1. Estimation of hydrological response of small Mediterranean watershed to fire by data analysis and modelling approach
Lebedeva L.1,3, Semenova O.2,4, Folton N.5
1Nansen Environmental and Remote Sensing Centre, St. Petersburg, Russia
2Gidrotehproekt Ltd, St. Petersburg, Russia
3State Hydrological Institute, St. Petersburg, Russia
4St. Petersburg State University, St. Petersburg, Russia
5National Research Institute of Science and Technology for Environment and Agriculture, Aix-en-Provence, France

2. The goals of the research:
Motivation and goal
Forest fires are reported to have crucial effect on runoff formation
Non-stationarity is still not accounted for in most hydrological models
The goals of the research:
to quantify the hydrological response of the small Mediterranean watershed to wild fire on daily and hourly timescales
to investigate an ability of the process-based hydrological model to cope with non-stationary post-fire conditions

3. Methodology
Detection of fire impact on hydrological regime by data analysis
Detection of fire-induced landscape changes based on literature review
Runoff formation process-based modelling with fixed parameters
Assessment of the hydrological change by model detection method
Simulation of the post-fire runoff, taking into account
the changes in vegetation and soil properties
simulated hydrographs and variable states for pre- and post-fire periods
detection of changes in hydrological regime after the fire
modelling approach applicable in non-stationary conditions

4. Study area: the Ruisseau du Rimbaud at Collobrieres, France
Area 1.46 km2; elevation m; daily and hourly data available for
Mediterranean climate with intense autumn rains and summer drought
Precipitation mm/year, flow mm/year, PE mm
Shrubby maquis and a degraded forest of cork oak, chestnut and maritime pines
Thin, sandy soils of the ranker type
August 1990 fire destroyed 85 % of the watershed
Vine P., Puech C., Clement B., Bouguerzaz F Remote sensing and vegetation recovery mapping after a forest fire. EARSel Advances in remote sensing. Vol.4, No 4 - XI
Fourcade B. , Coudrain-ribstein A. , Martin C What can be deduced from chemical measurement in an open-field raingauge? An example in the Maures Massif, southeastern France. Hydrological Sciences Journal  Vol. 47, Iss. 3

5. Peak flood discharge vs rainfall on daily time step
There is no changes of the peak floods on daily time step after the fire

6. Peak flood discharge vs rainfall on hourly time step
Increase of hourly peak discharges can be detected during three years after the fire (1990–1992)

7. Instantaneous peak flood discharge vs rainfall
Relationship between instantaneous peak flood discharge and precipitation within 24 hours throughout the autumn-winter period (September, October, November and December) . Period after the fire: September November 1994 (Cosandey et al. 2005)
Cosandey C, Andréassian V, Martin C, Didon-Lescot JF, Lavabre J, Folton N, Mathys N, Richard D The hydrological impact of the Mediterranean forest: A review of French research. Journal of Hydrology 301:1–15

8. Median peak floods before and after the fire
P = 53 mm
P = 45 mm
Qpeak = 0.65 m3/s
P = 40 mm
Qpeak = 0.59 m3/s
Qpeak = 0.71 m3/s
Median peak floods increased in three post-fire years and decreased after opposite to rainfall changes

9. Process-based hydrological modelling
Employs dynamic set of parameters which can change with time
Minimum calibration (parameters can be obtained apriori)
Basic input data, daily or hourly resolution (air humidity and temperature, precip)
Free of scale problem (from soil column to large basin)
initially developed by Prof. Yury Vinogradov

10. Detection of hydrological change by modelling
Hourly data
Daily data
Pre-fire
Modelling results do not detect any significant changes after the fire on a regular basis
Post-fire
NSE
0.52
0.76
NSE
0.45
0.76

11. Results of the Hydrograph model application to Rimbaud watershed, daily time step
The NS and bias show strong positive correlation with annual rainfall and are not to be considered as adequate model evaluation criteria

12. Hourly observed vs simulated peak floods
Slight underestimation of hourly high flood peaks greater than 2 m3/s and overestimation of floods lower than 2 m3/s

13. Detection of separate floods influenced by fire
Hourly observed vs simulated peak floods
Peak flood discharge vs rainfall
Four flood events in post-fire period have shown a 25–50% increase in peak discharge compared to the events caused by the same rainfall in the reference period.
The Hydrograph model was applied with new landscape parameters

14. Development of post-fire model parameters for 1990-1992
Bare soil increased up to 90 % immediately after the fire (Vine et al. 1996). Related vegetation parameters were modified:
before fire after fire
shadow fraction by vegetation, %
interception storage capacity, mm
landscape albedo, %
coefficient of evaporation, 10-8hPa s
2) Water-repellent, or hydrophobic soil layer formation (DeBano (2000) was reflected by the following soil parameters:
coefficient of infiltration, mm min-1 : before fire after fire
upper soil layer
middle and lower layers
variation coefficient of infiltration

15. Observed and simulated with pre- and post-fire parameters hydrographs of selected peak floods
A newly developed set of model parameters improved the efficiency to a certain extent.

16. Conclusions
No significant changes in hydrological regime of the Rimbaud watershed after the fire in 1990 are detected on daily scale Fire impact is localized on increase of hourly peak discharges during three years after the fire (1990–1992) in wet season The Hydrograph model continuous simulations at hourly and daily time steps satisfactorily fit the whole period Post-fire model parameters reflecting changing environment result in slightly improved efficiency of simulations of selected outstanding flood peaks Discernible fire impact is localized on separate floods events only and has nonlinear character Changing in time observable model parameters are prospective for simulations in non-stationary conditions

17. Thank you for your attention!

18. Analysis of peak floods and rainfall data
The response to heavy rain is particularly violent after the fire (Lavabre and Martin, 1997).
134 daily and 190 hourly flood events were investigated:
precedent rainfall higher than 20 mm
wet season from September to December only
1967–1989 and 1993–2006 – the reference periods
1990–1992 – the post-fire period