Modelling water quality and ecosystem metabolism in regulated rivers

Wide-spread flow regulations have modified rivers globally through changes in multiple environmental stressors that regulate ecosystem processes such as metabolism. Despite ubiquitous river regulation, current metabolism models do not include multiple stressor influences. Additionally, these models were developed for estimation at reach-scale, thus limiting our ability to predict metabolism across expansive river catchments. This thesis aims to expand ecosystem metabolism estimation to regulated rivers, which is achieved by developing two river segment-scale models. The first model, hourly QUESTOR (Quality Evaluation and Simulation Tool for River-systems), supports metabolism estimation in multi-stressed lowland rivers with flow and water quality regulation. Using a case study of the River Thames in England, I demonstrated the model's application for estimation of metabolism and of its controls such as flow, water temperature, light availability, nutrients and biomass. Comparing this model with statistical modelling provided insights into the multiple stressor controls of metabolism in lowland, regulated rivers. The model also segregates biochemical respiration pathways as well as estimates metabolism at sites without regular monitoring and/or under changing climate-management conditions. The second model, MUFT (Metabolism estimation in rivers with Unsteady Flow conditions and Transient storage zones), was developed by coupling an unsteady flow routing model and a solute transport model with the two-station metabolism model. I applied the model along a river stretch downstream of a hydropower plant in the River Otra in Norway. The MUFT model presents a parsimonious approach to estimate metabolism for the first time in hydropeaking environments and/or transient storage zones. Comparing both models, I made recommendations for metabolism modelling in regulated rivers and outlined directions for future research. The modelling approaches presented here unlock new possibilities for broad-scale metabolism estimation across diverse river environments, which in turn will help reduce uncertainties in our global estimates of freshwater carbon fluxes.