Conceptual evaluation of continental land-surface model behaviour

Continental land-surface models, such as the landscape component of the Australian Water Resources Assessment System (AWRA-L), aim to simulate the water balance over a wide variety of climates, land forms and land uses. To accommodate this range of hydrological conditions, model conceptualisation has to be flexible, while at the same time robust and parsimonious to allow for calibration using sparse data sets.In this study a Monte Carlo sensitivity analysis of the AWRA-L system is carried out as a step preceding calibration in which the hyperspace formed by parameters and initial conditions is explored using Latin Hypercube Sampling. The main goal is to test whether the model behaviour is in accordance with current understanding of Australian hydrology and to guide calibration. To visualise and analyse the high-dimensionality of the output space and the complex, non-linear interactions between processes and parameters, we used Self Organizing Maps, a non-parametric neural network.The results show that the main cause of non-linear model behaviour can be attributed to the ratio of rainfall over potential evaporation ratio, which determines which processes will dominate the water balance and the persistence of initial conditions. The model behaviour corresponds well to the current understanding of the hydrology of the Australian continent.

► Pre-calibration sensitivity analysis of the land-surface model AWRA-L.
► Visualisation of interactions between variables with Self-Organizing Maps.
► Results compare with the known hydrological conditions in Australia.
► Parameters that can be constrained by calibration differ between dry and wet regions.