Locating the hotspot for groundwater arsenic pollution

By Nick KachelApril 15th, 2020

A new computer model to predict arsenic pollution will help to support water management decisions and develop new arsenic remediation strategies.

Image credit: Eawag

Did you know arsenic is one of the most common inorganic contaminants found in drinking water worldwide?

Arsenic is tasteless and odourless, but highly toxic to humans. If ingested over long periods, even low concentrations can cause damage to health, including hyperpigmentation of the skin, hyperkeratosis on the palms and soles, disorders of liver, cardiovascular and kidney function, and various types of cancer.

Arsenic contamination is a problem of global significance, but it is particularly prevalent in aquifers across South and Southeast Asia. For Bangladesh alone it is estimated that arsenic kills 43,000 people every year.

Particularly puzzling is that the level of arsenic concentrations can vary dramatically over short distances, for example between different wells within the same village. Therefore people in many areas are completely unaware of the risk because their groundwater wells have never been screened for arsenic. Up to 20 million people a year could be exposed without knowing.

Identifying the pollution source

To address this problem, tremendous research efforts have been dedicated over the last two decades to better understand the sources and distribution of arsenic-polluted groundwater.

However, much of this research has focused on the often very detailed geochemical characterisation of sediments and porewaters, while paying less attention to the strong interaction that may occur role between groundwater flow and geochemical reaction processes.

Against this backdrop, a team of scientists from Flinders University, CSIRO and the University of Western Australia, together with colleagues at the Swiss Federal Institute of Aquatic Science and Technology (Eawag), set out to integrate much of what has been learned over the years into computer simulations that mimic the complex interactions between groundwater flow and solute transport.

Simulation results illustrating the reactive transport of tritium, helium and arsenic from the Red River into the Holocene aquifer underlying Van Phuc village.

A detective’s job: Reconstructing past arsenic behaviour

In other areas of contaminant hydrogeology – the study of contaminant behaviour in groundwater – reactive transport modelling has proven a successful tool for analysing field observations. This involves using previously collected field data (such as arsenic and other concentrations at different wells) to create a ‘hindcast’ of coupled flow and geochemical mechanisms (as opposed to a forecast) that has caused the groundwater pollution. In this process the model and its parameters are successively improved until the simulation results agree sufficiently well with the field-measured data. This allows researchers to unravel which chemical and physical processes have played a key role in the evolution of a contamination.

Learning to simulate the behaviour of contaminants like arsenic within aquifers allows researchers to predict where and when pollution might occur in the future.

Assembling a computer model for arsenic

The Australian team of computer modellers pulled in expertise from across the globe to adjust their model to the simulation of arsenic transport in groundwater systems. Swiss collaborators Michael Berg and Rolf Kipfer have closely studied arsenic pollution at various sites in Vietnam and Bangladesh.

The field site that was selected for the modelling study was a highly arsenic polluted and well characterised site about 20 kilometres south of Hanoi, Vietnam.

It first involved setting up a numerical groundwater flow and transport model along a transect that, starting at the interface between the Red River and the Holocene aquifer underlying Van Phuc village, followed the groundwater flow over several kilometres.

The team then used the measured concentrations of tritium, a radioactive isotope that entered the groundwater system from the atmosphere during the times of nuclear bomb testing, and its decay product helium, a noble gas, to reconstruct how fast and where the groundwater was moving over the last five decades.

Once the model simulations were able to match the concentrations that were measured, additional groundwater constituents and geochemical processes were added to the model in order to simulate how arsenic was mobilised and transported in the groundwater.

From the beginning of the work a key hypothesis was that the changes in groundwater flow that occurred over the past 50 years since the city of Hanoi started to extract groundwater to satisfy its steadily increasing water demand, were the main trigger for the high concentrations that were observed below Van Phuc.

Eventually, the numerical model allowed the team to pinpoint the source of arsenic to the river muds that are regularly deposited at the more slow-flowing zones of the Red River.

The organic matter contained in those muds fuels a variety of biogeochemical reaction, most importantly the reductive dissolution of iron oxides, which explains the release and transport of arsenic into the aquifer underlying the Van Phuc village.

The team also found that the release mechanism and the persistence of the river-groundwater interface as a biogeochemical reaction hotspot requires some re-fuelling by a re-occurring deposition of sediments that are enriched in organic matter, Fe-oxides and arsenic.

Finally, they constructed a simpler surrogate model of their field-scale model and ran it in predictive mode to illustrate the interplay of the four key factors found to control the occurrence and longevity (abundance of reactive organic matter; abundance of iron oxides; magnitude of groundwater flow; river mud deposition rate) on the evolution and longevity of arsenic release at surface water/groundwater interfaces.

The researchers are now looking to apply and test their computer model to other arsenic contaminated sites around the world, with the aim to support water management decisions and to develop new arsenic remediation strategies.

Their findings have now been published in Nature Geoscience.


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