It is a critical time for water resource management, which is facing a series of major challenges including climate change. This phenomenon is generating longer periods of drought and more intense rainfall. Tackling this issue, along with the problems of demographic growth and urban development, poses multiple challenges in different areas for water management authorities, which call for answers that go beyond traditional engineering solutions, requiring instead a holistic and technological approach.
Thus, in 2024, digital transformation will emerge as an essential tool to address these challenges. Analyzing data, identifying trends and applying technologies such as big data, machine learning and artificial intelligence are set to play a fundamental role in the new era of water management. However, this approach also calls for major investments in gathering and processing valid, high-quality data.
In addition, climate change is also affecting the data sets that have traditionally been used for studies and forecasts, as not all of them reflect its impact. This requires resilient responses, i.e., the capacity to adapt, anticipate and foresee the most adverse scenarios to optimize water management, minimizing the risk of floods and droughts.
In this sense, tools such as Decision Support Systems (DSS) and Early Warning Systems (EWS) represent a key technological trend to address these extreme events.
The repercussion of extreme events on water management
The repercussions of increasingly frequent, more intense droughts go beyond surface water, affecting groundwater bodies and decreasing their quality due to overexploitation of aquifers during dry periods. Effective management must address both water quantity and quality in the context of prolonged droughts, as overexploitation not only depletes resources, but also worsens their quality and may increase the concentration of pollutants and saltwater intrusion. Therefore, decision support systems must include hydrogeochemical models to assess and manage water quality during drought episodes.
Droughts also have an economic and social cost, affecting agriculture, triggering crop failures and increasing production costs. In addition, many communities are facing drinking water shortages, thus exacerbating poverty and causing social unrest.
Flash floods, which are fueled by extreme weather events, represent another emerging challenge in the 21st century. The frequency of torrential rains has increased dramatically, generating flooding in areas that were not previously deemed to be vulnerable.
These events have wreaked economic and social havoc around the world. Loss of life, damage to infrastructure, loss of property and displacement of communities are just some of their multiple consequences. In economic terms, direct and indirect losses amount to billions of dollars, affecting the financial stability of entire regions.
Harnessing technology to respond to water management challenges: EWS and DSS
Decision Support Systems (DSS) are fundamental tools that enable relevant agencies to make decisions based on analyzed data. These systems address medium- and long-term planning and management through the use of digital technologies to analyze data, identify trends and implement AI-based strategies.
Early Warning Systems (EWS) focus on preventing and generating warnings for short-term extreme weather events. The ability to pinpoint these events 2-3 days in advance is essential. The UN Sendai Framework (2015-2030) highlights the importance of increasing resilience to natural disasters and addresses the need to deploy early warning systems.
It is essential to highlight the differences between DSS and EWS. While DSS focus on medium- and long-term decision-making, EWS focus on early warnings and short-term prevention. Both are vital components of integrated water resource management and complement each other.
Both systems aim to ensure water security and bring efficient resource management. Decision support systems provide a decision-making framework by developing medium- and long-term forecasting models, while EWS focus on rapid analysis of immediate situations and responses.
The application of new technologies based on predictive algorithms and real-time access to data seeks to improve the accuracy and speed of models and their analysis. DSS use advanced algorithms to build increasingly accurate predictive scenarios, while EWS take advantage of real-time access to quickly assess critical scenarios.
DSS and EWS applications in water resource management
Early warning and rapid response
An early warning system needs to deliver rapid responses, highlighting the need for tools and software that can provide accurate data in the shortest possible time, given that the provision of effective warnings is essential for emergency management agencies. The use of artificial intelligence for meteorological and hydrological forecasting has its shortcomings in these stochastic (they do not respond to any pattern) and convective (they occur suddenly and are concentrated in very specific areas) scenarios, which means that any early warning software must be based on physical processes and supervised by an expert.
EWS, which are designed to help in short-term situations, are essential to manage flash floods. Their main purpose is to quickly analyze the magnitude of an event and issue real-time warnings. They enable fast, effective responses to emergencies by directly informing security forces and civil defense agencies.
Changes in precipitation patterns require continuous operational improvements. The use of satellite technology to analyze rainfall provides a more accurate assessment of extreme events. This improves EWS’ ability to forecast flash floods and enhances emergency planning and response.
Dam management and operating rules
Smart reservoir and dam management is vital to address water stress and flooding. These infrastructures must have optimized systems that take into account the quantity and quality of stored water. Artificial intelligence has a crucial role to play in operational strategies based on preset rules and objectives that minimize damage and optimize water use.
Operating rules must be carefully defined, and systems must be optimized to minimize parameters such as personal injury, the areas affected, and economic costs. Systems that comprehensively analyze how reservoirs are operated and AI-based intelligent reservoir operation proposals are a crucial tool for dam operators, highlighting the need to be able to make quick, effective decisions.
Emerging technologies and practical solutions
In 2024, some technologies such as self-correcting algorithms, access to real-time data and satellite technology will be leveraged to respond to the aforementioned water management challenges. The trends for the coming year are detailed below.
Self-correcting algorithms and smart reservoir management
The application of self-correcting algorithms in rainfall series and meteorological data is essential. Early identification of faults in measuring devices and the introduction of smart reservoir management, based on preset operating rules, are key factors to ensure system efficiency.
Real-time data access and satellite technology
Real-time access to data is a challenge, but also an urgent need. Satellite technologies play a key role in enabling continuous spatial observation of weather conditions and rainfall patterns. The use of advanced communication systems improves data availability and deliver better responses.
Application of technological tools
The practical application of technological tools, such as comprehensive digital platforms for monitoring and displaying data at gauging stations and wells in real time and predicting surface and groundwater reserves, demonstrates how digital transformation is influencing water management. The deployment of DSS and EWS are a fast and flexible response to the sector’s ongoing challenges.
Resilient and sustainable management
DSS and EWS are essential tools to combat growing challenges in water resource management at global level. The expansion and continuous improvement of these systems, together with the application of emerging technologies, are key to achieve robust and sustainable water management. DSS and EWS will complement each other in the coming year in building resilient communities to address extreme weather events, from drought forecasting to rapid flood response.
Smart reservoir and dam management, supported by advanced algorithms, will provide solutions to water stress, ensuring the availability of a quality water supply. Satellite technology and real-time access to data will become vital tools for rainfall analysis and critical situation analyses.
International cooperation is seen as a key factor in the Sendai framework to address the planet’s water challenges. The creation of shared platforms and system integration at global level strengthens anticipation and response capabilities, contributing to reduce the risk of disasters and increasing countries’ resilience.
In short, moving towards resilient and sustainable water management implies ongoing integration of innovative technologies, international cooperation, and a holistic approach ranging from prevention to rapid response. DSS and EWS will be instrumental on this journey to build a future where water is efficiently, adaptively, and sustainably managed.
Idrica’s Water Technology Trends 2024 report provides a comprehensive list of trends for the industry, including integrated water resource management.
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