With the advent of Wireless Sensor Networks, the ability to predict nutrient-rich discharges, using on-node prediction models, offers huge potential for enabling real-time water reuse and management within an agriculturally-dominated catchment Existing discharge models use multiple parameters and large historical data which are difficult to extract and this, coupled with constraints on network nodes (battery life, computing power, sensor availability etc.) makes it necessary to develop low-dimensional models.