Decision Support Systems to contribute to a Water-Smart Society: Camila Forero from Aqualia

A smart and sustainable society recognises the true value of water, which enables all our economic activities, maintains health and well-being, and contains essential resources. As part of the REWAISE project, which contributes to a Water-Smart society, I help integrating digital innovations to support alternative water management. This could sound a bit abstract, so the best way to understand this concept is to show you how I use digital tools through the different stages of the water cycle, to generate a high impact on the performance of each process.

My name is Camila Forero, I’m the main researcher of Aqualia involved in the development of digital solutions linked to REWAISE. I’m an Electronical Engineer specialised in Telecommunications Management. I moved to Spain from Colombia in 2018 to take a master’s degree in Telecommunication Engineering and joined Aqualia in 2019. Since I started in the company, I am actively involved in the digital solutions related to REWAISE. Nowadays I’m based in Vigo, the main industrial hub of Galicia and one of the project´s Living Labs.

Decision Support Systems (DSS) take up much of my time. A DSS is a digital tool that supports business and technical decision-making. DSSs serve in management, operations and planning of companies and services, to help people take actions and solve problems that may be rapidly changing and not easily specified in advance.

Let’s take a look at my work throughout the water cycle. In raw water reservoirs, algal blooms are rapid increases and accumulations of algae which create a big problem for the treatment of drinking water. Working with the U. Autónoma of Madrid (UAM), Aqualia has recently developed a laboratory method to identify cyanobacteria in water and quantify their toxicity as a method of early identification of algal blooms.

Once the water enters the drinking water plant, during water disinfection, Trihalomethanes (THM) can be generated. These volatile chemical compounds are due to the reaction of organic matter with chlorine chemicals used in treatment and they must be limited in drinking water. Pilot tests performed in an Aqualia treatment plant showed elimination of THM greater than 84% after membrane nanofiltration, these results are being compared to the performance of other options. 

Conventional treatment of drinking water requires the optimal dosage of chemicals in a sequence of processes. In our joint work with the University of Zagreb and Aqualia, we develop a DSS based on mathematic models to evaluate the concentration of key parameters in each reaction before and after dosing, allowing to optimise the amount of reagents and lower the operational cost.

Water and energy efficiency through DSS: case studies at Fonsalía and Moaña

In the current context of water scarcity, desalination is becoming a suitable solution in water stressed territories. Desalination is more energy demanding than other processes to treat drinking water, so efficiency is a key point in its operation. Machine Learning (ML) algorithms are now used to develop a DSS for energy optimisation in Fonsalía Desalination Plant (Canary Islands). To reach this goal, we use a software to analyse historical data and energy needs related to pumping pressure and flow rates, and to generate periodic operation suggestions for our operators, reducing electricity consumption in a range between 6% and 10%.

Energy saving is a key requirement nowadays, and even sewage systems must improve their performance to avoid spills and minimise electricity needs. In the Moaña municipality in Galicia, we are developing a software that uses numerical optimisation methods and mathematical modelling of the main collector of the town, to optimise pumping energy in the operation of the sewage network. It helps us to control the four pumping stations adjacent to the wastewater treatment plants (WWTP), adjusting their flows and operational regime depending on network storage capacity and downstream treatment capacity.

Once the wastewater reaches the WWTP, several processes remove and eliminate contaminants to reach an effluent quality that can safely be returned to the receiving water cycle.

As the wastewater is treated, biological processes are used to remove dissolved and suspended organic matter, where aeration provides oxygen to the bacteria to decompose harmful substances.

Diffused aeration systems maximize oxygen transfer and minimize odours, but these processes have high energy demands.

With the University of Zagreb, we are developing optimal control models to minimize the energy consumption at Moaña WWTP, using biological process models based on ASM2 algorithms from the International Water Association (IWA), with very good initial results. 

With all these opportunities at Aqualia to learn and apply different digital tools in the integral water cycle, I am very satisfied to help maximising the value of water by optimising resource efficiency. In the coming months, I will expand my studies and developments of new solutions linked to REWAISE, integrating also activities of the project partners in the UK, Sweden, Poland and the Czech Republic, where various options to increase circularity and resilience of a smart water economy are being demonstrated.

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