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.