PhD defence: Anne Lausten Hansen

Anne Lausten Hansen defends her thesis

Spatially distributed nitrate reduction potential in the saturated zone in till areas - Challenges and uncertainty assessment

Supervisors
Professor Karsten Høgh Jensen, IGN
Research Professor Jens Christian Refsgaard, GEUS

Assessment committee
Professor Peter K. Engesgaard (chairman), IGN
Senior Hydrologist Thomas Harter, UC Davis - USA
Professor Michael Rode, Helmholtz Centre for Environmental Research, UFZ - Germany

Abstract (shortened)
The topic of this PhD study was modeling of spatially distributed nitrate transport and reduction at catchment scale, which is of interest in order to delineate so-called nitrate sensitive and nitrate robust areas with respectively low and high nitrate reduction potential. The research firstly focused on some of the main challenges in this topic: to estimate the depth of the redox interface and to accurately simulate local scale water flow patterns. These two issues are important since they control how much and where nitrate is reduced in the saturated zone. Secondly, the study also looked into the uncertainty on the estimated nitrate reduction potentials and evaluated on the predictive capability of catchment scale models. Among other results, the study found that geological uncertainty give rise to large uncertainty on the predicted nitrate reduction at grid scale, but the uncertainty decreased with increasing scale. The decrease in uncertainty was found to be largest at small scales and then leveled off at a scale corresponding to the mean length of sand lenses in the study area, indicating that the spatial resolution of the geology is constraining at what spatial scale a distributed model has predictive capabilities. The main outcome from this PhD research was that nitrate sensitive and nitrate robust areas can be predicted using a physically-based distributed model, but since catchment models most often lack predictive capabilities at grid scale the uncertainty on the estimated nitrate reduction potential at grid scale is large. It should therefore be evaluated at which spatial scale the predicted nitrate reduction potential can be used. The reason for the lack of predictive capability at grid scale is insufficient description of spatial patterns of parameters and input data in the models. In particular, it is important to describe the spatial variation in the location of the redox interface and the local scale geological heterogeneity, which control the local scale groundwater flow patterns, in the model

The thesis is available from the PhD administration office 04.1.409