Thesis (Ph.D.)--University of Western Australia, 2006.

[Truncated abstract] During the last fifty years mathematical models of catchment hydrology have been widely developed and used for hydrologic forecasting, design and water resources management. Most of these models need large numbers of parameters to represent the flow generation process. The model parameters are estimated through calibration techniques and often lead to ‘unrealistic’ values due to structural error in the model formulations. This thesis presents a new strategy for developing catchment hydrology models for representing streamflow and salinity generation processes. The strategy seeks to ‘learn from data’ in order to specify a conceptual framework that is appropriate for the particular space and time scale under consideration. Initially, the conceptual framework is developed by considering large space and time scales. The space and time scales are then progressively reduced and conceptual model complexity systematically increased until ultimately, an adequate simulation of daily streamflow and salinity is achieved. This strategy leads to identification of a few key physically meaningful parameters, most of which can be estimated a priori and with minimal or no calibration. Initially, the annual streamflow data from ten experimental catchments (control and cleared for agriculture) were analysed. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in stream zone saturated area. The annual evapotranspiration losses from native vegetation and pasture, the ‘excess’ water (resulting from reduced transpiration after land use change), runoff and deep storage were estimated by a simple water balance model. The model parameters are obtained a priori without calibration. The annual model was then elaborated by analysing the monthly rainfall-runoff, groundwater and soil moisture data from four experimental catchments. Ernies (control, fully forested) and Lemon (53% cleared) catchments are located in zone with a mean annual rainfall of 725 mm. Salmon (control, fully forested) and Wights (100% cleared) are located in zone with mean annual rainfall of 1125 mm. Groundwater levels rose and the stream zone saturated area increased significantly after clearing. From analysis of this data it was evident that at a monthly time step the conceptual model framework needed to include a systematic gain/loss to storage component in order to adequately describe the observed lags between peak monthly rainfall and runoff.