Research Highlight

HGS RESEARCH HIGHLIGHT - Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources

Authors: Wolfgang Kurtz, Andrei Lapin, Oliver S. Schilling, Qi Tang, Eryk Schiller, Torsten Braun, Daniel Hunkeler, Harry Vereecken, Edward Sudicky, Peter Kropf, Harrie-Jan Hendricks Franssen, and Philip Brunner

Online data acquisition, data assimilation and integrated hydrological modelling have become more and more important in hydrological science. In this study, we explore cloud computing for integrating field data acquisition and stochastic, physically-based hydrological modelling in a data assimilation and optimisation framework as a service to water resources management. For this purpose, we developed an ensemble Kalman filter-based data assimilation system for the integrated hydrological model HydroGeoSphere, which is able to run in a cloud computing environment. A synthetic data assimilation experiment based on the widely used tilted V-catchment problem showed that the computational overhead for the application of the data assimilation platform in a cloud computing environment is minimal, which makes it well suited for practical water management problems. Advantages of the cloud-based implementation comprise the independence from computational infrastructure and the straightforward integration of cloud-based observation databases with the modelling and data assimilation platform. 

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HGS RESEARCH HIGHLIGHT - On the effects of preferential or barrier flow features on solute plumes in permeable porous media

Authors: Megan Sebbena and Adrian Werner

Discrete flow features (DFFs) such as fractures, faults, sand lenses and clay layers are common geologic features in groundwater systems. DFFs can provide preferential pathways (i.e. ‘preferential flow features’; PFFs) or act as barriers (i.e. ‘barrier flow features’, BFFs) to fluid flow and solute transport. Considerably less research attention has been paid to the role of DFFs in modifying groundwater flow and solute transport where the host rock is permeable, compared to low-permeability rocks. A numerical investigation was conducted within this study to explore how the distributions of solute plumes in permeable aquifers are influenced by a DFF.

HydroGeoSphere was used to evaluate the impact of 2D flow effects within DFFs, which were treated as thin bands of porous media. We show the changes to solute plumes that occur where both BFFs and PFFs are encountered in otherwise permeable rock aquifers (e.g. sandstone and limestone). Additionally, the potential role of ‘back dispersion’ (i.e. the anomalous movement of solutes from the PFF back into the matrix against the direction of groundwater flow) on predictions of PFF effects are explored. The numerical simulations were used to quantify the displacement and widening (or narrowing) of a steady-state solute plume as it crosses a DFF in idealised, 1 × 1 m aquifers. A simple analytical expression for the advective displacement of a solute plume encountering a DFF is provided.

The outcomes of this study suggest that PFFs typically have a more significant influence on plume distributions than BFFs, and the impact of DFFs on solute plumes generally increases with increasing aperture. Plumes crossing a PFF are less symmetrical, and peak solute concentrations beneath PFFs are considerably lower than plumes in BFF cases.

Steady-state salinity distributions for PFF Cases A, B and C (decreasing variability between the PFF and matrix hydraulic conductivities), and Scenarios 1, 2, 3 and 4 (increasing PFF aperture). PFFs are indicated by transparent white lines.

Steady-state salinity distributions for PFF Cases A, B and C (decreasing variability between the PFF and matrix hydraulic conductivities), and Scenarios 1, 2, 3 and 4 (increasing PFF aperture). PFFs are indicated by transparent white lines.

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     Steady-state salinity distributions for BFF Cases D, E and F (increasing variability between the BFF and matrix hydraulic conductivities), and Scenarios 1, 2, 3 and 4 (increasing BFF aperture). BFFs are indicated by transparent white lines.

Steady-state salinity distributions for BFF Cases D, E and F (increasing variability between the BFF and matrix hydraulic conductivities), and Scenarios 1, 2, 3 and 4 (increasing BFF aperture). BFFs are indicated by transparent white lines.