Hydrologic and biogeochemical signatures in intensively managed catchments: data synthesis and development of a passive surfacewater quality sampler

This study presents a conjunctive data synthesis and technology development approach to aid in enhancing understanding of the scaling behavior of water flow and nutrient transport in intensively managed agricultural catchments. Anthropogenic modifications to the landscape, with agricultural activities being a primary driver, have resulted in significant alterations to hydrologic and biogeochemical cycles. Significant research has been directed towards understanding and predicting the changes in these cycles in an effort to mitigate the associated adverse effects. Typical modeling efforts suffer from scaling issues associated with heterogeneities that arise at the catchment scale. New parsimonious approaches that rely on emergent patterns in data have been proposed to aid current modeling efforts. This study adopts a data synthesis approach to identify emergent patterns in hydrologic and nitrogen solute behavior in the context of agricultural activities at the catchment scale. The results of the synthesis indicate a strong anthropogenic signature in agricultural landscapes through (a) decrease in variability in the streamflow distribution with increase in the proportion of the catchment that is artificially drained and (b) relatively low variability in nitrogen concentration relative to discharge. Due to the dependence of such data synthesis methods on reliable data, a new method of data collection, through the use of an innovative passive sampling device, is developed to aid in future data synthesis and subsequent modeling efforts. Initial laboratory studies towards the development of the device achieved in this thesis indicate its ability to capture flow-averaged solute concentration over a specified deployment period. Future work involves testing the device under various field deployment conditions. The relatively low cost of the device would enable the estimation of spatially distributed flow-averaged concentrations that would complement existing costlier measurement methods, and significantly aid future modeling efforts and management decisions.