The project has created scientific progress through individual secondments, facilitating the supra-disciplinary aims and objectives. From March 2020 until the end of the (extended) funding period, the undertaking of in person secondments became impossible due to COVID19 lockdowns and later restrictions to the movement between different countries that prevented the international as well as inter-sectoral exchange in the action, at least in person. The project leadership team efforts during this time were on ensuring the safety of project participants that were on active secondments and providing support to best conduct research while under local lockdown.
To mitigate these COVID induced limitations, a first project extension was applied for and granted, however, travel between participating countries and institutions hadn’t resumed in time. A second project extension was unfortunately not granted, preventing the project from implementing outstanding secondments. The main emphasis of the network has therefore been on trying to deliver as much as possible of the planned actions and deliverables without being able to actually conduct in-person secondments during this time.
WP 3 facilitated the development, testing and validation of in-situ sensor technology for high-frequency and high-spatial resolution monitoring. During the 2nd project period covered by this report, the research team endeavoured to further develop the new concepts initiated in the first project phase in the joint networking of multiple property sensors under dynamic flow conditions, and advanced capacities in monitoring the dynamic breakthrough of reactive fluorescence tracers under variable discharge and turbidity conditions. We used joint up approaches were used to deploy those innovations locally when project exchanges through secondments became impossible.
From first phase innovations, WP 4, focused on developing novel approaches for integrating high-frequency sensor technology for large-scale distributed sensor network monitoring. The main focus in this phase has been on creating automated calibration and validation scripts for the optimised analysis of fluorescence tracer breakthrough curves, the results of these have been published.
WP 5 aimed at providing innovative statistical approaches and modelling techniques for efficiently handling, processing and analysing complex sets of big data with variable frequency and resolution. We have been focussing on developing algorithms for the synthesis of the large interdisciplinary data sets generated in project and designed automated analysis methods for microbial metabolic activity tracers, and simulated nutrient dynamics in rivers using high-frequency nutrient data to reassess prior nutrient models.
Finally, WP 6 focussed on developing strategies for visualising and aiding decision making based on high-frequency environmental sensor network monitoring and adaptive modelling approaches. These developments were conducted to better guide real-time responses to multiple environmental stressors. Building on the first phase advances, we created predictive understanding of river corridor exchange: standardization of metadata, critical evaluation of the information content and support volumes for measurement techniques, multiscale model-data integration, and advancing theoretical models of river corridor exchange.
