September Researchers uses Cork Harbour in developing new model to assess surface water quality

University of Galway, in collaboration with Charles Sturt University in Australia, have used artificial intelligence and data mining on Cork Harbour to revise a water quality index (WQI).

Surface water quality poses significant environmental, sociological, and economic risks in many parts of the world and the new model can benefit individuals and a range of government and non-government agencies.

The research was conducted by University of Galway PhD researcher’ Md Galal Uddin, under the supervision of Dr Indie Olbert, leader of the University’s EcoHydroInformatics Research Group, and Dr Stephen Nash, in collaboration with the research team of Professor Azizur Rahman from Charles Sturt University, Australia.

Using complex mathematical algorithms, the team developed a simple water quality tool that can be used to assess the level of pollution in waters. The proposed model is simple to use and does not require extensive knowledge of chemistry, biology nor statistics, as opposed to other models.  

While similar tools have already been developed in other countries including USA, Canada, Spain and the UK, one had not been developed for Irish waters. The tool provides a highly accurate assessment of water quality that is superior over the existing models, and is universal so can be easily adopted by other countries. 

Assessment of water quality using this tool can support development of an optimal strategy to efficiently control of water quality and to determine its category such as good, fair, marginally or poor.  The tool can also help to optimize water quality monitoring and as such to aid the provision of the most cost effective system of water quality monitoring, which in general is considered as very costly.  

Since mid-20th century there has been observed a continuous deterioration of water quality (WQ) across Europe due to increasing population, urbanization, and industrialization. One of the main environmental pressures imposed by human activities are nutrient enrichment and climate change. Currently, around 60% of surface waters in the EU have not achieved "good’ status, in Ireland - nearly 47%.

Dr Indiana Olbert said: “Surface waters are considered to be at high risk of having poor water quality in the near future and it will be extremely difficult to maintain good water quality status.

“Water quality assessment allows to diagnose the health of a waterbody and provides necessary information for more effective water resources management including relevant polices to ensure the "good" status of water quality. This research provides a state of the art yet simple to use tool to provide the accurate assessment of water quality.”

Researcher Galal Uddin said: “We identified 30 WQI models globally, only seven WQI models are unique in terms of architecture; all the others are modified. Recently, many studies have reported that existing models produce higher uncertainty in the final assessment. Consequently, assessment results do not express actual scenarios of water quality. We also investigated and compared our model uncertainty with the core established seven models. We found less uncertainty (less than 2%) in our model, whereas more than 7% of uncertainty is associated with other models.”

“A significant implication of this model is that EU countries have been trying to develop a unique method for assessing water quality. Our methodology could be adopted by EU countries because it was specifically focused on the EU coastal water quality because this model is an improved version of the state-of-the-art WQI model.

“Compared to that, it’s very simple and straightforward mathematical functions are cost effective. It could be effective to improve the existing monitoring program and reduce the monitoring cost. Environmental protection agency (EPA), Marine research Institute, and agriculture department Ireland could adopt this methodology for the assessment of surface water quality more accurately and rapidly.”

The findings were recently published in the Journal of Water Research and is available at https://doi.org/10.1016/j.watres.2022.118532

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