Balancing uncertainty and complexity to incorporate fire spread in an eco-hydrological model

Wildfire affects the ecosystem services of watersheds, and climate change will modify fire regimes and watershed dynamics. In many eco-hydrological simulations, fire is included as an exogenous force. Rarely are the bidirectional feedbacks between watersheds and fire regimes integrated in a simulation system because the eco-hydrological model predicts variables that are incompatible with the requirements of fire models. WMFire is a fire-spread model of intermediate complexity designed to be integrated with the Regional Hydro-ecological Simulation System (RHESSys). Spread in WMFire is based on four variables that (i) represent known influences on fire spread: litter load, relative moisture deficit, wind direction and topographic slope, and (ii) are derived directly from RHESSys outputs. The probability that a fire spreads from pixel to pixel depends on these variables as predicted by RHESSys. We tested a partial integration between WMFire and RHESSys on the Santa Fe (New Mexico) and the HJ Andrews (Oregon State) watersheds. Model assessment showed correspondence between expected spatial patterns of spread and seasonality in both watersheds. These results demonstrate the efficacy of an approach to link eco-hydrologic model outputs with a fire spread model. Future work will develop a fire effects module in RHESSys for a fully coupled, bidirectional model.

[1]  A. Solomon,et al.  Temporal and spatial structure in a daily wildfire-start data set from the western United States (1986–96) , 2008 .

[2]  David M. Hannah,et al.  Ecohydrology and hydroecology: A ‘new paradigm’? , 2004 .

[3]  C. Tague,et al.  Ecohydrology and Climate Change in the Mountains of the Western USA – A Review of Research and Opportunities , 2010 .

[4]  Gordon E. Grant,et al.  Parameterizing sub-surface drainage with geology to improve modeling streamflow responses to climate in data limited environments , 2012 .

[5]  Peter J. Weisberg,et al.  Fire history, fire regimes, and development of forest structure in the central western Oregon Cascades , 1998 .

[6]  Donald McKenzie,et al.  Power laws reveal phase transitions in landscape controls of fire regimes , 2012, Nature Communications.

[7]  Inez Y. Fung,et al.  Mid-latitude afforestation shifts general circulation and tropical precipitation , 2010, Proceedings of the National Academy of Sciences.

[8]  G. Caldarelli,et al.  Percolation in real wildfires , 2001, cond-mat/0108011.

[9]  Christina L. Tague,et al.  RHESSys: Regional Hydro-Ecologic Simulation System—An Object- Oriented Approach to Spatially Distributed Modeling of Carbon, Water, and Nutrient Cycling , 2004 .

[10]  H. Bugmann,et al.  Water and carbon fluxes of European ecosystems: an evaluation of the ecohydrological model RHESSys , 2007 .

[11]  Valeriy Y. Ivanov,et al.  Modeling plant–water interactions: an ecohydrological overview from the cell to the global scale , 2016 .

[12]  M. Krawchuk,et al.  Implications of changing climate for global wildland fire , 2009 .

[13]  Christina L. Tague,et al.  Influence of spatial temperature estimation method in ecohydrologic modeling in the Western Oregon Cascades , 2013 .

[14]  Dongwook W. Ko,et al.  Modeling fire and landform influences on the distribution of old-growth pinyon-juniper woodland , 2008, Landscape Ecology.

[15]  N. McDowell,et al.  An Integrated Model of Environmental Effects on Growth, Carbohydrate Balance, and Mortality of Pinus ponderosa Forests in the Southern Rocky Mountains , 2013, PloS one.

[16]  Riccardo Minciardi,et al.  Regional partitioning for wildfire regime characterization , 2008 .

[17]  Andreas Krause,et al.  The sensitivity of global wildfires to simulated past, present, and future lightning frequency , 2014 .

[18]  M. Finney FARSITE : Fire Area Simulator : model development and evaluation , 1998 .

[19]  Robert V. O'Neill,et al.  Analysis of parameter error in a nonlinear model , 1980 .

[20]  Joe H. Scott,et al.  Standard Fire Behavior Fuel Models: A Comprehensive Set for Use with Rothermel?s Surface Fire Spread Model , 2015 .

[21]  Ajith H. Perera,et al.  Modeling wildfire regimes in forest landscapes: abstracting a complex reality , 2015 .

[22]  B. Malamud,et al.  Characterizing wildfire regimes in the United States. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[23]  M. L. Heinselman Fire in the Virgin Forests of the Boundary Waters Canoe Area, Minnesota , 1973, Quaternary Research.

[24]  Maureen C. Kennedy,et al.  Using a stochastic model and cross-scale analysis to evaluate controls on historical low-severity fire regimes , 2010, Landscape Ecology.

[25]  C. Azorín-Molina,et al.  Impact of climate and land use change on water availability and reservoir management: scenarios in the Upper Aragón River, Spanish Pyrenees. , 2014, The Science of the total environment.

[26]  C. Tague,et al.  The sensitivity of forest water use to the timing of precipitation and snowmelt recharge in the California Sierra: Implications for a warming climate , 2013 .

[27]  N. Stephenson,et al.  Actual evapotranspiration and deficit: biologically meaningful correlates of vegetation distribution across spatial scales , 1998 .

[28]  Mohd Talib Latif,et al.  Fitting a mixture of von Mises distributions in order to model data on wind direction in Peninsular Malaysia , 2013 .

[29]  E. David Ford,et al.  MULTI-CRITERIA ASSESSMENT OF ECOLOGICAL PROCESS MODELS , 1999 .

[30]  George M. Hornberger,et al.  Selection of parameter values in environmental models using sparse data: A case study , 1985 .

[31]  Ellis Q. Margolis,et al.  Fire history and fire―climate relationships along a fire regime gradient in the Santa Fe Municipal Watershed, NM, USA , 2009 .

[32]  E. Natasha Stavros,et al.  Regional projections of the likelihood of very large wildland fires under a changing climate in the contiguous Western United States , 2014, Climatic Change.

[33]  R. Keane,et al.  Estimating historical range and variation of landscape patch dynamics: limitations of the simulation approach , 2002 .

[34]  J. Randerson,et al.  Spatial patterns and controls on burned area for two contrasting fire regimes in Southern California , 2016 .

[35]  David E. Calkin,et al.  Research and development supporting risk-based wildfire effects prediction for fuels and fire management: status and needs , 2013 .

[36]  Robert A. Norheim,et al.  Forest ecosystems, disturbance, and climatic change in Washington State, USA , 2010 .

[37]  R. Rothermel A Mathematical Model for Predicting Fire Spread in Wildland Fuels , 2017 .

[38]  John B. Bradford,et al.  Climate change, fire management, and ecological services in the southwestern US , 2014 .

[39]  Lee H. MacDonald,et al.  Climate change impacts on fire regimes and key ecosystem services in Rocky Mountain forests , 2014 .

[40]  C. Tague,et al.  Subsurface storage capacity influences climate–evapotranspiration interactions in three western United States catchments , 2015 .

[41]  LELAND J. JACKSON,et al.  An Introduction to the Practice of Ecological Modeling , 2000 .

[42]  D. Hannah,et al.  Ecohydrology and Hydroecology: An Introduction , 2008 .

[43]  R. Shakesby,et al.  Wildfire as a hydrological and geomorphological agent , 2006 .