Predicting wildfire induced changes to runoff: A review and synthesis of modeling approaches. (16th May 2022)

• Record Type: Journal Article
• Authors: Partington, Daniel; Thyer, Mark; Shanafield, Margaret; McInerney, David; Westra, Seth; Maier, Holger; Simmons, Craig; Croke, Barry; Jakeman, Anthony John; Gupta, Hoshin; Kavetski, Dmitri
• Is Part Of: Wiley interdisciplinary reviews. Volume 9:Number 5(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-16
• Subjects: hydrological modeling -- runoff prediction -- wildfire disturbance; Hydrology -- Periodicals; 553.705
• DOI: 10.1002/wat2.1599
• Languages: English
• ISSNs: 2049-1948

Abstract

Abstract: Wildfires elicit a diversity of hydrological changes, impacting processes that drive both water quantity and quality. As wildfires increase in frequency and severity, there is a need to assess the implications for the hydrological response. Wildfire‐related hydrological changes operate at three distinct timescales: the immediate fire aftermath, the recovery phase, and long‐term across multiple cycles of wildfire and regrowth. Different dominant processes operate at each timescale. Consequentially, models used to predict wildfire impacts need an explicit representation of different processes, depending on modeling objectives and wildfire impact timescale. We summarize existing data‐driven, conceptual, and physically based models used to assess wildfire impacts on runoff, identifying the dominant assumptions, process representations, timescales, and key limitations of each model type. Given the substantial observed and projected changes to wildfire regimes and associated hydrological impacts, it is likely that physically based models will become increasingly important. This is due to their capacity both to simulate simultaneous changes to multiple processes, and their use of physical and biological principles to support extrapolation beyond the historical record. Yet benefits of physically based models are moderated by their higher data requirements and lower computational speed. We argue that advances in predicting hydrological impacts from wildfire will come through combining these physically based models with new computationally faster conceptual and reduced‐order models. The aim is to combine the strengths and overcome weaknesses of the different model types, enabling simulations of critical water resources scenarios representing wildfire‐induced changes to runoff. This article is categorized under: Water and Life > Conservation, Management, and Awareness Science of Water > Hydrological Processes Science of Water > Water and Environmental Change Abstract : Wildfire threats are increasing and there is a need to assess these implications on hydrological functioning through hydrological modelling. Possible changes to hydrological functioning in an undisturbed catchment (panel a) elicited by wildfire (panel b) are shown in the resultant aftermath short‐term changes (panel c) and medium‐term recovery phase (panel e). Long‐term changes are dependent on the next fire and so could include recovery to pre‐fire conditions (panel a) or the increased or decreased streamflow conditions in (panel c) and (panel e). Comparison of some possible storm event responses (panel d) highlights a need for models to capture key processes responsible for these differing responses. Furthermore, long‐term impacts are potentially associated with an increase in wildfire frequency/severity (panel f). Through combining strengths and overcoming weaknesses of different model types, improvements in predicting wildfire induced hydrological impacts can be realised. (Key: E, evaporation; ET, evapotranspiration; GW, groundwater; I, infiltration; Interception, canopy, understory, and litter interception; P, precipitation; R, recharge).