Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.

BG6.2
Advancing understanding of hydrochemical and ecological processes in freshwater ecosystems using high-frequency measurements with sensors, wet-chemistry analysers and lab-on-a-chip instruments
Co-organized as HS10.12
Convener: Magdalena Bieroza | Co-conveners: Per-Erik Mellander, Michael Rode

The last two decades have brought a major technological advancement in collection of water quality and biogeochemical data in streams, rivers and lakes using automated in situ wet-chemistry analysers, optical sensors and lab-on-a-chip instruments. Matching the water quality measurement interval with the timescales of hydrological responses (from minutes to hours) led to discovery of new hydrochemical and biogeochemical patterns in streams along with improved understanding of the underlying processes e.g. concentration-discharge hysteresis and diurnal cycling. We are now at the frontier of further advancing this understanding for a wide range of solutes and particulates in streams, rivers and lakes using rapidly developing technology of wet-chemistry analysers, optical sensors and lab-on-the-chip instruments. This is an exciting opportunity to gain new knowledge of stream hydrochemical and ecological functioning.

This session aims to discuss the most recent advances in sensor technology, application and acquired knowledge of stream water quality and underlying chemical and ecological processes. We invite presentations in the following topics:
• Understanding chemical and ecological patterns and processes observed with in situ sensors
• In situ deployment of sensors in streams, rivers and lakes
• Advances in sensor technology
• Quality assurance and uncertainty in the sensor measurements
• Statistical and pattern recognition analysis of sensor data
• High spatial and temporal resolution water quality chemical and ecological monitoring with sensors
• Using sensor data for calibration and validation of stream water quality chemical and ecological models