Mitigating the global water crisis: digital twin Earths offer a promising solution

While headlines scream “surprise” as cities drown in extreme rainfall or crumble under pressure, the truth is starker. These disasters are not sudden shocks but the culmination of predictable vulnerabilities we have chosen to ignore. It is past time to ditch the reactive “fire drill” mentality and proactively build resilience. 

To give a specific example, riverine flooding is an increasingly common risk in many developing nations. The 2022 floods in Pakistan affected 33 million people, and more than 1,730 lost their lives, with an estimated total damage of US$15.2 billion (1). The direct impact of floods is projected to be approximately 2.2% of fiscal year gross domestic product (GDP) in 2022. We know that such catastrophic disasters are recurrent in the present and will be in the future, so what needs to be done to prepare better and respond in a timely fashion? 

One step toward a set of solutions is the development of digital twin Earth (DTE) models, which offer a groundbreaking approach by creating virtual replicas of Earth. These models enable high-resolution simulations of climate processes and extreme events by integrating real-time data from sensors, satellites, and models to visualize and predict the impacts of climate change on a local scale (2). This helps communities anticipate and prepare for extreme events such as floods, droughts, wildfires, and heat waves. 

The global water cycle, for example, faces significant disruption fueled by climate change, resulting in an amplified frequency and intensity of extreme events. Robust decision-support systems are imperative to effectively navigate these evolving processes. These systems necessitate the seamless integration of cutting-edge advancements in remote sensing, both in situ and via citizen observations, coupled with high-resolution Earth system modeling, artificial intelligence (AI), information and communication technologies, and high-performance computing capabilities (3). 

In their Frontiers in Science lead article, Brocca et al. report a noteworthy contribution: a 4-dimensional DTE hydrology datacube for the whole Mediterranean Basin (4). To calibrate and test the quality of the modeling system, the Po River Basin in northern Italy was selected as a first case study, owing to the availability of high-quality ground observations. This innovative tool merges high-resolution Earth observation (EO) data with sophisticated models of water flow and storage, empowering us to anticipate floods and landslides, effectively manage irrigation for precision agriculture, and glean deeper insights for enhanced water resource management (5).  

Despite these significant strides, further progress is essential. Efforts are needed to ensure the validation of high-resolution data products across diverse regions, foster the creation and integration of compatible multidimensional datacubes, and develop EO data retrieval algorithms and models that seamlessly function across multiple scales. Other crucial next steps include effectively managing the uncertainties inherent in both EO data and models, bolstering computational power through interoperable cloud-based processing environments that uphold open data principles, and strategically harnessing the power of AI and machine learning (6). 

Digital twins are emerging as powerful tools for managing climate risks. By integrating real-time data, historical information, and predictive modeling, they can offer insights into the potential impacts of climate change on various sectors and infrastructure (7). This policy outlook explores the potential of digital twins for climate risk management and examines the policy considerations surrounding their development and deployment. 

Applying digital twin Earth models to tackle climate extremes  

Digital twins are just one tool in a broader toolbox for tackling climate extremes. However, as these virtual worlds evolve, they hold immense potential for the following:  

• Enhanced preparedness and resilience. Digital twins can simulate the effect of extreme weather events, such as floods, droughts, and heatwaves on specific locations and infrastructure, allowing for better preparedness and proactive risk-mitigation strategies. 

• Improved decision-making. By providing real-time data and predictive insights, digital twins can inform decision-making across sectors, including urban planning, infrastructure development, and resource management, leading to more sustainable and resilient solutions. 

• Facilitating climate adaptation. Digital twins can be used to evaluate the effectiveness of adaptation measures and optimize their implementation, helping communities and businesses adjust to changing climate conditions. 

• Boosting financial resilience. By improving risk assessment and providing data-driven insights, digital twins can help insurers develop more accurate risk models and tailor insurance products to specific climate vulnerabilities, leading to increased financial resilience. 

• Promoting transparency and accountability. Digital twins can be used to track the impact of climate change and the effectiveness of mitigation and adaptation strategies, fostering transparency and accountability in climate action. 

Digital twin policy considerations 

While digital twins represent a powerful tool for climate risk management, concerns surrounding data privacy, security, and equitable access cannot be ignored. Strong policies are crucial to navigate this digital frontier responsibly, including: 

• Data governance. Policies must ensure ethical and secure data collection, storage, and usage, with clear ownership and access control regulations. This safeguards individual privacy and prevents misuse of sensitive information. 

• Standardization and collaboration. Standardized platforms and protocols are essential for seamless data exchange and collaboration across different initiatives. This prevents fragmentation and facilitates knowledge sharing for a broader impact. 

• Inclusion and equity. Affordable access and capacity-building support for developing countries are critical for everyone to benefit from this technology. Inclusive approaches ensure diverse voices are heard and solutions are effective globally. 

• Responsible AI and governance. A robust governance framework with ethical guidelines and oversight of AI practices minimizes potential biases and discriminatory outcomes. This fosters trust and transparency throughout decision-making processes. 

• Public engagement and education. Educating the public about digital twins and their applications builds trust and understanding. Engaging with communities ensures informed participation in decisions impacting their lives and encourages responsible climate action. 

Implementing digital twins entails challenges, and collaboration across industries, academic communities and even space agencies is key to unlocking their transformative potential. We can overcome these challenges by: unifying data through standardized formats and open-source solutions; prioritizing robust cybersecurity measures; investing in training programs to create a skilled workforce; and focusing on user-centric design alongside clear cost-benefit analyses and success stories.  

Societal gains from digital twin technology in flood and water management 

Imagine a virtual replica of your city, constantly monitoring water levels, predicting floods, and optimizing water usage. This, in essence, is the power of digital twins for flood risk and water resource management. Therefore, society should engage with research on the benefits of digital twin technology at this early stage despite challenges such as data availability, model complexity, and cost, as well as ethical considerations related to data privacy and access.  

Enhanced flood preparedness demands a holistic approach that blends real-time data, historical records, simulations, and community insights. Digital twins unlock more precise flood forecasts, granting authorities precious time for warnings and evacuations. A collaborative “whole-of-society” approach is vital to evaluate potential flood scenarios, guiding strategic responses, prioritizing critical infrastructure, and minimizing damage. Continuous monitoring of flood control systems through improved infrastructure management is crucial for preventative maintenance and repairs, ultimately reducing the risk of catastrophic infrastructure failure during floods (6). 

Water security also remains a complex challenge for millions lacking access to clean water, but innovative solutions and responsible management are paving the way for a more sustainable future. We can build this more resilient future where everyone enjoys clean and safe water by tackling societal challenges such as infrastructure gaps and pollution, embracing innovations such as water-saving technologies and desalination, and ensuring equitable access for marginalized communities. Digital twins, acting as virtual water managers, can pinpoint inefficiencies in allocation across sectors, allowing for optimized distribution and minimizing waste, a crucial step toward water security for all. 

Acknowledgement

The author would like to thank all funders who support the CGIAR Initiative on Climate Resilience research through their contributions to the CGIAR Trust Fund: www.cgiar.org/funders.

References

1. The World Bank. Pakistan: Flood Damages and Economic Losses Over USD 30 billion and Reconstruction Needs Over USD 16 billion - New Assessment (2022). Available at: https://www.worldbank.org/en/news/press-release/2022/10/28/pakistan-flood-damages-and-economic-losses-over-usd-30-billion-and-reconstruction-needs-over-usd-16-billion-new-assessme 

2. Dari J, Brocca L, Quintana-Seguı́ P, Escorihuela MJ, Stefan V, Morbidelli R. Exploiting high-resolution remote sensing soil moisture to estimate irrigation water amounts over a Mediterranean region. Remote Sens (2020) 12(16):2593. doi: 10.3390/rs12162593 

3. Rigon R, Formetta G, Bancheri M, Tubini N, D’Amato C, David O, et al. HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists. Hydrol Earth Syst Sci (2022) 26:4773–800. doi: 10.5194/hess-26-4773-2022 

4. Brocca L, Barbetta S, Camici S, Ciabatta L, Dari J, Filippucci P, et al. A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations. Front Sci (2024) 1:1190191. doi: 10.3389/fsci.2023.1190191 

5. Ghaith M, Yosri A, El-Dakhakhni W. Synchronization-enhanced deep learning early flood risk predictions: the core of data-driven city digital twins for climate resilience planning. Water (2022) 14:3619. doi:10.3390/w14223619 

6. Ye X, Du J, Han Y, Newman G, Retchless D, Zou L, et al. Developing human-centered urban digital twins for community infrastructure resilience: a research agenda. J Plan Lit (2023) 38(2):187–99. doi:10.1177/08854122221137861 

7. Verdict. Digital twins: Key to addressing climate change. GlobalData Thematic Intelligence (2023). Available at: https://www.verdict.co.uk/digital-twins-combat-climate-change/