Integrating high-resolution tracer data into lumped conceptual rainfall-runoff models
PublisherUniversity of Aberdeen
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Environmental change is currently regarded as one of the greatest threats to water resources. Limited knowledge of hydrological processes prevents from adequate characterization of systems behaviour to future changes. Geochemical and isotope tracers are considered reliable tools to study physical processes, but tracer studies are often constrained by the temporal and spatial variability in the tracer response and coarse data sets. Novel automatic sampling devices and inexpensive laser spectroscopy made higher-resolution stable isotope tracer data feasible. This thesis presents approaches to integrate geochemical tracer data, high-resolution stable isotope tracer data and process dynamics observed in the field into lumped conceptual rainfall-runoff models to study catchment hydrological processes at different scales. The use of such process-based data successfully aided model conceptualization and calibration in the quest for simple water and solute transport models with improved representation of process dynamics. In particular, high-resolution isotope data could identify temporally and spatially variable flow pathways to assess diffuse pollution transport, which otherwise might have been lost. This work showed that pollutants in some catchments are likely to rapidly discharge into the stream and due to geological properties reside over longer periods in deeper groundwater systems. In other words, changes to these systems today are likely to show an immediate effect fading persistently over decadal time periods. Such knowledge is important if catchment remediation and recovery has to be assessed from a management point of view such as for example targeting measures and cost-effective land management to improve water quality status.