Abstract. The aim of this paper is to illustrate the effects of selected catchment storage thresholds upon runoff behaviour, and specifically their impact upon flood frequency. The analysis is carried out with the use of a stochastic rainfall model, incorporating rainfall variability at intra-event, inter-event and seasonal timescales, as well as infrequent summer tropical cyclones, coupled with deterministic rainfall-runoff models that incorporate runoff generation by both saturation excess and subsurface stormflow mechanisms. Changing runoff generation mechanisms (i.e. from subsurface flow to surface runoff) associated with a given threshold (i.e. saturation storage capacity) are shown to be manifested in the flood frequency curve as a break in slope. It is observed that the inclusion of infrequent summer storm events increases the temporal frequency occurrence and magnitude of surface runoff events, in this way contributing to steeper flood frequency curves, and an additional break in the slope of the flood frequency curve. The results of this study highlight the importance of thresholds on flood frequency, and provide insights into the complex interactions between rainfall variability and threshold nonlinearities in the rainfall-runoff process, which are shown to have a significant impact on the resulting flood frequency curves.

Abstract. Traditional statistical approaches to flood frequency inherently assume homogeneity and stationarity in the flood generation process. This study illustrates the impact of heterogeneity associated with threshold non-linearities in the storage-discharge relationship associated with the rainfall-runoff process upon flood frequency behaviour. For a simplified, non-threshold (i.e. homogeneous) scenario, flood frequency can be characterised in terms of rainfall frequency, the characteristic response time of the catchment, and storm intermittency, modified by the relative strength of evaporation. The flood frequency curve is then a consistent transformation of the rainfall frequency curve, and could be readily described by traditional statistical methods. The introduction of storage thresholds, namely a field capacity storage and a catchment storage capacity, however, results in different flood frequency "regions" associated with distinctly different rainfall-runoff response behaviour and different process controls. The return period associated with the transition between these regions is directly related to the frequency of threshold exceedence. Where threshold exceedence is relatively rare, statistical extrapolation of flood frequency on the basis of short historical flood records risks ignoring this heterogeneity, and therefore significantly underestimating the magnitude of extreme flood peaks.

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[1] A comparative study is performed to explore interactions between climate variability and landscape factors that control water balance variability in three diverse regions of Australia: Perth (temperate with distinct dry summers); Newcastle (temperate with no distinct dry season); and Darwin (tropical region affected by monsoons). This comparative analysis is carried out through adoption of a common conceptual model. The similarity and differences between the three catchments are explored through evaluation of signatures of streamflow and soil moisture variability, and systematic sensitivity analysis with respect to parameters representing various landscape characteristics. The results of the analysis show that the biggest contributor to the differences between the catchments is the distribution of soil depth and the soil's drainage characteristics. The second factor is climate, as exemplified by the (annual) climatic dryness index and the intra-annual (seasonal) variability of both rainfall and potential evaporation, and associated rainfall intensity patterns, and their interactions with the soil properties (i.e., soil depth and the soil's drainage characteristics). In Perth and Darwin, climate seasonality is responsible for a seasonal switching on/off of subsurface stormflow at the start/end of the wet season, respectively. In Newcastle, where soil moisture contents hover near the field capacity value throughout the year, subsurface stormflow occurs frequently throughout the year, with event-based switching on/off in response to individual storms of moderate magnitude and temporal clustering of small storms. In addition, in rare circumstance, surface runoff is triggered in response to extreme storm events and temporal clustering of moderate to large storm events.Citation: Samuel, J. M., M. Sivapalan, and I. Struthers (2008), Diagnostic analysis of water balance variability: A comparative modeling study of catchments in

[1] A unit gradient multiple wetting front model is described, in which the infiltration and redistribution behavior of individual ''square wave'' fronts is simulated for unponded rainfall infiltration. Drainage recession behavior of this model is demonstrated to be equivalent to that of a capacitance (bucket) model for certain scenarios, suggesting a possible physical basis for capacitance model parameters with respect to drainage prediction. The ability of the wetting front model to account for the variable time lag between surface infiltration and drainage generation at depth, which cannot be achieved using a capacitance model, is demonstrated to improve predictions of the 25-year average drainage regime of a free-draining lysimeter in Colbitz, Germany, when compared to capacitance model predictions. Improvement in predictions compared to the capacitance model is most apparent in deeper and drier soils, where the infiltration-drainage time lag is significant. Comparison with a numerical Richards equation solution suggests that drainage behavior predicted by the model is reasonable for the conditions considered, despite neglecting capillary impacts. The ability of the model to differentiate between drainage response time and the age of draining water gives the approach general applicability for problems requiring simulation of the age of water involved in hydrological response to storms.