Using E2 to Model the Impacts of Bushfires on Water Quality in South-Eastern Australia

Approximately 1.3 million ha of forested and agricultural land in eastern Victoria, Australia, was burnt by bushfires in early 2003. The impact of these fires on the water quality in rivers and storages has the potential to be significant. This paper describes a modelling process to assess the impacts of the fires on water quality of receiving waters and river systems in the fireaffected catchments. More specifically, this study set out to; 1. Construct and parameterise models using the E2 catchment modelling framework to represent the flow, and sediment and nutrient loads for the water storages and river systems in fire-affected catchments in eastern Victoria. 2. Assess the likely impacts of the fires on loads of total suspended sediments (TSS), total nitrogen (TN) and total phosphorus (TP) in the water storages and rivers of the fire-affected catchments. E2 is a modelling framework that provides a flexible approach to whole-of-catchment modelling. It allows the creation of integrated models through the process of selection and linkage of component models. E2 may be configured to predict flow and constituent sediments and nutrient loads at any point in a river network over time. Digital elevation models (DEM) of the four catchments were imported into E2, and subcatchment boundaries were delineated. Rainfall surfaces derived from spatial interpolation of ground-based observation data onto a 5 km x 5 km grid was pre-processed to provide a weighted average daily rainfall for each sub-catchment. Data of long term mean monthly potential evapotranspiration (PET) was also used as inputs to the rainfall-runoff models. Model parameters were determined by calibration against observed flows at stream gauging stations. Digitised landuse layers were reclassified in E2 to form three functional units (FU?s); Forest, Agriculture and Other. A second digitised landuse layer incorporating the burnt areas was imported into the model to create a ?burnt? scenario. Values of constituent concentration (for dry weather concentration, DWC, and event mean concentration, EMC) were applied to each FU so that predicted loads equalled the loads calculated from pre- and post-fire water quality data at monitoring stations within each catchment. Pre- and post-fire loads of TSS, TN and TP predicted by the model at points of interest (catchment outlets and water storages) were then compared in terms of the relative long term changes (rather than absolute changes) in loads. These predictions of load increases carry important assumptions and limitations including; outputs are long term averages, no allowance has been made for changes in streamflow, for recovery of vegetation, or for the storage, deposition or remobilisation of sediments and nutrients. Furthermore, there are uncertainties with the constituent data used to calibrate the model, assumptions were made when assigning values of DWC and EMC to FU?s, and assumptions were made on behaviour of constituents in water storages. Proportional increases in loads at the catchment outlets were generally smaller than increases observed at the water quality monitoring sites. These differences reflect the proximity of the monitoring stations to the burnt areas, the total percentage of catchment burnt, and the amount of rainfall. The model predicted that, compared to pre-fire conditions, the Ovens, Kiewa, Hume and Snowy catchments would deliver, on average, approximately 27 times greater TSS, 4.9 times greater TN, and 7.9 times the amount of TP.