Implication of river bed hydrogeological properties in surface water and groundwater interactions: a case study in South Australia

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Sina Alaghmand, Simon Beecham, Ali Hassanli

Thursday 2 july 2015

11:00 - 11:15h at Oceania Foyer (level 0)

Themes: (T) Water resources and hydro informatics (WRHI), (ST) Surface and subsurface flow interactions

Parallel session: 11L. Water resources - Flow interactions

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Although, SW and GW are hydraulically interconnected, they are often considered as two separate systems and are consequently analyzed independently. A number of versatile and powerful physically-based numerical models have been developed to describe SW-GW flows and solute interactions in a fully-integrated manner. However, characterization of the SW-GW system is complex because of the nature of the processes involved, and the uncertainty of land cover and aquifer properties. The uncertainty is even more profound at or near any river beds. This paper aims to quantify the influence of hydrogeological properties of the model including hydraulic conductivity, porosity and clogging layer thickness on flow dynamics and solute transport between a river and a saline shallow groundwater aquifer. This study is one of the first attempts to investigate the impacts of such geological properties using a 3D physically-based fully integrated numerical model, HydroGeoSphere, driven by observed field data. Clark’s Floodplain, located on the Lower Murray River in South Australia was selected as the study site. The results show that the hydrogeological properties can significantly control the SW-GW interactions including flow dynamic and solute transport in the adjacent floodplain aquifer. For instance, it appears that thicker clogging layer can accelerate the salinization due to lower groundwater level, lower bank storage rate higher ET rate. Also, it was shown that clogging layer thickness can influence the bank storage only during high river flows. Overall, it is demonstrated that proper understanding of the model properties is an essential step to generate effective numerical models that can be used by water managers. In fact, this can be part of an uncertainty reduction process that is very worthwhile since worldwide there is significant investment in water resource projects. In addition, this can significantly speed up the calibration and validation processes.