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Cn 6 th14_aveiro_modelling_runoff_and_erosion_in_a_fire-prone_environment_coelho

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  • Mitigation strips with fire-resistant species, understorey management, controlled tree spacing etc
  • Seasonal fluctuations in fire probability (per month), averaging about 2%/month
    Highest probabilities tend to fall a little after a fire, but esentiaslly an annual cycle.
    Blue dots are random fires actually geenrated (9 in 50 years)
  • Between fires, erosion rate almost unchanged (c. 3 T/Ha/yr)
  • In this environment:
    Average 25% increase in erosion due to wildfires, but this can be masked by variations in the weather
    Effect best seen by comparing paired catchments – with and without fire
  • Transcript

    • 1. Esteves, T.C.J.1 ; Ferreira, A.J.D.1 ; Soares, J.A.A.2 ; Kirkby, M.J.3 ; Shakesby, R.A.4 ; Irvine B.J.3 Ferreira, C.S.S.1 ; Coelho, C.O.A.2 , Carreiras, M.A.1 1 Dpt. of Environment, Escola Superior Agrária de Coimbra, Coimbra, 3040-316, Portugal 2 Dpt. of Environment and Planning, Universidade de Aveiro, Aveiro, 3810-193, Portugal 3 School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom 4 Dpt. of Geography, Swansea University, SA2 8PP, United Kingdom Modelling runoff and erosion in a fire-prone environment LANDCON October 2010 Mjk: Slide 1 Background To Portguese study sites To PESERA model Application of PESERA to post-fire responses
    • 2. Fires and soil degradation LANDCON October 2010 Mjk: Slide 2 Dry summer vegetation Wild fires Accidental Ignition Increased Soil Erosion Re-growth of Vegetation Irreversible soil degradation Loss of fine earth and nutrients Seasonal climate Positive Impact Sustainable Un-sustainable
    • 3. LANDCON October 2010 Mjk: Slide 3 Location of study areas in Portugal
    • 4. Land degradation after fires in the Caratão catchment study area LANDCON October 2010 Mjk: Slide 4 Former forests of Pinus Pinaster and Eucalyptus globulus. 70% burned 1998-2005 Steep (>20o ) stony cambisols over metamorphic rocks
    • 5. Experimental fire in Vale Torto catchment on February 20th 2009 View of the catchment near Góis, 4 months after the prescribed fire LANDCON October 2010 Mjk: Slide 5 • Catchments monitored before & 2 years after fire for infiltration, runoff , sediment yield and vegetation • Control catchment monitored in parallel over the same period • Main measures adopted were preventive forestry
    • 6. The DES!RE Project • Look at degradation and conservation in an integrated way • Improve indicators of soil degradation status • Develop promising mitigation/ remediation methods for each area with stakeholders • Evaluate effectiveness of measures locally • Use models to evaluate potential effectiveness for a wider surrounding areaLANDCON October 2010 Mjk: Slide 6
    • 7. Preventive forestry conservation measures LANDCON October 2010 Mjk: Slide 7
    • 8. Biophysical model based on PESERA (Pan-European Soil Erosion Risk Assessment) • A previously developed coarse scale model to provide an estimator of soil erosion risk at the regional scale • Applicable at 1 km resolution with existing pan-European data , but OK down to c. 100m with better data from study sites. • Explicit physical basis originally designed primarily to – i) monitor regional distribution of erosion risk and – ii) examine future risk under climate/ land use scenarios. • Potential to apply observed rainfall and compare with observed erosion rates for calibration/ validation • Continued support through current EU projects (DES!RE, DESURVEY, MIRAGE) • Potential to provide outputs for biomass, Soil organic Matter, moisture status and water quality LANDCON October 2010 Mjk: Slide 8
    • 9. LANDCON October 2010 Mjk: Slide 9 Gridded (50 km) Climate Data or Rf, Temp & Pot E-T Vegetation Biomass (kg/m2 ) Runoff and Climate/Vegetation Erosion Potential, Ω Combined Erosion, kΛΩ DigitalSoil,land-useandGeology mapsat1:500000 Topographic Potential, Λ DTM (50-250m grid) Erodibility, k Runoff Water balance (SMD) Soil Storage Ground Cover: Compare with AVHRR Partitioning of hydrology ET
    • 10. Main PESERA Input data sources at 1 km resolution Parameter Default Source for Europe Grid Res’n Climate Daily rainfall Potential E-T, Temp MARS 50km Soil Texture, crusting, erodibility, water storage capacity, Effective depth (m) European Soil Database 1km Land use Category of use, crop, planting dates, rooting depth, initial cover, water use efficiency CORINE 2000 250m 1km Topography Standard deviation of elevation around each SRTM 90m LANDCON October 2010 Mjk: Slide 10
    • 11. Legend estimated annual erosion (t/ha/yr) 0 0 - 0.5 0.500000000 - 1 1.000000001 - 3 3.000000001 - 5 5.000000001 - 10 10.00000001 - 30 30.00000001 - 50 Primary output from PESERA model LANDCON October 2010 Mjk: Slide 11
    • 12. Modifications to PESERA to model fire response• Fire Ignition & Spread – Fire Danger Index (FDI) calculated from Temperature, Temp. Range and number of dry days in each month – Number of fire start-ups estimated from visitor numbers and frequency of lightning strikes (generally unimportant in Europe) – Probability of fire = No of Start-ups x FDI – Area & Intensity of fire increases with wind speed and decreases with fuel load (biomass) and its moisture content. • Post-fire erosion and recovery – Partial destruction of Biomass, Cover and Soil Organic Matter in response to severity of burn, increasing post-fire erosion rate – Some delay in erosion onset as highly absorbent ash layer wets up – Additional Increase in post-fire erodibility due to more disturbed available material. This component reduces in proportion to subsequent rainfall amounts. – Regrowth of vegetation and cover (using existing routines) associated with further reduction in erosionLANDCON October 2010 Mjk: Slide 12
    • 13. Fire probability and occurrence in an example 50 year period LANDCON October 2010 Mjk: Slide 13
    • 14. Cumulative 50-year erosion with and without wildfires LANDCON October 2010 Mjk: Slide 14 With wildfires: Fires shown in red (Value indicates fire area) Without wildfires Largest non-fire erosion event (240 mm in month: 49 mm in day) Erosion event increased following major fire (210 mm in month: 25 mm in a day)
    • 15. LANDCON October 2010 Mjk: Slide 15 Conceptual model of post-fire response
    • 16. Example 10-year time series with and without random fires LANDCON October 2010 Mjk: Slide 16 Largest erosion event when heavy rainfall coincides with a moderate-sized fire With wildfires –fires are black spikes No wildfires –same climatic sequence Largest fire damages vegetation – takes 5 years to recover Largest non-fire erosion event - impact almost unchanged
    • 17. Four realisations of 50 -yr wildfire regime. Climate is the same, and only random fire occurrence changes LANDCON October 2010 Mjk: Slide 17 Vertical scales approximately the same. Red dots indicate timing and area of fires
    • 18. LANDCON October 2010 Mjk: Slide 18 Variability due to weather and random incidence of wildfires Range with fires Range without fires
    • 19. Interval between managed fires and average biomass & erosion LANDCON October 2010 Mjk: Slide 19 Erosion level with no fires Biomass level with no fires Number of wildfires almost unchanged , but less severe As interval between managed fires decreases (to the left), average biomass is decreased, erosion is reduced, but wildfire are as frequent, though smaller in area and less in severity
    • 20. Effect of a 2o C temperature rise in this Portugal environment • Increases potential E-T (50%) • Increased Winter Actual E-T (15% over year) • Slight increase in Biomass • Slight decrease in Soil Organic Matter • Slight decrease in Soil Erosion without Fires • 20% Increase in Fire frequency and severity, but re-growth in winter after fires is more rapid • Ratio of erosion with : without fires increased, but the total rate is not as high as at present.LANDCON October 2010 Mjk: Slide 20
    • 21. Conclusions • Modelling is able to simulate at least some of the major interactions between fire and erosion • Most important effects not yet incorporated: – Thinning of soil and irreversible soil loss – Hydrophobic increases immediately after fire • Main effects shown by modelling – Response to fires is very strongly dependent on the magnitude of immediately following storms – Prescribed fires reduce total erosion, but not necessarily the number of small wildfires LANDCON October 2010 Mjk: Slide 21
    • 22. LANDCON October 2010 Mjk: Slide 22
    • 23. Components of PESERA model LANDCON October 2010 Mjk: Slide 23 Land Cover Soil TypeClimate Topography Storm Runoff Threshold Distribution of Storm and Non- storm Runoff Saturated Subsurface Flow, Snowmelt and Frozen Ground Runoff Erodibility Relief Accumulated Erosion

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