Reactive management responses to sensor data
Coupling telemetered sensor networks to data analytics solutions will be needed to enable the development of dynamic visualisation dashboards, providing environmental managers with unprecedented insights into the real-time status of the whole river network. These sensor systems also present new opportunities for the democratisation of catchment data with public-facing web-hosted applications. By engaging the public in the process, initiatives that improve insights into water quality by enhancing the level of detail and coverage in both space and time supplement the data generated by scientists and government organizations. To achieve this, it is crucial to establish and distribute appropriate and consistent protocols to the public (Amador-Castro et al., 2024). With additional potential for alerting citizen scientists, reliable information on water quality could be obtained quickly during events, increasing the spatiotemporal resolution and complementing the data produced by scientists and government institutions. As ML methods improve, the ability to upscale from localised data collection points in space, and to robustly infer system dynamics over time where data gaps exist (Segatto et al., 2021), offers potential for significant improvements in both reactive and proactive management (Figure 2). Predictions of future conditions (forecasting) will become possible, similar to recent advances applied to standing freshwaters (Lofton et al., 2023), enabling improved responses to future problems. Sensor data can be used directly or aggregated to develop metrics for evaluating the ecological status of a river section. Such data will be used together with information on water quality and discharge to support decisions on water management, especially by elucidating links between water quality, ecosystem respiration, and carbon emission.