The digital revolution in river basin management

As science and technology advanced, hydrology began to follow more systematic and quantitative approaches. The introduction of conventional hydrological models, such as those developed by Darcy, Horton, Clark and the SCS, marked a significant leap forward in terms of a more accurate mathematical understanding of hydrological processes. These models provided scientists with a way to quantify phenomena such as snowmelt, groundwater infiltration, and the rainfall-runoff process, although these processes remained difficult to measure and model due to their stochastic nature and spatial and temporal variability. The lack of accurate data and the inherent complexity of natural systems limited the capability of these models to provide accurate predictions.

The digital revolution has transformed watershed management, ushering in a new era of advanced technologies and massive data

The digital revolution has further transformed river basin management, heralding a new era spearheaded by advanced technologies and massive data. Hydrometeorological satellites now afford unprecedented views of the Earth's atmosphere and land surface, providing real-time data on precipitation, soil moisture, and changes in snow cover. This information has significantly enhanced the accuracy of hydrological models, enabling scientists and water utilities to make better-informed, more timely decisions.

Decision support systems

In this context, Decision Support Systems (DSS) have emerged as crucial tools in modern river basin management. These systems combine data from multiple sources, including satellites, weather stations and ground-based sensors, and use advanced mathematical models to furnish predictions and recommendations. Artificial intelligence has taken these systems to a new level, enabling the analysis of large volumes of data and the identification of complex patterns that traditional models were unable to grasp. Artificial intelligence (AI) can anticipate the behaviour of continuous variables and analyse relationships in stochastic processes, helping to assess risks and optimize water management. In addition, AI and big data analytics bring unprecedented potential to adapt to climate change impact. AI can identify trends and patterns that indicate changes in climate conditions by analysing vast amounts of historical and current data. This helps to predict and mitigate the impact of floods and droughts with greater accuracy and greater anticipation.

Therefore, optimized reservoir management becomes crucial, as these water systems play a vital role in providing water security by attenuating floods and accumulating water to supply the population, irrigate fields, and generate hydroelectric power. Thus, efficient reservoir use planning can avert devastating floods and ensure that sufficient water is available during periods of drought. Digitalisation, new mathematical models and artificial intelligence can assist in optimizing reservoir management, analysing flood risk and maximizing water availability for diverse needs.

Challenges in river basin digitalisation

Despite these advances, there are significant challenges to the implementation of digital technologies in river basin management. First, the density of sensors in watersheds is much lower than in urban environments, making it difficult to create accurate digital twins. These digital twins, which are virtual representations of physical systems, require detailed, real-time data to be effective.

Accordingly, the number of sensors in river basins is one of the areas where the difference between urban and non-urban water is most striking. In a city, it is common to find a dense array of sensors that monitor the status of the drinking water and sanitation networks as well as electromechanical installations, WWTPs and DWTPs. However, in a river basin, the density of these devices can be up to a thousand times lower. This not only hampers real-time data collection, but also limits the ability to detect and anticipate critical changes in the hydrological environment. Therefore, investment in installing sensors is essential to bridge this gap and improve hydrological modelling accuracy.

Another major challenge is the calibration of rating curves, which usually provide flow results and are essential to connect hydrological models with the measured reality. These curves establish the relationship between water levels and flow rates in rivers, yet they must be finely calibrated to ensure the models are accurate. Acquiring precise data for this task remains a significant hurdle as calibration requires not only extensive data, but also the ability to adjust models to specific local conditions, which can be extremely complex due to the spatial and temporal variability of hydrological phenomena.

As we advance towards a more digital future, the combination of traditional methods and modern technologies can offer the best solutions

In these cases, digital transformation has significantly improved early warning systems for floods and droughts by harnessing sensor data and hydrological models to predict the occurrence of extreme events and provide the authorities and the general public with advance warning. AI applied to the modelling of meteorological phenomena, such as the AIFS model, has proved to be especially effective in pinpointing patterns that precede convective events that are likely to generate floods, thus improving the capacity for anticipation and response. Similarly, drought warning and resource optimization systems use climate and water use data to forecast shortages and propose sustainable management strategies. However, the implementation of these systems requires robust infrastructure and effective coordination between different agencies and tiers of government.

Along these lines, the Xylem Vue powered by GoAigua platform (XVPGA) has become one of the best examples of how to tackle the challenges posed by digital water management in river basins. The platform is the result of a partnership between Idrica and Xylem and incorporates specific modules and algorithms that enable real-time management of extreme events, as well as medium- and long-term hydrological planning through dashboards and a user-friendly GIS viewer.

Xylem Vue powered by GoAigua is designed to offer outstanding performance in massive data analysis, time series and high-resolution hydrometeorological satellite mapping, providing accurate analyses in the shortest possible time, while guaranteeing high-quality, traceable results.

The platform can perform detailed spatial and temporal analyses on the different integrated meteorological models. It can also calculate IDF (Intensity-Duration-Frequency) curves for high-intensity events, generating hydrographs at both deterministic and probabilistic levels, and assessing the flood risks associated with peak flows. It uses statistical processing and AI with historical data, together with models for meteorological reanalysis six and seven months in advance and for climate change scenarios to generate water planning models that improve decision-making in the medium and long term.

The platform includes a powerful hydrological alert management and reporting module, simplifying the visualization and monitoring of extreme events for emergency management stakeholders.

The use of XVPGA systematizes and standardizes the complex process of hydrological analysis, creating a robust database for informed decision-making. This helps basin managers manage their surface water bodies, groundwater bodies and reservoirs, providing hydraulic and water security for their operating areas, and to respond holistically to watershed challenges.

Cultural change as the cornerstone of digital transformation

However, water resource management cannot solely rely on technological solutions. It is critical to understand that true digital transformation in river basin management is not only about embracing new technologies, but also about shifting the way we think, work and cooperate. Technology, both at the hardware and software level, is a crucial part of this transformation, but real success hinges on aligning all the stakeholders involved and adopting new working methods. Collaboration between scientists, engineers, water utilities and other players is key to making the most of the opportunities afforded by digital transformation, especially for decision makers.

AI can identify trends and patterns that indicate changes in climate conditions by analysing vast amounts of historical and current data

There is no doubt that artificial intelligence, through its ability to analyse massive data trends and behaviours, has emerged as a powerful tool in water management, as it is capable of unlocking hidden relationships and providing new insights that improve water resource planning and management. However, the implementation of these technologies requires investment in training and capacity building to ensure that water practitioners can take full advantage of them.

The move towards digital transformation also implies significant cultural change within organizations and communities involved in water resource management. Embracing advanced technologies and new working approaches requires an open mindset and readiness for change. Stakeholders must be willing to work together more closely, share data and information, and adopt interdisciplinary approaches to solving complex problems. This cultural shift is pivotal to effectively mainstreaming new technologies and maximizing their positive impact on watershed management.

Therefore, education and training are essential elements of this transformation. Water practitioners must be equipped with the skills and knowledge required to use new technologies effectively. This includes both technical training in the use of digital tools and AI models, as well as the development of skills for critical analysis and informed decision-making. Universities and research centres have a crucial role to play in preparing the next generation of water utility managers, ensuring that they are well-versed in meeting the challenges of an increasingly digital world.

Investment in research and development is equally crucial. Hydrology is a constantly evolving science, and continuous improvement of models and technologies is imperative to keep abreast of changes in the natural environment and the demands of society. Partnerships between academia, government agencies and the private sector can drive innovation and develop new solutions for water resource management.

In conclusion, we have evolved from being dependent on traditional observations and empirical knowledge to using advanced technologies and artificial intelligence models to manage our river basins. This has significantly enhanced our ability to forecast and respond to extreme events, optimize water use, and manage our water resources more sustainably. However, the real revolution does not lie in technology alone, but in people's ability to adapt and work together in this new digital environment. The only way we can effectively address the challenges of watershed management in the 21st century is through a holistic approach that combines technology, knowledge, and cooperation.

We must continue to invest in research and development, foster training and education among water practitioners, and advocate policies that promote the uptake of advanced technologies. This will enable us to take full advantage of the opportunities afforded by digital transformation and to guarantee sustainable, resilient management of our valuable water resources. Ultimately, the goal is to create river basin management systems that are not only efficient and effective, but also equitable and sustainable, thus ensuring that future generations can enjoy and benefit from this resource while being shielded from the effects of extreme events.