Aquadvanced

Institutional setting

Aigua de Rigat is a company that holds shares in Agbar (68%), a company of the French multinational Suez and 32% of shares in the City of Igualada (La Veu, 2018).

Suez and Schneider Electric created a joint venture with the aim of making it a leader in the water digitalization sector (Independent, 2021)

Aquadvanced is part of the launch of “Advanced Solutions”, a new range of tailor-made solutions offered™ by SUEZ ENVIRONNEMENT and Schneider Electric to respond to the challenges of local administrations and industry (Schneider Electric, 2021)

Geographical setting

The Carme-Capellades aquifer (CC) is a body of water whose intense exploitation has caused a significant decrease in levels in recent decades worsening its quantitative state and affecting the natural discharge in different points such as the Capellades raft

Figure 1 Location of the CC aquifer, the recharge zone (P1) and the aquifer upwellings (P2). Retrieved from: https://www.revistaigualada.cat/wp-content/uploads/2020/12/revista-igualada-66-24.pdf

In area P1, occupying the municipalities of La Llacuna, Mediona, Santa Maria dels Miralls and a small part of Bellapart and Querol is the recharge zone. In the P2 region the upwellings of the aquifer are located and includes the municipalities of Orpí, Carme, the Torre de Claramunt, the Pobla de Claramunt, Capellades, Sant Joan de Mediona, Cabrera d’Anoia and Sant Quintí de Mediona (Martí. P. O, 2020)

Historical overview

The coexistence of blockchain with the Internet of Things (IoT) will define a new technological paradigm for the coming years. The combination of both technologies in the monitoring and management of resources with energy or water is attractive. While IoT tools collect a large accumulation of data in real time, blockchain is able to evaluate, simulate and even make predictions.

IoT is being a very useful technology to model and monitor environmental phenomena. It allows wireless network connection, allowing distant devices to be connected to each other more easily. They are applicable in multiple fields, from treatment plants (wastewater or water treatment plants) to the modeling of aquifers or the control of the quality and quantity of the water resource.

Artificial intelligence (which allows to assess, understand, recognize and decide) combined with blookchain (verify, execute and record) allow to generate models that allow monitoring and prediction. In this sense, machine learning stands out, a technology based on statistical learning methods (Mustafa, H.M et al., 2021)

This combination has been applied in numerous projects recently; for example, Open Water Web (Open Data Platform), Waspmote Smart Water (platform for quality monitoring), WaterWatch (tool to produce multiple flow maps) among others. (Salam, A., 2020).

Evidence of benefits from implementation

With this tool you can integrate and analyze all the data of the status and operation of the network and facilities, and transform them into information and simple criteria for decision making.

The Aquadvaced Well Watch software allows the optimization of the operation of the extraction, guarantee the commitment of supply of the supplied populations and manages to reduce the losses in the distribution network (they can exceed 30% of the volume) giving the possibility of using a greater amount of the resource.

Through Aquadvanced Well Watch, the distribution network allows to identify these leaks and advance to maintenance or repair actions of elements of the network in real time.

Replication potential in SUDOE region

Real-time measurement systems contribute to data collection, reducing difficulty, minimizing costs. The difficulty of replication lies in the software, the treatment and extraction of the data that provide valuable information.

There is the possibility to acquire the software developed by Suez and Schneider Electric and deploy it in the desired region. There is also the possibility of developing our own software adapted to the particular case, adapting the technological and business approach represented by this initiative in the management of hydrogeological resources, which is applicable to any groundwater exploitation system.

Future outlook

The future management of water resources will be based on the control, analysis and interpretation of data, to obtain a sustainable and optimized management, an approach that management bodies call “intelligent management”. Thus, the judicious use of data contributes to guaranteeing the supply in quality and quantity, controlling efficiency and opening lines of improvement based on the information collected, which will be necessary in a scenario of scarcity of water resources.

Key points of the innovative method

• Base the management of an exploitation system on the massive collection of data and its interpretation using machine learning methods.
• The implementation of these technologies, together with the evaluation of their performance, should indicate new strategies in aquifer exploitation systems and distribution of resources to users.