Quantum Technology based hydrological Sensor Networks

Increasing global pressures on freshwater ecosystems and rapid environmental change are jeopardizing critical, life-supporting ecosystem services. The highly dynamic and often non-linear behavior of (eco)hydrological processes pose unique challenges in understanding, monitoring, and conserving freshwater ecosystems. Moreover, currently available modelling and management tools have been developed under an assumption of stationarity - a boundary condition that no longer holds in the context of global change. Complex process interactions often cause hydrological processes to show pronounced temporal dynamics and exhibit marked non-linear behavior in response to environmental change. Such behavior manifests itself by the occurrence of distinct thresholds, tipping points or hot moments, periods of enhanced (re)activity, and rapid regime shifts, but may also be associated with pronounced spatial heterogeneity, producing locations of enhanced activity or hot spots.

Current monitoring technologies provide very limited capacity to observe such non-linear and non-stationary process behavior at adequate spatial and temporal scales and resolution. Therefore, this PhD project will build on recent advances in sensor platform and network technologies to better capture non-linear hydrological process behavior. Therefore, the project will combine the core skills of the Quantum Technology Hub at the UoB School of Physics and Astronomy (Prof. K. Bongs) with the sensor network and smart tracer facilities and expertise at the School of Geography, Earth and Environmental Sciences (Prof. D.M. Hannah, Prof. S. Krause, Prof. J. McDonnell).