Wildfire Impact on Water Yield Within Sydney's

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Wildfire Impact on Water Yield Within Sydney's Wildfire impact on water yield within Sydney’s drinking water supply catchments Jessica Heath, Chris Chafer, Tom Bishop, Floris Van Ogtrop AtAgroecosytems Group Faculty of Agriculture, Food and Natural Resources Background › PhD project: Wildfire impacts on hydrology within the Sydney drinking water supply catchments › Three components: • 1) Assessing the impact of the 2001/2002 summer wildfires on water yield within the Sydney drinking water supply catchments; • 2) The impacts of wil dfir e on soil w ater r epell en cy, vi a studyin g 2 si tes burn t in late 2009; and • 3) The role vegetation plays on the hydrological cycle post-wildfire 2 Background › Wildfire impact on the hydrological cycle › Victorian studies have demonstrated a change in water yield post-wildfire - Langford 1976 - Vertessy et . al. 2001 › Victorian and Sydney catchments obtain very different vegetation - Victoria: Obligate seeders - Sydney: Obligate resprouters 3 Research Objectives › Did the 2001-2002 summer wildfires have had an impact on the post- wildfire water yield? Average Average Average weekly Max Burnt weekly weekly Water Temp Area Catchment Rainfall (mm) yield (ML) (Degrees) (%) Pre Post Pre Post Pre Post Burke River 18 17 403 229 18.41 19.14 83.16 Erskine Creek 18 13 19 16 23.60 24.78 98.46 Glenbrook Creek 19 16 329 141 23. 60 24. 78 97. 23 Nattai River 7 7 453 224 18.41 19.14 57.05 Grose River 11 10 2181 1744 23.59 24.23 0 Kedumba River 20 21 325 211 16. 88 17. 73 0 Kowmung River 17 16 1778 984 16.88 17.73 0 = burnt 4 Research Objectives 5 Study area Grose River Four burnt and three control catchments Kedumba River Glenbrook Creek Burke – 83% fire Kowmung River affected Sydney Erskine- 98% fire Erskine Creek affected Lake Glenbrook- 97 % Burragorang fire affected Nattai River Legend Nattai – 57% fire Urban affected Reservoirs Burnt Study area Control BkBurke River 05 102030 Kilometers 6 Methods Sub-catchment delineation DiData processing Statistical Analysis 7 Methods Sub-catchment delineation › Drainage area above each hydrometric site was defined - Depressionless DEM by filling in artificial sinks - Calculate flow direction and flow accumulation maps which are used to determine the watershed above each hydrometric station 8 Methods Data processing › Data collected between the 1st January 1991 - 31st January 2010. - Hourly flow data: 7 hydrometric stations - Hourly rainfall data: Thiessen polygons were used to calculate total rainfall based of surrounding rainfall gauges - Max imu m daily temperatu re data: Data gathered from closest temperatu re gau ge to hydrometric station › All data was converted to weekly data through the use of R as daily intervals produced too much noise within the data › First 12 months of data immediately post-wildfire ignored due to missing dtdata- can bdthtiitildlldbe assumed that an increase in water yield levels occurred 9 Methods Statistical Analysis › Distribution considered - Generalized Additive Models (gam) • Guassian family • Gamma family 10 Methods Statistical Analysis › Predictor variables - Simple model: water yield, rainfall and temperature - Slightly more complex model: Extended simple model to include dummy seasonal variables (sine and cosine) - Most complex model: Lagged water yield were incorporated into the model › Post-fire data was predicted based of the pre-fire model . › Nash-Sutcliffe coefficient,,,, 95% confidence interval , flow duration curves, residual plots 11 Results Gamma data Catchment NSE* pre-fire NSE* post-fire Burke River 0.91 0.75 Erskine Creek 0.72 0.85 Glenbrook Creek 0.64 0.53 Nattai River 0.55 0.53 Grose River 0.90 0.41 Kedumba River 0.73 0.61 Kowmung River 0.63 0.33 * NSE ranges from -∞ to 1 12 Results Confidence Intervals 13 Results Flow duration curves 14 Results Residuals- burnt 15 Results Residuals- unburnt 16 Summary › Variation in water yield levels across both burnt and unburnt sites › Pre-wildfire models predict the post-wildfire models well › The FDC follow a similar trend across all sites › No trend in residual plots= wildfire has no obvious effect on water yield 17 References › Langford, K., 1976. Changes in yield of water following a bushfire in a forest of eucalyptus regnans. Journal of Hydrology 29, 87-114. › Vertessy, R.A., Watson, F.G.R., O’Sullivan,S.K., 2001. Factors determining relations between stand age and catchment water balance in mountain ash forests. Forest Ecology and Management 143, 13-26 Contact details: Jess Hea th, email : jh ea 2850@un i.sy dney.e du.au 18.
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