Integrating fire with hydrological projections: model evaluation to identify uncertainties and tradeoffs in model complexity

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Conference Proceeding


It is imperative for resource managers to understand how a changing climate might modify future watershed and hydrological processes, and such an understanding is incomplete if disturbances such as fire are not integrated with hydrological projections. Can a robust fire spread model be developed that approximates patterns of fire spread in response to varying topography wind patterns, and fuel loads and moistures, without requiring intensive calibration to each new study area or time frame? We assessed the performance of a stochastic model of fire spread (WMFire), integrated with the Regional Hydro-Ecological Simulation System (RHESSys), for projecting the effects of climatic change on mountain watersheds. We first use Monte Carlo inference to determine that the fire spread model is able to replicate the spatial pattern of fire spread for a contemporary wildfire in Washington State (the Tripod fire), measured by the lacunarity and fractal dimension of the fire. We then integrate a version of WMFire able to replicate the contemporary wildfire with RHESSys and simulate a New Mexico watershed over the calibration period of RHESSys (1941-1997). In comparing the fire spread model to a single contemporary wildfire we found issues in parameter identifiability for several of the nine parameters, due to model input uncertainty and insensitivity of the mathematical function to certain ranges of the parameter values. Model input uncertainty is caused by the inherent difficulty in reconstructing fuel loads and fuel moistures for a fire event after the fire has occurred, as well as by issues in translating variables relevant to hydrological processes produced by the hydrological model to those known to affect fire spread and fire severity. The first stage in the model evaluation aided the improvement of the model in both of these regards. In transporting the model to a new landscape in order to evaluate fire regimes in addition to patterns of fire spread, we find reasonable outcomes with respect to both. This two-stage model evaluation against multiple criteria and for more than one landscape demonstrates that a relatively simple model of fire spread can be sufficiently robust to simulate fire regimes for varying ecosystems and time periods. A careful model evaluation allows for identification of model uncertainties, which are then reduced by improvements to model structure. When integrating a fire spread model with a hydrological model for watershed projections it is insufficient to determine the adequacy of the fire spread module independently of the hydrological model. The integration of the two models should be assessed as vigorously as the individual modules.

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American Geophysical Union Fall 2013 Meeting




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