Abstract. The role that hydrology plays in governing the interactions between dissolved organic carbon (DOC) and nitrogen in rivers draining lowland, agricultural landscapes is currently poorly understood. In light of the potential changes to the production and delivery of DOC and nitrate to rivers arising from climate change and land use management, there is a pressing need to improve our understanding of hydrological controls on DOC and nitrate dynamics in such catchments. We measured DOC and nitrate concentrations in river water of six reaches of the lowland river Hampshire Avon (Wiltshire, southern UK) in order to quantify the relationship between BFI (BFI) and DOC : nitrate molar ratios across contrasting geologies (Chalk, Greensand, and clay). We found a significant positive relationship between nitrate and BFI (p < 0.0001), and a significant negative relationship between DOC and BFI (p < 0.0001), resulting in a non-linear negative correlation between DOC : nitrate molar ratio and BFI. In the Hampshire Avon, headwater reaches which are underlain by clay and characterized by a more flashy hydrological regime are associated with DOC : nitrate ratios > 5 throughout the year, whilst groundwater-dominated reaches underlain by Chalk, with a high BFI have DOC : nitrate ratios in surface waters that are an order of magnitude lower (< 0.5). Our analysis also reveals significant seasonal variations in DOC : nitrate transport and highlights critical periods of nitrate export (e.g. winter in sub-catchments underlain by Chalk and Greensand, and autumn in drained, clay subcatchments) when DOC : nitrate molar ratios are low, suggesting low potential for in-stream uptake of inorganic forms of nitrogen. Consequently, our study emphasizes the tight relationship between DOC and nitrate availability in agricultural catchments, and further reveals that this relationship is controlled to a great extent by the hydrological setting.
The use of robotics in harsh environments, such as nuclear decommissioning, has increased in recent years. Environments such as the Fukushima Daiichi accident site from 2011 and the Sellafield legacy ponds highlight the need for robotic systems capable of deployment in hazardous environments unsafe for human workers. To characterise these environments, it is important to develop robust and accurate localization systems that can be combined with mapping techniques to create 3D reconstructions of the unknown environment. This paper describes the development and experimental verification of a localization system for an underwater robot, which enabled the collection of sonar data to create 3D images of submerged simulated fuel debris. The system was demonstrated at the Naraha test facility, Fukushima prefecture, Japan. Using a camera with a bird’s-eye view of the simulated primary containment vessel, the 3D position and attitude of the robot was obtained using coloured LED markers (active markers) on the robot, landmarks on the test-rig (passive markers), and a depth sensor on the robot. The successful reconstruction of a 3D image has been created through use of a robot operating system (ROS) node in real-time.
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