Research Highlights

Research

The SOS-Water Project is uncovering critical insights into the challenges facing global water resources. Through cutting-edge research, advanced modeling, and real-world case studies, we are improving our understanding of water crises and developing strategies to ensure a sustainable, resilient, and equitable future for water management

A detailed overview of the different work-packages that are offered by SOS-Water.
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Droughts, Floods,
and Climate Change

Climate change is altering water availability, increasing the frequency of droughts and floods, and introducing greater uncertainty into water systems. These changes pose significant challenges for water security, agriculture, energy production, and urban development.

One of the key findings of the SOS-Water Project is that multi-year drought cycles are becoming more common, particularly in regions like Southern Europe, where declining precipitation and rising temperatures are reducing water availability. In the Júcar River Basin in Spain, research indicates that prolonged dry periods could significantly impact agriculture and drinking water supplies unless adaptive strategies are implemented.

At the same time, flood risks are increasing due to heavier and more erratic rainfall patterns. In theDanube Basin, for example, extreme flooding events have become more frequent, overwhelming existing flood defenses and putting communities at risk. Our project is working to integrate hydrological data, climate projections, and forecasting to help policymakers and water managers better anticipate and prepare for these extreme events.

To improve resilience, our research highlights the importance of integrated water storage solutions, adaptive reservoir management, and nature-based flood protection strategies. By combining advanced forecasting with smart infrastructure planning, we can help communities adapt to the new realities of climate-driven water variability.

Water Quality &
Pollution Trends

Water availability is only part of the equation—ensuring that water remains clean and safe for human and ecological use is equally critical.  

In the RhineRiver Basin, nitrate pollution from agricultural fertilizers continues to be a major concern, contributing to water degradation and ecosystem stress. Meanwhile, in the Mekong Delta, salinity intrusion linked to climate change and upstream water management is threatening both drinking water supplies and agricultural productivity.

To tackle these challenges, SOS-Water is leveraging forecasting models that use real-time water monitoring data to predict and detect pollution hotspots before they reach crisis levels. By combining Earth observation technologies, remote sensing, and automated water sampling, we are improving early detection capabilities, allowing for more proactive and targeted water management responses.

The Water-Food-Energy Nexus:
Managing Competing Needs

Water is a shared resource that must support multiple sectors—including agriculture, energy production, and urban consumption. Managing these competing demands is a growing challenge, particularly in regions where climate variability is reducing available water supplies.

Agriculture is by far the largest consumer of freshwater resources, accounting for over 70% of global withdrawals. In the case studies conducted by SOS-Water, our research highlights how unsustainable irrigation practices and inefficient water use contribute to water scarcity, particularly in semi-arid regions. The project is exploring more efficient irrigation techniques, improved soil moisture management, and crop selection strategies that reduce water dependency while maintaining food security.

At the same time, the project is studying hydropower and its trade-offs with environmental sustainability. While hydropower is a key renewable energy source, its water demands can disrupt river ecosystems and impact downstream water users and compromise the connectivity of aquatic ecosystems Our models assess how hydropower can be managed more sustainably, balancing electricity generation with ecological conservation and water availability for other users.

Using scenario-based simulations, our research is also forecasting future water demands and trade-offs to help policymakers develop strategies that ensure amore harmonized balance between water, food, and energy needs.

Nature-Based Solutions
for Water Management

One of the most promising areas of research in water sustainability is nature-based solutions—using ecosystems and green infrastructure to manage water resources more effectively. Instead of relying solely on engineered solutions such as dams and levees, natural systems like wetlands, floodplains, and urban green spaces can provide cost-effective and sustainable water management benefits.

For example, in the Danube Basin, restored wetlands are playing a crucial role in flood mitigation by absorbing excess water during extreme weather events and gradually releasing it back into the system. These ecosystems also filter pollutants, support biodiversity, and improve groundwater recharge.

In urban environments, green roofs, permeable surfaces, and rainwater harvesting are being explored as solutions to improve water retention, reduce runoff, and enhance climate resilience. Research from SOS-Water demonstrates that integrating green infrastructure into city planning can significantly reduce urban flood risks while improving overall water sustainability.

Our case studies showcase successful implementations of these approaches, proving that working with nature rather than against it can be a highly effective strategy for long-term water security.

Shaping the Future
of Water Management

The research conducted in SOS-Water is providing critical insights for policymakers, scientists, and water managers working to ensure a secure and sustainable future for water resources. By combining advanced modeling, cutting-edge technology, and real-world case studies, our findings are helping to develop more effective and equitable water management policies at regional, national, and global levels.

As the project moves forward, our continued research will further refine these strategies, expand our case studies, and contribute new knowledge to the global effort to secure a Safe Operating Space for Water. Stay connected as we share more updates, results, and solutions in the coming months!

Advanced Modeling

Advanced Modeling
for Water Governance

Effective water governance requires accurate predictions of future water availability, demand, and risks. The SOS-Water Project leverages advanced hydrological models, climate simulations, and AI-powered analytics to provide decision-makers with real-time insights into water resources. By combining traditional water cycle models with cutting-edge machine learning and Earth observation technologies, we enhance our ability to assess water stress, extreme weather events, and long-term sustainability challenges. These tools help policymakers make informed choices about water allocation, infrastructure investment, and climate adaptation strategies

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Hydrological & Climate Models Used in SOS-Water 

Hydrological and climate models serve as the foundation for water risk assessment and management. Within the SOS-WaterProject, we use state-of-the-art hydrological models, such as PCR-GLOBWB, CWatM and SWAT, to simulate river flows, groundwater dynamics, water quality and the impacts of climate variability. These models integrate vast amounts of historical data, real-time monitoring, and future climate projections, allowing researchers to quantify water scarcity risks, predict droughts, and assess the likelihood of extreme flood events

In addition to hydrological models, we incorporate regional and global climate models (CMIP6, CORDEX) to explore how climate change affects precipitation patterns, temperature shifts, and water availability in different regions. By combining these approaches, we create scenario-based forecasts that help policymakers understand the long-term implications of climate-induced water stress

A key innovation in our modeling approach is the integration ofAI-powered analytics. Machine learning algorithms process satellite data, historical water usage records, and environmental variables to detect patterns and provide real-time water resource predictions. These AI-enhanced models improve decision-making by offering faster and more accurate assessments of changing water conditions. 

Water StressIndicators & Their Applications  

To make data-driven water governance more accessible, the SOS-Water Project has developed a set of comprehensive water stress indicators. These indicators allow for a quantitative assessment of water availability, demand, and quality, helping decision-makers pinpoint vulnerable regions and prioritize intervention efforts. 

Our findings indicate that some regions are approaching critical thresholds where water use surpasses sustainable limits. This is particularly evident in areas experiencing rapid population growth, industrial expansion, and agricultural intensification. Through advanced water risk mapping, we have identified hotspots of water stress, where resources are depleting faster than they can be replenished. 

These indicators serve as the basis for policy recommendations, guiding actions such as water allocation planning, investment in alternative water sources, and infrastructure adaptation strategies. By combining hydrological models with AI-driven analytics, we provide a dynamic and continuously updated assessment of water risks, ensuring that policy responses remain proactive rather than reactive. 

AI &Machine Learning for Smart Water Management 

ArtificialIntelligence (AI) and Machine Learning (ML) have transformed water management by enabling real-time monitoring, forecasting, and early warning systems. Within SOS-Water, AI technologies are applied across several key areas: 

  • Flood &Drought Early Warning Systems: AI models analyze climate patterns, soil moisture levels, and hydrological trends to predict extreme weather events with greater accuracy. This allows authorities to take precautionary measures, reducing the economic and humanitarian impacts of water-related disasters
  • Industrial& Agricultural Water Monitoring: AI-driven remote sensing tools track water consumption patterns in irrigation, manufacturing, and urban settings, ensuring that usage remains sustainable and efficient. 
  • Satellite-BasedWater Quality Assessments: By processing high-resolution satellite imagery, AI models detect pollution hotspots, algal blooms, and changes in water clarity, allowing authorities to intervene before contamination spreads. 
  • One of the major breakthroughs in SOS-Water has been the development of AI-enhanced water governance tools that link scientific research with real-world applications. These technologies are being used to optimize water distribution, minimize losses, and enhance resilience in water-stressed areas.