Climate change, population growth, urbanization, pollution, and overexploitation are threatening the ecosystem and livelihoods, water, as an important climate connector, requires integrated management approaches to face new challenges. Knowledge of the interactions between the various types of water and its various uses is key to guaranteeing its availability, safety, and protection.
To address these challenges and ensure water security for all, we need to find new ways of managing water resources that are more efficient, sustainable, and equitable. This is where the convergence of disruptive technologies plays an increasingly important role in the management of water resources. Particularly, data and artificial intelligence have become the most promising tool to address this challenging scenario by advancing in their ability to understand complex interrelationships and accelerating in the development of autonomous and predictive models.
Data and AI are powerful technologies that can help water actors in monitor, understand, predict, and manage water systems, becoming accelerators of further effectiveness, efficiency, and flexibility in the use of water resources. They can also help us innovate, engage stakeholders, and empower communities. By governing, gathering, managing, and analysing data, we can increase the understanding of how water resources are changing over time, identify areas where actions are needed, and develop strategies to preserve and improve access to water resources, even predictively to anticipate critical scenarios.
Following some examples of how data and AI currently contribute to optimize the use of the water and minimize sanitation crisis by accelerating a positive change:
- Data and AI can help us monitor water quantity and quality by using various sources of information such as sensors, satellites, drones, or citizen science platforms to collect and analyse real-time or historical data on water availability, use, or pollutants, pathogens, nutrients in water sources. This can help us detect anomalies, identify trends, evaluate impacts, identify risks, inform decision-making, enforce regulations, or raise awareness among consumers.
- Data and AI can help us understand water dynamics and interactions by using advanced methods such as machine learning, deep learning, or natural language processing to extract knowledge and insights from complex datasets such as hydrological models, climate scenarios, or social media posts. This can help us reveal patterns, discover relationships, explain phenomena, or generate hypotheses.
- Data and AI can enhance water supply management by using smart meters, leak detection systems, or predictive models to optimize water distribution networks, reduce losses, or forecast demand. This can help increase efficiency, save costs, or prevent shortages.
- Data and AI can help us predict water outcomes and risks by using sophisticated techniques such as artificial neural networks, support vector machines, or ensemble methods to build predictive models or simulations based on data inputs such as weather forecasts, demand projections, or management scenarios. This can help us anticipate changes, estimate uncertainties, assess vulnerabilities, or optimize decisions.
- Data and AI can help us manage water resources and services by using smart technologies such as internet of things (IoT), cloud computing, or blockchain to enable automation, traceability or coordination of water operations such as irrigation systems, distribution networks, or treatment plants. This can help us improve efficiency, reduce costs, enhance reliability or quality of water resources or services.
- Data and AI can help us innovate new solutions for water challenges by using creative approaches such as generative adversarial networks (GANs), reinforcement learning (RL), or evolutionary algorithms to design novel products services business models policies or partnerships that address specific needs or opportunities. This can help us create value add diversity foster collaboration or inspire change.
- Data and AI can help us engage stakeholders and empower communities by using interactive platforms such as web applications mobile applications chatbots or games to communicate share learn or participate around water issues such as awareness raising education feedback consultation or action taking. This can help us increase transparency accountability participation satisfaction or ownership.
Current advances in artificial intelligence are driving the evolution to a predictive management approach of the water value chain. The use of new digital technologies throughout the whole water cycle is becoming a reality, form day to day, helping water managers to make more informed decisions about how to allocate water resources and plan for future water needs.
The ICT4Water cluster is a hub for EU-funded research and innovation projects on ICT applied to water management, from more than 10 years has been contributing on accelerating the dissemination and exploitation of the results of European Union (EU) funded activities in digital technologies applied to the whole water ecosystems. Currently, over 60 projects are active and former members working together in a thriving and interconnected Community contributing to accelerate exploitation of results and outcomes from projects members by delivering co-produced knowledge to a wide range of stakeholders and actors within the water sector.
Many ICT4Water projects and cluster action groups contribute, and already contributed, to the acceleration resulting from the convergence of disruptive technologies, here are some examples.
B-WaterSmart project B-WaterSmart accelerates the transformation to water-smart economies and societies in coastal Europe and beyond. Accelerating change requires a clear understanding of the roadmap to follow and one of the holistic concepts for a future vision that is more and more discussed is water-smartness. B-WaterSmart will produce a number of public outcomes that will be demonstrated in real systems at our Living Labs. Portfolio of water-smart applications & data for multiple purposes in a circular economy context, including planning tools based on water-energy-nutrients balance, water allocation optimization and negotiation platforms, solutions for smart metering, sensoring and monitoring of infrastructure, risk assessment, and decision support tools and ‚water-smart for climate-ready‘ building certificates & app.
IMPETUS project is working with stakeholders in 7 biogeographical demo sites across Europe to assess risks and propose measures for adaptation to climate-change induced water shortage, drought, and compromised water quality. Using remote sensing data, water quality analysis, AI-based models and by involving stakeholders at the regional and sub-regional scale, the project will design and implement Resilience Knowledge Boosters tailored to the context, needs and potential for solutions of each region.
Mar2Protect through an AI powered tool, will integrate real-time information from sensors placed in risk locations with other important information (preferences of social agents, risk assessment…) to provide an holistic approach to prevent groundwater contamination from the impacts of climate change and global change. The tool will allow a new generation of Managed Aquifer Recharge approach to improve groundwater quality and quantity. The core of the innovative Managed Aquifer Recharge is the M-AI-R Decision Support System which will incorporate technological and societal engagement information using an Artificial Intelligence-based evaluation to improve groundwater quality and quantity.
The StopUp project will combine IoT-sensors, real-time online data processing and hybrid modelling to decide on the opportune moment and location for sampling. Auto-samplers installed in the catchment will then be triggered for sampling at these specific moments. This innovative approach of event-driven in-situ sampling will a much better capture pollutants that are only sporadically released but have a large impact on natural aquatic ecosystems. By combining modelling of complex urban catchments, water sampling and continuous water quality measurements, we aim to better understand pollution sources and pathways of catchments.
Wastewater plays a key role both as a reusable resource but also as a carrier for energy and materials to be extracted, treated, stored and reused within a dynamic socio-economic and business oriented industrial ecosystem. The project ULTIMATE introduces the concept of Water Smart Industrial Symbiosis, aiming to create economic value and increase sustainability by valorising resources within the water cycle through nine case studies across Europe. This is achieved through digital tools, including ontologies for data, Decision Support Systems for optimising process modelling for various case studies of industrial-domestic water re-use, to investigate future scenarios, assist stakeholders in making strategic decisions for the future, including the impacts of climate change, promoting circular economy in a symbiosis context.
The project NEXOGENESIS is facilitating the next generation of effective and intelligent water-related policies utilising Artificial Intelligence and reinforcement learning to assess the water-energy-food-ecosystem (WEFE) nexus. The objective is to reduce uncertainties of how new policies and stakeholder behaviour affect the nexus through the integration of Self-Learning Nexus Assessment Engine (SLNAE) output with policy feasibility assessments, along with validation of findings by stakeholders. This will lead to better cross-sectoral policy-making and governance, leveraging synergies and avoiding trade-offs to support trade developments, especially for transboundary river basins.
In coordination with the former and live ICT4Water projects and water associations related with the water sector, the Intelligent and Smart Systems (ISS) working group is implementing the latest release of the ICT4WATER action plan. The objective is to establish a high-level architecture to map most promising projects for wider implementation of intelligent and smart systems in the water domain. The proposed architecture will contain features such as data brokering, data models, digital twins, advanced decision-making tools, advanced visualization, and soft sensors to demonstrate the impacted-on cities & territories, agriculture, energy, etc. given the uncertainties brought by climate change.
By using AI to analyse data and make predictions, water managers can make more informed decisions and improve the sustainability of the water cycle. Therefore, data and artificial intelligence (AI) are one of the key drivers to accelerate he change by helping us understand, monitor, manage, and optimize the water cycle in ways that were not possible before, plus to enable innovation, collaboration, and participation among different actors and sectors.
Data and AI are not magic technologies that can solve all water challenges without any trade-offs. They also introduce ethical, social, environmental, or technical challenges that need to be addressed carefully such as data quality, privacy, security, bias, accountability, or governance. However, they offer tremendous potential to accelerate positive change in the whole water cycle if we use them wisely responsibly, inclusively, collaboratively, and creatively.
Data and AI urgently must contribute to deploy resilient water systems that allow to adapt to new situations of water stress and world changes with normality, structure, continuity and in a sustainable way. We must not solve a specific problem, but rather transform the water resource management to guarantee the greatest availability of present and future water.
Gabriel Anzaldi Varas1, Violeta Kuzmickaite2, Lydia Vamvakeridou-Lyroudia3.
- Eurecat Technology Centre, Spain
- EC REA B3 – Biodiversity, Circular Economy and Environment
- KWR Water Research, the Netherlands
The mentioned ICT4Water cluster projects have received funding from the European Union’s Horizon research and innovation programme under respective grant agreements: B-WaterSmart (No 869171), Mar2Protect (No 101082046), Impetus (No 101037084), StopUP (No 101060428), ULTIMATE (No 869318), NEXOGENESIS (No 101003881). The ICT4Water cluster is supported by the European Research Executive Agency (REA).
Read more about the cluster inputs to EC policies and recent publications here.