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.

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Presentation transcript:

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

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

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

Study area: the Ruisseau du Rimbaud at Collobrieres, France Area 1.46 km2; elevation 470 - 620 m; daily and hourly data available for 1968-2004 Mediterranean climate with intense autumn rains and summer drought Precipitation - 1200 mm/year, flow - 700 mm/year, PE - 900 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. 1996. 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. 2002 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

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

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)

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 1990 - November 1994 (Cosandey et al. 2005) Cosandey C, Andréassian V, Martin C, Didon-Lescot JF, Lavabre J, Folton N, Mathys N, Richard D. 2004. The hydrological impact of the Mediterranean forest: A review of French research. Journal of Hydrology 301:1–15

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

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 www.hydrograph-model.ru

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 1968-2004 0.52 0.76 NSE 1990-1992 0.45 0.76

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

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

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

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, % 30 0 interception storage capacity, mm 2 0 landscape albedo, % 20 10 coefficient of evaporation, 10-8hPa s 0.3 0.17 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 3.75 1.5 middle and lower layers 1.5 0.75 variation coefficient of infiltration 0 0.7

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.

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 1967-2004 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

Thank you for your attention!

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