Erosion, flash floods and debris flows are hydro-geomorphic processes that intensify due to catchment disturbance by wildland fire. Predictive models of these processes are used by land managers to quantify rehabilitation effectiveness, prioritize resources and evaluate trade-offs between different management strategies. Predictions can be difficult to make, however, because of heterogeneous landscapes, stochastic rainfall, and the transient and variable fire effects. This paper reviews hydro-geomorphic response models for burned areas and explores how modelling approaches and sources of uncertainty change depending on the focus question (or purpose) and the associated spatial-temporal scale of the model domain. The review shows that current models focus primarily on predicting catchment responses during a recovery period (within-burn timescales), a relatively short temporal window during which rainfall is an important source of uncertainty. At longer (between-burn) timescales, the fire regime itself, and not just fire severity, becomes a variable component of the model. At this temporal scale, the catchment processes respond to variations in the frequency and severity with which a landscape is conditioned (or ‘primed’) by fire and rain storms. Conditioning is a stochastic process that is determined by the spatial-temporal overlap of fire disturbance and rain storms. The translation of overlaps to hydro-geomorphic responses is a function of intrinsic catchment attributes (e.g. permeability, slope and catchment area). Capturing the stochastic interplay between fire and rain storms is important when land-management questions shift towards the issues of climate change and landscape-scale interventions such as prescribed burning. The review therefore includes a discussion on fire and rainfall regimes as variables which drive decadal and regional variability in hydro-geomorphic processes.
Nyman P, Sheridan GJ, Lane PNJ. 2013. Hydro-geomorphic response models for burned areas and their applications in land management. Progress in Physical Geography 37(6) 787–812. DOI: 10.1177/0309133313508802.