Modeling tools for examining how climate change & management influence wildfire activity & effects

Transcription

1 Modeling tools for examining how climate change & management influence wildfire activity & effects Erin Hanan December 2018 Great Basin Climate Forum

2 Frequency of large, severe wildfires is increasing Dennison et al (2014) Due to: Human activities Climate change

3 Frequency of large, severe wildfires is increasing Ignitions

4 Frequency of large, severe wildfires is increasing Ignitions Fuels Photo: Zion Klos

5 Frequency of large, severe wildfires is increasing Ignitions Climate/weather Fuels Photo: Zion Klos Image: newyorktimes.com

6 Frequency of large, severe wildfires is increasing Ignitions Climate/weather Fuels Photo: Zion Klos Image: newyorktimes.com All have been modified by humans!

7 Ignitions Increased fire occurrence Lengthened fire seasons Balch et al (2017)

8 Fuels Fire suppression Overstocked forests Accumulation of dead materials Ladder fuels Especially problematic in seasonally dry forests

9 Image:npr.org

10 Climate change Warmer temperatures Earlier snowmelt Fuel aridity

11 Climate change => Fuel aridity => Large fires

12 Low signal to noise at watershed scales due to: Interannual variability in meteorological forcings Confounding factors: Image: nasa.gov Image: nasa.gov Image: Colorado State Forest Service

13 How do climate change & fuel management interact to influence wildfire activity at watershed scales in the western U.S.?

14 Simulation models can address complexity and bridge scales Fire Water Plants Soils

15 RHESSys: regional hydro-ecologic simulation system Land Cover Hydrologic outputs: snowpack, streamflow, evaporation, etc. Soils Rivers Time/Space Budgets for Carbon, Nitrogen, Water, Energy Elevation Algorithms / Assumptions Vegetation outputs: plant productivity, mortality, etc.

16 How do we use RHESSys? Develop and apply simulation models to: Estimate how vegetation, carbon, nitrogen, and water fluxes will respond to: Fire Beetles Active management Other disturbances Integrate data from multiple sources: Remote sensing Field observations Mechanistic understanding

17 Simulating processes: streamflow, NPP, nitrogen Partitions a watershed into a hierarchical set of spatial units: Patch Hill Basin

18 Running RHESSys Landscape characteristics Topography Vegetation Drainage network Soil Hierarchical & distributed landscape elements Watershed Hill Patch

19 Running RHESSys Landscape characteristics Topography Vegetation Drainage network Soil Inputs Library of veg & soil parameters Climate time series Disturbance history Hierarchical & distributed landscape elements Process-based sub-models Watershed Hydrologic Canopy Hill Soil BGC Patch

20 Running RHESSys Landscape characteristics Topography Vegetation Drainage network Soil Hierarchical & distributed landscape elements Outputs Inputs Library of veg & soil parameters Climate time series Disturbance history Process-based sub-models C & N in soils & plants Streamflow N export Timeseries Watershed Hydrologic Hill Soil BGC Patch Canopy Spatial

21 Coupled fire regime model Ecohydrologic model Fire effects model Fire spread model

22 Stochastic Fire start based on: Fuel Moisture Fire spread based on: Fuel Moisture Wind Slope RHESSys input data Fire spread model: WMFire

23 Fire effects model Overstory height threshold Understory height threshold Accounts for: Fire intensity Canopy structure Understory Mortality Overstory Mortality Proportion Mortality Understory Mortality Parameter (k1) Proportion Mortality Slope Parameter (k3) Centerpoint Parameter (k4) Intensity (i u ) Understory & Litter Consumption (gc m 2 ) Bart et al. (in press)

24 Why RHESSys? Stood up to challenges: Streamflow Nitrate export Remote sensing of veg Flux tower data Tree rings Photosynthesis

25 Multi-criteria calibration and validation NSE = 0.7 Daily Streamflow Record Model Steady State kg C / m 2 Ponderosa Pine in Oregon kg C / m 2 Plant C Leaf C Stem C Root C Coarse Woody Debris Litter C Spruce-Fir in Colorado kg C / m Soil C Total C Literature-Reported Carbon Stores Elev = 3,100 m, Age = 190 yrs cor= Year Tree Ring Record Remote Sensing Vegetation Indices Dugger, A.L., Tague, C., and Margolis, E.Q. A three-pronged approach to coupled carbon and water-cycling model validation in a semi-arid mountain watershed.

26 What research questions? 1. How does post-fire recovery vary with belowground environmental characteristics, such as soil depth and resource availability?

27 What research questions? 1. How does post-fire recovery vary with belowground environmental characteristics, such as soil depth and resource availability? Favorable environment Resource poor 20-years 70-years RHESSys accounts for long term effects of belowground properties on vegetation, e.g. carbon allocation

28 What research questions? 2. How does climate change influence postfire nitrate export in chaparral?

29 What research questions? 2. How does climate change influence postfire nitrate export in chaparral? N export highest when fire is followed by drought Soil microbes are less sensitive than plants are to drought Mineral N accumulates during the hot, dry summer, and is then flushed with winter rain Erin J. Hanan, Naomi Tague, & Joshua Schimel. "Nitrogen cycling and export in California chaparral: the role of climate in shaping ecosystem responses to fire." Ecological Monographs 87.1 (2017):

30 What research questions? 3. Is warming likely to cause significant mortality events in the southern Rocky Mountains?

31 What research questions? 3. Is warming likely to cause significant mortality events in the southern Rocky Mountains? High Baseline +2 C Warming +4 C Warming Mid Low Orange is high probability of mortality Tague, C. L., McDowell, N. G., & Allen, C. D. (2013). An integrated model of environmental effects on growth, carbohydrate balance, and mortality of Pinus ponderosa forests in the southern Rocky Mountains. PloS one, 8(11).

32 What research questions? 5. What are the roles of climate change & fire suppression in driving wildfire activity?

33 What research questions? 5. What are the roles of climate change & fire suppression in driving wildfire activity? Complete exclusion No exclusion Anthropogenic climate change x100 x100 Without anthropogenic climate change x100 x100

34 No prior exclusion Complete prior exclusion No anthropogenic climate change 95 th percentile: 176 Fire starts: th percentile: Fire starts: 668 Anthropogenic climate change 95 th percentile: Fire starts: th percentile: Fire starts: 982

35 Research in the Great Basin: 1. How do climate change and fuel management influence fire activity in the Great Basin? 2. How will future wildfires influence: a. Recovery rates of vegetation? b. C sequestration and streamflow? c. Postfire N export? Goals: Improve the algorithms for fire spread Forecast future wildfire risk Develop strategies to mitigate those risks