Irrigation is an indispensable technology used to augment agricultural production in the semi-and and arid regions. However, poor water management (eg. unsuitable location of reservoirs) can lead to the creation of perched water tables and secondary salinisation. In some irrigated areas in the northern Murray Darling Basin, point-source salinisation has occurred (Trialnaillis et. al. 2003a) whilst in others there is little or no evidence. This is because waterlogging and salinisation occur as a function of interactions between various biophysical factors such as agronomy, geology, hydrology, climate and topography. In order to determine where these problems may arise, biophysical features that are influenced by agronomic practices need to be generated. Stored in Geographic Information Systems (GIS), the interaction between biophysical data layers can be related to where salinisation occurs, and where these conditions may be met elsewhere. Recently airborne geophysical methods have been used to develop layers (eg. National Dryland Salinity Program). The start-up-cost of around $7-121ha is prohibitive. Alternatively, salinity hazard and risk maps are being produced at catchment level (e. g. State Government Agencies) using qualitative soil/geology data and land use information. The results may lead to maps of low accuracy/interpretability. A major reason for this is that weightings given to particular biophysical layers are subjective (i. e. assigned by so-called experts). In the following paper we describe the development and spatial distribution of deep drainage (DD) risk, average clay content (0-7 in) and average salt store (0-10 in) in the cotton growing districts of Trangie and Warren in the lower Macquarie valleys of central New South Wales (see Figure I). By doing this we mapped individual biophysical layers thought to contribute to the causes of water logging at a site where soil salinisation was first reported in the Trangie district in the early 1980&#39s. Critical values thought to cause salinisation were determined: a) DD risk is greater than 0.5 beneath water reservoirs; b) average clay content (0-7 in) > 38 %; and, c) average salt store (0-10 in) > 2.5 dS/in. By using GIS type analysis we mapped where these three conditions would be met and hence create salinity hazard maps associated with the construction of reservoirs. The results are consistent with areas where salinity has been experienced. The maps also indicate where best management practices developed in Trangie district could be extended.