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New cheatgrass-wildfire probability equation #324

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kpalmqui opened this issue Jun 19, 2019 · 16 comments
Closed

New cheatgrass-wildfire probability equation #324

kpalmqui opened this issue Jun 19, 2019 · 16 comments

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@kpalmqui
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Our current equation that determines wildfire probability based on this years cheatgrass biomass was implemented improperly. Our implementation:

fire_prob = -0.117 + .0093 * cheatgrass_biomass
ignition threshold (biomass g/m2) required to utilize the above equation: 12.05

based on Figure 2 of Whisenant et al. 1990 Changing fire frequencies on Idaho's Snake River Plains: ecological and management implications

This is improperly implemented because the x-axis in Figure 2 is relative frequency (%), not biomass. As such, the threshold of cheatgrass biomass that triggers wildfire is currently set too low. This issue will revist and overhaul the cheatgrass-wildfire equation by re-examining the data in the literature to either: 1) identify a direct link between cheatgrass biomass and fire probability or 2) derive a link between cheatgrass biomass and fire probability via a relationship between cheatgrass cover and cheatgrass biomass.

see bottom of rgroup.in file for description and parameters associated with the current equation

@kpalmqui
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Two goals here:

  1. identify a new ignition threshold based on biomass
  2. derive a new equation that relates fire probability to biomass

@menglandjohns
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Here is the equation and summary document based off of the most current data scaled according to Balch et al.
Cheatgrass_fire_equation_summary.docx
@kpalmqui @chaukap

@kpalmqui
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kpalmqui commented Feb 4, 2020

@menglandjohns we need to create an equation for the relationship between cheatgrass cover and annual fire probability (not FRI) as that is what STEPWAT2 implements. Can you update this accordingly? And also provide the actual equation here in the comments for Chandler. Thanks!

@menglandjohns
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menglandjohns commented Feb 4, 2020

Updated, sorry.

Cheatgrass_fire_equation_summary.docx

Equation is y = 0.0074x^0.0649

@kpalmqui
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kpalmqui commented Feb 4, 2020

@menglandjohns great thanks!

@kpalmqui
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kpalmqui commented Feb 4, 2020

@chaukap @menglandjohns these parameters will replace cheatgrass_coefficient and wild_fire_slope. We are no longer utilizing a linear relationship here between cheatgrass abundance and fire probability, but rather have fit a power function. Because of this the ignition parameter is no longer needed.

We clearly need a flag to turn the cheatgrass-wildfire feedback loop on or off (which used to be accomplished by setting ignition to > 0). Where do you think the best place is for that flag in inputs? Perhaps where it is now at the bottom of rgroup.in?

I believe the best option will be to implement the power function @menglandjohns has derived within the code, rather than providing the coefficients in inputs (as it is now). What are your thoughts?

@kpalmqui
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@menglandjohns when you get a chance can you post and summarize some of your results from testing that demonstrate that this equation is working as expected? I.e. that as cheatgrass abundance increases, so does fire? And reflect on FRI values under different cheatgrass abundances?

Thanks!

@menglandjohns
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menglandjohns commented Mar 4, 2020

@kpalmqui @chaukap
Results summary: under low cheatgrass levels (eind 10, pestab .10) fire return intervals are higher than background levels but remain over 300 years (86 fires over all years and iterations), and cheatgrass biomass does not surpass 11 g/m2.

At high cheatgrass levels (eind 30, pestab 0.5) cheatgrass biomass achieves >100g/m^2 biomass within two years and remains near that level over the full 300 years. Fire return intervals spiked to about 100 years (228 fires over all years and iterations). Moderate cheatgrass levels (eind 20, pestab .2) resulted in fire intervals closer to those of high cheatgrass than low (just over 100 years).

High BRTE:
high_brte_biomass_testing.xlsx
Low BRTE:
low_brte_biomass_testing.xlsx

@kpalmqui
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kpalmqui commented Mar 5, 2020

@menglandjohns thanks! so it appears that the code is working as expected?

Quick question for you about your calculated fire return-intervals: I see there were 302 fires across all years and iterations in the high_brte_biomass_testing file. For a simulation run for 300 years and 100 iterations, the FRI should be: 30,000 years/302 fires = ~99 years between fires.

Can you doublecheck the calculated FRIs?

@menglandjohns
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@kpalmqui yes, you’re correct about that FRI. I’ll double check the data from the other test runs as well. The FRI is definitely increasing with increased cheatgrass, so that’s working as expected, but maybe not at the rate we would expect?

@kpalmqui
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kpalmqui commented Mar 7, 2020

@menglandjohns thanks! I am going to close this issue as this functionality is working as expected.

@kpalmqui
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@chaukap reopening this issue to add new comments regarding testing after the changes you have pushed.

@kpalmqui kpalmqui reopened this Mar 10, 2020
@kpalmqui
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I did some follow-up testing and manipulated eind to create low, medium, and high cheatgrass biomass conditions. Those excel files are below.

The FRI for these conditions:
Low brte biomass: 4.8 g/m2, 0.46% cover, FRI=191
Medium brte biomass: 21.7g/m2, 2.1% cover, FRI=99
High brte biomass: 83g/m2, 8% cover, FRI=127

@chaukap @menglandjohns this is not what we would expect. I am looking into why this might be - particularly why the high brte biomass results in less frequent fire. It should results in FRIs of 50 years. Re-checking our equation as a starting place.

@kpalmqui
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There was a problem with the original equation as specified. It was using the Bradley et al. 2018 fire probability values instead of the re-scaled Bradley et al. 2018 fire probabilities based on the fire data presented in Balch et al. 2013. Here is the correct equation:

y = 0.015x ^0.0649

image

New version of cheatgrass.fusco.fig2.calculations update 3.11.xlsx

@kpalmqui
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@chaukap I will implement this small change and then re-test.

kpalmqui added a commit that referenced this issue Mar 12, 2020
…ual fire probabilities, issue #324

See issue #324 for more detail
@kpalmqui
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Here are the results from the new test runs:

I did some follow-up testing and manipulated eind to create low, medium, and high cheatgrass biomass conditions. Those excel files are below.

The FRI for these conditions:
Low brte biomass: 3.8 g/m2, 0.4% cover, FRI=99 years
Medium brte biomass: 21.6g/m2, 2.1% cover, FRI=62 years
High brte biomass: 78g/m2, 7.5% cover, FRI=58 years

These values are correct based on the equation above and the FRIs expected in the above excel file. Therefore I am closing this issue. @chaukap @menglandjohns

bmassavg.lowcheatgrass.xlsx

bmassavg.mediumcheatgrass.xlsx

bmassavg.highcheatgrass.xlsx

dschlaep added a commit that referenced this issue Aug 4, 2022
- SOILWAT2 will soon get a major new release with several improvements and new features
* milestone: https://github.com/DrylandEcology/SOILWAT2/milestone/13
* PR: DrylandEcology/SOILWAT2#325

- the purpose of this STEPWAT2 branch is to track progress in SOILWAT2 towards that major release and add any necessary changes to the STEPWAT2/SOILWAT2 interface
* one of the goals is to limit code changes required in STEPWAT2 and to reproduce previous STEPWAT2 behavior and output (new settings will be set such that they reproduce previous behavior)

- as of now, this commit pulls in SOILWAT2 commit ac323024c142840211c6e41d84083e7f4211ef3b (Merge pull request #324 from DrylandEcology/feature_soildensity_type)
* see PR: DrylandEcology/SOILWAT2#324
* new behavior: user specifies whether input soil density represents matric or bulk density (new input in `siteparam.in` with backwards compatible value of 0 = matric)
* this commit produces identical STEPWAT2 output as the current "master" (2022-June-17) on commit 69486d5
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