Fire can result in hydro–geomorphic changes that are spatially variable and difficult to predict. In this research note we compile 294 infiltration measurements and 10 other soil, catchment runoff and erosion datasets from the eastern Victorian uplands in south-eastern Australia and argue that higher aridity (a function of the long-term mean precipitation and net radiation) is associated with lower post-fire infiltration capacities, increasing the chance of surface runoff and strongly increasing the chance of debris flows. Post-fire debris flows were only observed in the more arid locations within the Victorian uplands, and resulted in erosion rates more than two orders of magnitude greater than non-debris flow processes. We therefore argue that aridity is a high-order control on the magnitude of post-wildfire hydro–geomorphic processes. Aridity is a landscape-scale parameter that is mappable at a high resolution and therefore is a useful predictor of the spatial variability of the magnitude of post-fire hydro–geomorphic responses.

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution ( KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire‐affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment‐scale estimates. Furthermore, the distribution of Ks was not clearly log‐normal and scale‐independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply‐limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.

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