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Abstract: Economic analysis of climate scenarios and alternative water policies is critical for development and implementation of appropriate water policies and programs. Mathematical models have been developed to assess water resources policies due to their ability to explicitly represent the biophysical dynamics of natural systems while integrating these within social and economic constraints. These models have been criticised, however, due to the problems of simplification, overspecialisation, plausibility and lack of empirical validation. This paper introduces a mathematical programming model which uses positive mathematical programming method to calibrate and model agriculture and water use in the Murray-Darling Basin of Australia. This paper reviews the theoretical and technical details of the model development including the key steps taken in collating and scaling the biophysical and economic data, and to address model parameterisation issues. The paper summarises results of an application of the model for assessing climate change impacts in the form of reduced rainfall and water allocations and increased crop water use for agricultural production. The results show the degree of variability in gross values under different climate scenarios compared to the base case scenario, especially in very dry years. The results also show how on-farm adaptation options and water markets can mitigate these losses. [Copyright &y& Elsevier]

Abstract: Regional-scale ecological restoration priorities such as increasing the extent and quality of native vegetation are generally planned at catchment scales, while on-ground restoration actions are generally implemented at paddock or farm scales. This paper describes the use of spatial multi-criteria assessment methodologies to construct maps of regional conservation priorities and assesses how these maps map influence farm-scale actions in Western Victoria, Australia (e.g. farm-scale revegetation for salinity, wind erosion, stock shelter, etc). The study also incorporates agricultural production in the decision analysis through the use of historical yield mapping data obtained from harvest logs from precision agriculture equipment. Via a stakeholder workshop, farmer land use priorities were elicited with and without access to maps of regional conservation priorities. Results highlight that production imperatives drive farmer-led conservation actions and that regional conservation priorities have only limited impact on actions. The paper also identifies limitations of applying MCA methods across multiple decision-making scales such as the need to generalise priorities where domain knowledge is relatively high, and the challenges associated with MCA criteria definition. [ABSTRACT FROM AUTHOR]

Abstract: Approximately 1.3 million ha of forested and agricultural land in south-eastern Australia was burnt by wildfires in early 2003. This paper describes a modelling process to assess the impacts of the fires on the quality of receiving waters and river systems in the fire-affected catchments. First, we construct and parameterise the E2 catchment modelling framework to represent the flow, and sediment and nutrient loads for the water storages and river systems in fire-affected sub-catchments and second, we assess likely impacts of the fires on loads of total suspended sediments (TSS), total nitrogen (TN) and total phosphorus (TP). Very good calibration (with coefficient of efficiency values generally greater than 0.8) of the rainfall-runoff models to observed flow at several gauging stations within each catchment was achieved. Digitised land use layers were reclassified to form functional units representing unburnt and burnt land uses. Pre- and post-fire loads of TSS, TN and TP predicted by the model at end of catchment outlets and water storages were then compared relative to pre-fire loads. Compared to pre-fire conditions, the models predicted that the Ovens, Kiewa, Upper Murray and Snowy catchments would deliver, on average, approximately 30 times greater TSS, 5 times greater TN, and 8 times the amount of TP. Proportional increases in predicted loads at the catchment outlets were generally smaller than increases observed at 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 predictions of load increases carry important assumptions and limitations, and such an approach can only be used for making relative assessments of the impacts of the fires on average suspended sediments and nutrient loads. [Copyright &y& Elsevier]

Abstract: Disturbance of forested catchments by fire, logging, or other natural or human induced events that alter the evapotranspiration regime may be a substantial threat to domestic, environmental and industrial water supplies. This paper describes the physically-based modelling of the long term changes in water yield from two wildfire affected catchments in north-eastern Victoria, Australia, and of fire and climate change scenarios in Melbourne''s principal water supply catchment. The effect of scale, data availability and quality, and of forest species parameterisation are explored. The modelling demonstrates the importance of precipitation inputs, with Nash and Sutcliffe Coefficients of Efficiency of predicted versus observed monthly flows increasing from 0.5 to 0.8 with a higher density of rainfall stations, and where forest types are well parameterised. Total predicted flow volumes for the calibrations were within 1% of the observed for the Mitta Mitta River catchment and <4% for the Thomson River, but almost −10% for the less well parameterised Tambo River. Despite the issues of data availability simulations demonstrated the potential for significant impacts to water supply in SE Australia from wildfire and climate change. For example, for the catchments modelled the moderate climate change impact on water yield was more pronounced than the worst fire scenario. Both modelled cases resulted in long term water yield declines exceeding 20%, with the climate change impact nearing 30%. A simulation using observed data for the first four post-fire years at the Mitta Mitta River catchment showed Macaque was able to accurately predict total flow. [Copyright &y& Elsevier]

Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia). [Copyright &y& Elsevier]