The Spatial optimisation Model for Analysing Catchment Management (SMAC) has been developed to examine the relationship between groundwater accessions from agricultural land, land salinisation and its medium-term economic effects. This mathematical programming model represents the farm and catchment-scale aspects of land management. The model quantifies the relevant inter-relationships between socio-economic conditions, including the economic and policy environment affecting farms, and the biophysical condition of the catchment, including agronomy, hydrogeology and soil salinisation. The SMAC model was chosen as the catchment-modelling tool in an ACIAR project on salinisation to be carried out by a research team headed by the University of Technology, Sydney and, in Thailand, the project will involve Khon Kaen University, The Royal Forest Department and the Land Development Department of the Ministry of Agriculture and Cooperatives. SMAC will be applied for hydrological, economic and social modelling, at catchment and other scales to evaluate the impact of revegetation in Thailand (Lam Pao and Khorat and Australia (Liverpool Plains and Upper Macquarie Valley). This paper describes the SMAC model and discusses the methodological and other challenges of applying it in other regions with different land-use systems, economic conditions and hydrology, and a data-sparse environment