Irrigation is an indispensable technology used to augment agricultural production in the semi-arid and arid regions of the world. Due to poor water management, including unsuitable location of water reservoirs and supply channels, water logging, perched water tables and secondary soil salinization is the consequent land degradation. In order to minimise the onset of irrigation induced salinization, biophysical information is required to map the various causal factors. This includes, land use, geology, hydrology, climate and topography. In the last 10 years this type of biophysical information is increasingly being generated and used in Geographic Information Systems (GIS) to identify salinity hazard. Unfortunately and due to the high cost of acquiring quantitative information, Government Agencies rely upon qualitative maps generated at regional levels and catchment scales. The result is the production of maps of low accuracy and interpretability at the district and land management scale. In addition, the salinity hazard maps are biased in that weightings are assigned based on expert knowledge about which biophysical factors are most significant in producing secondary soil salinization. In irrigated agricultural districts more detailed information is required. The approach used in this paper involves the development of quantitative biophysical data layers (i.e. land use, hydrology, geology, etc.,) at the management level. For example, and with respect to the hydrology, a relationship is established between electromagnetic induction signal data (i.e. EM38 and EM34) and simple salt-water balance models to map deep drainage and groundwater recharge. This information along with other data layers is stored in GIS format and is used with local knowledge to develop a salinity hazard map in the lower Macquarie valley, New South Wales Australia. The results show that the methodology identifies current areas of secondary salinization and suggests where further work is required to assess the potential hazard.