Phosphorus is a key irreplaceable nutrient that plays a major role in crop nutrition. The mineral form of phosphorus fertiliser is a mined resource and its supply comes predominantly from geopolitically sensitive parts of the world. A renewable source of phosphorus such as biosolids therefore offers a sustainable option. Nevertheless, continuous application of biosolids needs to be managed to ensure that soil is not saturated with nutrients which can then become a cause for concern in terms of enrichment of water bodies in the event of an erosion. Existing field trials have demonstrated the efficacy of biosolids as phosphorus fertiliser to meet crop demand whilst maintaining an environmentally safe amount in the soil. However, field trials are expensive, and an alternative would be a geospatial tool that builds on such information to act as a decision support tool to determine suitability of land to receive biosolids whilst ensuring that phosphorus levels are in environmentally safe limits. Thus, a novel and evidence-based decision support method for assessing land suitability for biosolids application at a national scale known as the Phosphate Acceptance Map (PAM) is described here. It provides a sound basis for addressing this need, layering over the model the means to capture a range of realistic scenarios, developed with industry practitioners, to allow exploration of the consequences of different land management strategies. The research method has involved the development and application of a modelling approach for phosphate acceptance, drawing from a collation of the core geographical and descriptive data themes required. These data describe both the environmental characteristics of the land under assessment, as well as the expression of nominal stakeholder values and protected areas. In considering the methods, it may be noted that the modelling drew upon key empirical data themes as a pragmatic approach. A number of key national datasets have been utilised such as the National Soil Map (Natmap), the ‘National Soil Inventory’ (NSI), geology and land use, as well as topography and prevailing climatic data. Demographic data was used to calculate potential arising nationally which was coupled together in the context of fertiliser recommendations. The issues addressed in the PAM modelling span borders and thus, where the data required is forthcoming, the methods demonstrated also have the potential to support wider application in other national contexts.