INTEGRATED GROUNDWATER-SURFACE WATER MANAGEMENT: A MODELING APPROACH TO EXPLORE SOCIOECONOMIC OPPORTUNITIES AND ENVIRONMENTAL IMPACTS IN AN OVER-ALLOCATED SYSTEM

In Australia, an over-allocation of water resources has led to the implementation of water reforms. Consequently policy makers have set reductions in surface and groundwater allocations, which have social, economic and environmental consequences that vary spatio-temporally within catchments. Catchment managers and the planning process require a means of assessing the likely impacts of water allocation decisions in a changing environment.

The presentation reports on a project that engages the expertise of industry and government interest groups within the Murray-Darling Basin's Namoi Catchment, in New South Wales, Australia. The Namoi is an important agricultural region and has one of the highest levels of groundwater extraction in Australia. The Lower Namoi Catchment, being the focus of this presentation, is an alluvial floodplain occupying an area of 5,100 km². The project combines integrated systems modelling with stakeholder engagement to encourage knowledge sharing and the identification of major risks, and to enable the exploration of opportunities for policy and landholder innovations. The integrated approach allows the simulation of socioeconomic, hydrological and ecological outcomes arising from key drivers including climate, water policy, farm production, and innovations in water use efficiency.

The main components of the project, which are stakeholder engagement, understanding and representing farmer decision making, the ecological assessment approach, and modelling of surface-groundwater interactions will be covered. But the presentation will focus particularly on the development of a catchment-scale model of connected surface-groundwater systems suitable for integration with socioeconomic modeling and river ecosystem modeling. The key challenge in developing the model is to identify an appropriate level of spatial aggregation and parameterisation that provides a satisfactory prediction of river flows, given the uncertainties in modelled output and observed data. There is also significant uncertainty surrounding the modelled outcomes due to the complexity of the management problem. Management of these uncertainties will be discussed.