture simulation, it appears that the uncertainties in the choice of land surface parameters and in the lower boundary condition of the soil layer exceed those arising from the atmospheric data. In current general circulation models, the land surface parameters contain significant uncertainties and the lower boundary is crudely treated. Therefore, it is likely that soil moisture predictions from current general circulation models are not sufficiently accurate to facilitate meaningful analysis of land surface processes.

Our intention in this study is to provide a simulation of soil moisture for the Australian continent. To this end there are three major tasks: the first is the development of a new land surface scheme with an improved treatment of surface soil hydrology. The second task is to establish a set of up-to-date parameters for the land surface, including soil and vegetation over the Australian continent using a geographical information system (GIS), and the third task is to couple the land surface scheme with an atmospheric model for the four-dimensional assimilation of soil moisture.

The soil moisture is calculated using the atmospheric land surface interaction scheme (ALSIS) driven by the output of the new University of New South Wales (UNSW) high-resolution limited-area atmospheric model (HLAM). This modelling approach and results are described in detail in the following sections of this paper. The aim of this paper is to describe preliminary results from an evolving system that is used to assist in the development of Australian Government policies concerning sustainable land-use management.

Section snippets

Simulation of soil moisture

For most simulation studies, soil moisture is typically obtained across both a spatially varying and time-independent domain. An important distinction thus needs to be made with field-based observations of soil moisture, which typically represent the time-integrated observations from point locations. Soil moisture prediction (and simulation) consequently encounters additional problems due to landscape and atmospheric heterogeneity. Topography, spatial variability in soil and vegetation

Discussion and conclusions

This paper describes a system to model soil moisture patterns and their evolution over the Australian continent. The land surface scheme, ALSIS, differs from many other schemes in the treatment of surface hydrology and the numerical formulation of the scheme. The non-linear relationships between soil hydraulic conductivity, matric potential and soil moisture content are based on the Broadbridge and White (1988)soil water retention model. The soil hydraulic parameters used to represent these

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