[Truncated abstract] Generally hydrologic and ecologic models operate on arbitrary time and space scales, selected by the model developer or user based on the availability of field data. In reality rainfall is highly variable not only annually, seasonally and monthly but also the intensities within a rainfall event and infiltration properties on semi-arid hillslopes can also be highly variable as a result of discontinuous vegetation cover that form mosaics of areas with vegetation and areas of bare soil. This thesis is directed at improving our understanding of the impacts of the temporal representation of rainfall and spatial heterogeneity on model predictions of hydrologic thresholds and surface runoff coefficients on semi-arid landscapes at the point and hillslope scales. We firstly quantified within storm rainfall variability across a climate gradient in Western Australia by parameterizing the bounded random cascade rainfall model with one minute rainfall from 15 locations across Western Australia. This study revealed that rainfall activity generated in the tropics had more within storm variability and a larger proportion of the storm events received the majority of rain in the first half of the event. Rainfall generated from fontal activity in the south was less variable and more evenly distributed throughout the event. Parameters from the rainfall analysis were then used as inputs into a conceptual point scale surface runoff model to investigate the sensitivity of point scale surface runoff thresholds to the resolution of rainfall inputs. This study related maximum infiltration capacities to average storm intensities (k*) and showed where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k* = 0.4) and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k* > 2). For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g*) and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g* <2). The sensitivity of surface runoff predictions and the influence of specific within storm properties were then analysed on the hillslope scale. '...' It was found that using the flow model we still get threshold behaviour in surface runoff. Where conditions produce slow surface runoff velocities, spatial heterogeneity and temporal heterogeneity influences hillslope surface runoff amounts. Where conditions create higher surface runoff velocities, the temporal structure of within storm intensities has a larger influence on runoff amounts than spatial heterogeneity. Our results show that a general understanding of the prevailing rainfall conditions and the soil's infiltration capacity can help in deciding whether high rainfall resolutions (below 1 h) are required for accurate surface runoff predictions. The results of this study can be considered a contribution to understanding the way within storm properties effect the processes on the hillslope under a range of overall storm, slope and infiltration conditions as well as an improved understanding of how different vegetation patterns function to trap runoff at different total vegetation covers and rainfall intensities.