# Climate change impacts on forest fires : INRA contribution

Jean-Luc Dupuy, François Pimont, Nicolas Martin-StPaul, Hélène Fargeon, Eric Rigolot

► To cite this version:

Jean-Luc Dupuy, François Pimont, Nicolas Martin-StPaul, Hélène Fargeon, Eric Rigolot. Climate change impacts on forest fires : INRA contribution. EUSTAFOR Forest fire workshop, Office National des Forêts (ONF). FRA., Jul 2017, Aix-en-Provence, France. 19 p. hal-01606916

HAL Id: hal-01606916

https://hal.science/hal-01606916

Submitted on 5 Jun 2020

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution - ShareAlike 4.0 International License
<figure><img src="image_2.png" /></figure>

INRA
SCIENCE & IMPACT

EUSTAFOR Forest Fire Workshop

Aix-en-Provence

26 - 27 April 2017

# Climate change impacts on forest fire risk : INRA contribution

Jean-luc Dupuy, François Pimont, Nicolas Martin, Hélène Fargeon, Eric Rigolot

INRA PACA, URFM Ecologie des Forêts Méditerranéennes, Avignon, France
## Outline

INRA researches on forest fires

Climate change impacts on forest fire risk

- conclusions from a survey of fire risk projections in Europe

- a PhD project on assessment of future forest fire risk in France

- some data issues
INRA researches on forest fires

Topics

* Fire behaviour modelling

* Fuel measurement and modelling

* Plant physiology, water stress and fuel moisture

Approach

* Process-based modelling, as far as possible

* Stand to landscape scales

Applications

* Fire risk evaluation

* Fuel treatment evaluation

* Climate change impacts on forest fire risk

<figure><img src="image_3.png" /><figcaption>Fuel break</figcaption></figure>

<figure><img src="image_4.png" /></figure>
Physically-based fire modelling : FIRETEC

* Coupling of physical processes driving fire spread, with atmospheric dynamics

- 3D fuel distribution (biomass, moisture)

* Equations solved on 3D grid

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

- Spatial resolution : 2 m

- Spatial scales: stand to landscape

* Predictions : fire contours, fire intensity, fluxes, temperatures,...
Fuel measurement : use of terrestrial LiDAR

Estimation of foliage biomass in forest
canopies

Theory : LiDAR point cloud density is proportional to foliage area

Development : calibration, post-processing
algorithms

<figure><img src="image_8.png" /><figcaption>Canopy bulk density profiles
in a Quercus pubescens stand</figcaption></figure>

<figure><img src="image_9.png" /></figure>
Modelling live fuel moisture dynamics

Development of a soil-plant hydraulic model
to predict survival time to drought

Measurement of plant hydraulic traits,
including shrubs

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>Chênes verts ayant subi la sécheresse dans l'Hérault</figcaption></figure>

Photo : Pierre Girard, DSF.

<figure><img src="image_12.png" /></figure>
# Climate change impacts on forest fire risk

**MEDWILDFIRELAB**

"*Global change impacts on wildfire activity and behaviour in southern Europe*", a networking action funded by the ERANET FORESTERRA (2014-2017).

<figure><img src="image_13.png" /></figure>

SEVENTH FRAMEWORK PROGRAMME

**Deliverable D2.1: Global change impacts on wildfire activity and behaviour in southern Europe**, by J-L Dupuy, M. Guijarro, P. Fernandes

**Literature survey** of studies assessing changes in wildfire danger or activity in Europe under global warming:
- synthetic view of expected changes
- current limitations of the methods used to produce these projections
# Climate change impacts on forest fire risk

## Projection methods

In Europe, most projections are based on the Fire Weather Index

These projections are useful to assess trends in potential fire danger and delimiting future fire-prone area

Some studies use statistical relations between climate and observed fire activity (not applicable in new fire-prone areas)

<figure><img src="image_14.png" /><figcaption>The Fire Weather Index (FWI)</figcaption></figure>

MEDWILDFIRELAB

<figure><img src="image_15.png" /></figure>
# Climate change impacts on forest fire risk

## Expected trends (summary)

Fire danger and fire season length are projected to increase everywhere in southern Europe.

In the warmest and driest, currently fire-prone regions, fuel availability could become the main limiting factor of fire activity. Projections of burnt areas are very uncertain.

The area at risk should expand to new fire-prone regions, such as the western and central France, Eastern Europe or the Mediterranean mountains.

MEDWILDFIRELAB

<figure><img src="image_16.png" /></figure>

Bedia et al. (2014)

Extreme fire danger

<figure><img src="image_17.png" /></figure>

Length of fire season

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>
Climate change impacts on forest fire risk

MEDWILDFIRELAB

<figure><img src="image_21.png" /></figure>

Limitations of current methods

Underlying hypotheses (FWI-based projections)

* warming will only change the frequency of
high flammability conditions (i.e. low fuel moisture)

- water balance is independent of soil and vegetation cover (drought codes)

* fuel moisture effect on fire does not depend on fuel structure

Moreover, warming and CO2 fertilization could affect current fuels

- aridification in driest areas -> fuel fragmentation

- biomass accumulation in wettest areas -> fuel continuity

But uncertainty on precipitations and complexity of biophysical processes preclude
predictive simulations to date

Current state-of-the-art leads to consider climate impacts as if fuels and
anthropogenic fire drivers do not change
Climate change impacts on forest fire risk

<figure><img src="image_22.png" /></figure>

Normalized rate of spread
(FIRETEC, moderate wind)

Fuel moisture effect may
depend on fuel structure
# Climate change impacts on forest fire risk in France

**PhD project (Hélène Fargeon, 2016-2019) : A process-based approach of climate change impact on forest fire risk in France**

Projection of the FWI shows an expansion of the potential fire-prone area in France

The project aims to:

- incorporate the fuel structure effect in fire projections

- model the water balance and fuel moisture by a process-based approach

Typical question: what will be the future risk for deciduous oak stands in France ?

<figure><img src="image_23.png" /><figcaption>(FWI computed from May 15 to October 15)</figcaption></figure>
# Climate change impacts on forest fire risk in France

## PhD project - General approach

<figure><img src="image_24.png" /></figure>
# Climate change impacts on forest fire risk in France

## PhD project - Main issues & research needs

<figure><img src="image_25.png" /></figure>

**Lack of fuel data**
# Climate change impacts on forest fire risk in France

## PhD project - Main issues & research needs

<figure><img src="image_26.png" /></figure>
# Climate change impacts on forest fire risk in France

## PhD project - Main issues & research needs

<figure><img src="image_27.png" /></figure>

**Model fuel moisture dynamics, mortality**
# Climate change impacts on forest fire risk in France

## Data issues

* Lack of fuel data, especially in temperate areas

* French NFI: very few data on litter, herbaceous and shrub layers; crown base height not measured

* Find proxies, build models

(e.g. Spanish NFI has much more fuel-oriented data)

* Use T-LiDAR scans of the NFI for shrub or tree canopy structure

* Use available allometries for loads, LAI

* Perform field fuel inventories for validation

<figure><img src="image_28.png" /><figcaption>T-LiDAR scan of a shrub layer</figcaption></figure>

<figure><img src="image_29.png" /></figure>
# Climate change impacts on forest fire risk in France

## Data issues

* Fuel moisture data for model validation

→ A French network for field monitoring of shrub fuel moisture content :

- 30 active sites in the Mediterranean region, 24 species,

- 1 sample/week at least (~15 June-15 September), up to 20 years of data

- operated by the ONF

<figure><img src="image_30.png" /><figcaption>*Sites on a water deficit gradient*</figcaption></figure>

<figure><img src="image_31.png" /></figure>
Thank you for your attention !