Exploring the concept of digital twins of wetlands for supporting ecosystem monitoring and management - Bing Lu; Lucie Francescutto; Sarah Howie; Hui Lin; Qiusheng Wu; Nicholas Hedley; Ali Jamali; Ian McDonald (Big Earth Data)
Wetlands provide numerous ecosystems services and benefits that are essential for human society and the environment. However, wetlands have suffered significant loss and degradation globally over the past few centuries due to human disturbances and climate change. It is thus critical to monitor wetlands comprehensively and manage effectively. Meanwhile, comprehensive monitoring is challenging due to difficulties in collecting various wetland data (e.g. in situ hydrological and ecological data, remote sensing images), data analysis using diverse models (e.g. physically based and data-driven), and data visualization. Digital twins, which integrate data collection, analysis, visualization, and sharing into a comprehensive platform, are promising for addressing these challenges. While the concepts and technologies of digital twins have been frequently explored for cities and farms, they have been discussed far less for wetlands. This study attempts to explore the concept of wetland digital twins, identify technologies needed, and discuss associated challenges and opportunities. Though technologies from digital twins of cities and farms are transferable, it is essential to recognize the unique challenges of wetlands, such as their remote locations, limited accessibility, and the need to minimize human interventions. This study aims to bring insights to wetland policymakers and practitioners, promoting digital twins for more effective managements.