Abstract
Constructive engagement with farming stakeholders around diffuse nutrient pollution remains an ongoing global sustainability challenge. Using a participatory action-research approach, this study integrates multi-year, high-frequency nitrate-sensing across three North Queensland sugarcane catchments (Herbert, Tully and Russell-Mulgrave) to examine whether digital sensing technologies, by delivering water quality information at scales relevant to farmer decision-making, can help break down long-standing barriers to farmer engagement with water quality science. Networks of nested, sub-catchment-scale nitrate-sensing stations delivered near-real-time data to farmers via a bespoke web application. Fine-scale monitoring resolved distinct land-use water-quality signatures and linked fertiliser timing and rainfall to nitrate loss at event scale, and identified 'hotspot' sub-catchments exporting two-to-three times the dissolved inorganic nitrogen (DIN) load of neighbouring areas within two-to-three years. At the paddock scale, a legume-adjusted, lower fertiliser-rate treatment lost less than half the nitrate of conventional practice during a monitored runoff event. From these experiences, we develop a transferable adaptive learning model — co-design, observe, discuss, attribute, shift — that couples fine-scale real-time data with structured social learning to make cause–effect relationships between practice and water quality observable, timely and locally attributable. Research within the broader program has further associated this participatory, trust-based approach with increased farmer confidence in water quality science and greater willingness to undertake practice change. Sensing technologies show clear promise as an engagement tool, though realising that promise depends on sustained investment in the participatory and trust-based foundations within which the technology is embedded.