Analysis of water-level response to rainfall and implications for recharge pathways in the Chalk aquifer, SE England

Water table response to rainfall was investigated at six sites in the Upper, Middle and Lower Chalk of southern England. Daily time series of rainfall and borehole water level were cross-corretated to investigate seasonal variations in groundwater-level response times, based on periods of 3-month duration. The time tags (in days) yielding significant correlations were compared with the average unsaturated zone thickness during each 3-month period. In general, for cases when the unsaturated zone was greater than 18 m thick, the time tag for a significant water-level response increased rapidly once the depth to the water table exceeded a critical value, which varied from site to site. For shallower water tables, a linear relationship between the depth to the water table and the water-level response time was evident. The observed variations in response time can only be partially accounted for using a diffusive model for propagation through the unsaturated matrix, suggesting that some fissure flow was occurring. The majority of rapid responses were observed during the winter/spring recharge period, when the unsaturated zone is thinnest and the unsaturated zone moisture content is highest, and were more likely to occur when the rainfall intensity exceeded 5 mm/day. At some sites, a very rapid response within 24 h of rainfall was observed in addition to the longer term responses even when the unsaturated zone was up to 64 m thick. This response was generally associated with the autumn period. The results of the cross-correlation analysis provide statistical support for the presence of fissure flow and for the contribution of multiple pathways through the unsaturated zone to groundwater recharge. (c) 2006 Elsevier B.V. All rights reserved.

Modelling nitrogen fluxes from the land surface to the coastal zone in European systems: the perspective of the INCA project

This paper describes the results and conclusions of the INCA (Integrated Nitrogen Model for European CAtchments) project and sets the findings in the context of the ELOISE (European Land-Ocean Interaction Studies) programme. The INCA project was concerned with the development of a generic model of the major factors and processes controlling nitrogen dynamics in European river systems, thereby providing a tool (a) to aid the scientific understanding of nitrogen transport and retention in catchments and (b) for river-basin management and policy-making. The findings of the study highlight the heterogeneity of the factors and processes controlling nitrogen dynamics in freshwater systems. Nonetheless, the INCA model was able to simulate the in-stream nitrogen concentrations and fluxes observed at annual and seasonal timescales in Arctic, Continental and Maritime-Temperate regimes. This result suggests that the data requirements and structural complexity of the INCA model are appropriate to simulate nitrogen fluxes across a wide range of European freshwater environments. This is a major requirement for the production of coupled fiver-estuary-coastal shelf models for the management of our aquatic environment. With regard to river-basin management, to achieve an efficient reduction in nutrient fluxes from the land to the estuarine and coastal zone, the model simulations suggest that management options must be adaptable to the prevailing environmental and socio-economic factors in individual catchments: 'Blanket approaches' to environmental policy appear too simple. (c) 2004 Elsevier B.V. All rights reserved.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.