Improving geological and process model integration through TIN to 3D grid conversion

The ability to extract properties from 3D geological framework models for use in the construction of conceptual and mathematical models is seen as increasingly important, however, tools and techniques are needed to support such information flows. Developing such methodologies will maximize the opportunity for information use and re-use, this is particularly important as the true value of such assets is not always known when they are first acquired. This paper briefly describes the cultural and technical challenges associated with the application of information derived from 3D geological framework models by hydrogeological process models. We examine how these issues are being addressed and present a tool, SurfGrid, which allows a user to generate 3D grids (voxels) of parameterized data from a series of geological surfaces. The procedures and tools described offer the ability to re-use expensively created assets by providing user friendly techniques that enable multidisciplinary scientists to extrapolate property distributions from geological models

A regional-scale conceptual and numerical groundwater flow model in fluvio-glacial sediments for the Milan Metropolitan area (Northern Italy)

Study region: The Milan metropolitan area lies on one of the most important aquifer in Italy, heavily exploited for public and industrial water supply. The area, covering 3135 km2 in the Po Plain (Northern Italy) with a continental climate, is bounded by the Po, the Adda and the Ticino rivers and by the prealpine foothills. Regional hydrology is characterised by a network of natural and man-made elements, and lowland springs. The sedimentary sequence, from bottom to top, is formed by meandering river plain deposits, the distal fringe of the glacial outwash plains and proximal braid-plain deposits. Study focus: This study proposes a general approach for aquifer geometry reconstruction and hydrodynamic parametrization of hydrofacies in fluvio-glacial deposits, and their implementation into a 3D regional groundwater flow model. This approach is based on sedimentologically-defined lithofacies/hydrofacies and their correlation in space to obtain nearly homogeneous subunits starting from available data (i.e. 8628 borehole logs, grain size distributions, well tests) and sedimentological knowledge. New hydrological insights for the region: The calibrated 3D FEM groundwater model allows quantifying the main components of the hydrogeological budget at the regional scale, and the fluxes among the different hydro-stratigraphic units. A sensitivity analysis of groundwater levels to the main recharge components suggests importance of anthropogenic disturbances with respect to natural recharge, and that land-use change may impact water resources more than climate change

Integrating deterministic lithostratigraphic models in stochastic realizations of subsurface heterogeneity. Impact on predictions of lithology, hydraulic heads and groundwater fluxes

Realistic representations of geological complexity are important to address several engineering and environmental challenges. The spatial distribution of properties controlling physical and geochemical processes can be effectively described by the geological structure of the subsurface. In this work, we present an approach to account for geological structure in geostatistical simulations of categorical variables. The approach is based on the extraction of information from a deterministic conceptualization of the subsurface, which is then used in the geostatistical analysis for the development of models of spatial correlation and as soft conditioning data. The approach was tested to simulate the distribution of four lithofacies in highly heterolithic Quaternary deposits. A transition probability-based stochastic model was implemented using hard borehole data and soft data extracted from a 3-D deterministic lithostratigraphic model. Simulated lithofacies distributions were also used as input in a flow model for numerical simulation of hydraulic head and groundwater flux. The outputs from these models were compared to corresponding values from models based exclusively on borehole data. Results show that soft lithostratigraphic information increases the accuracy and reduces the uncertainty of these predictions. The representation of the geological structure also allows a more precise definition of the spatial distribution of prediction uncertainty, here quantified with a metric based on Shannon information entropy. Correlations between prediction uncertainties for lithofacies, hydraulic heads and groundwater fluxes were also investigated. The results from this analysis provide useful insights about the incorporation of soft geological data into stochastic realizations of subsurface heterogeneity, and emphasize the critical importance of this type of information for reducing the uncertainty of simulations considering flux-dependent processes

Stochastic modelling of hydraulic conductivity derived from geotechnical data: an example applied to central Glasgow

Characterising the three-dimensional (3D) distribution of hydraulic conductivity and its variability in the shallow subsurface is fundamental to understanding groundwater behaviour and to developing conceptual and numerical groundwater models to manage the subsurface. However, directly measuring in situ hydraulic conductivity can be difficult and expensive and is rarely carried out with sufficient density in urban environments. In this study we model hydraulic conductivity for 603 sites in the unconsolidated Quaternary deposits underlying Glasgow using particle size distribution and density description widely available from geotechnical investigations. Six different models were applied and the MacDonald formula was found to be most applicable in this heterogeneous environment, comparing well with the few available in situ hydraulic conductivity data. The range of the calculated hydraulic conductivity values between the 5th and 95th percentile was 1.56×10–2–4.38mday–1 with a median of 2.26×10–1 mday–1. These modelled hydraulic conductivity data were used to develop a suite of stochastic 3D simulations conditioned to existing 3D representations of lithology. Ten per cent of the input data were excluded from the modelling process for use in a split-sample validation test, which demonstrated the effectiveness of this approach compared with non-spatial or lithologically unconstrained models. Our spatial model reduces the mean squared error between the estimated and observed values at the excluded data locations over those predicted using a simple homogeneous model by 73 %. The resulting 3D hydraulic conductivity model is of a much higher resolution than would have been possible from using only direct measurements, and will improve understanding of groundwater flow in Glasgow and reduce the spatial uncertainty of hydraulic parameters in groundwater process models. The methodology employed could be replicated in other regions where significant volumes of suitable geotechnical and site investigation data are available to predict ground conditions in areas with complex superficial deposits

A methodology for assessing flood risk from multiple sources

Ph. D. Thesis.Antecedent catchment conditions can affect the severity of flooding, and floods are typically worse when multiple flood sources superimpose. Over one million properties in the UK are at risk of flooding from multiple sources, however, groundwater, fluvial and pluvial flood sources are usually considered separately due to their differing characteristics. This PhD study was composed of two parts: (1) developing a methodology for assessing the risk of flooding from multiple sources, including the creation of a groundwater-surface water modelling system and (2) conducting a national assessment identifying catchments with potential for flooding from multiple sources. The modelling system used 1000 years of synthetic weather data to create realistic meteorological inputs for a physically-based, spatially-distributed hydrological catchment model (SHETRAN-GB). The hydrological model then simulated 1/30, 1/100 and 1/1000 year catchment conditions, which were used as inputs for a high resolution hydraulic model (HiPIMS). The hydraulic model then routed rainfall, stream flow and groundwater emergence to generate a detailed and comprehensive assessment of flood risk. Sensitivity tests compared the flood extents and depths from different methods of integrating groundwater and surface water conditions from the hydrological model into the hydraulic model to find the best method for linking the models. The capability of a national automated hydrological model to simulate groundwater levels was tested at five case study catchments using open source hydrogeological datasets. Automated model configurations were unable to reproduce historical groundwater levels, however simple automated improvements did increase performance. Improved parameterisation of a basic subsurface increased model performance more than the introduction of more complex geology, although the latter was found to be erroneous in places. Correlations between observed and simulated groundwater levels ranged significantly but were as high as 0.9 at some locations. At one case study site, the model domain was given subsurface boundary conditions and increased from its topographic watershed to the estimated groundwater catchment. This dramatically increased the model’s performance and its sensitivity to parameters. The automated setups provided a useful modelling base, but local calibration, improved hydrogeological parameters, subsurface boundary conditions and the use of groundwater domains are necessary for producing good simulations in catchments containing groundwater. New indexes were derived for classifying flow regimes to aid the identification of catchments likely to benefit from the developed methodology, and an initial 29 multisource catchments were identified out of a total of 435 analysed. Multisource catchments are distributed around the UK but are typically confined to areas with permeable bedrock, thus are most commonly found in the South of England. This research demonstrated that the inclusion of groundwater in the flood risk assessment increased the flood hazard by prolonging the flood duration from hours to days but did not notably increase flood depths. Furthermore, the patterns of flood extent changed depending on the proportion of the flood waters that were derived from the subsurface. In summary, this study provides a methodology for the better quantification, mapping and understanding of multisource flood risk, and identifies catchments that are likely to benefit from the approach