Reflections on the Application of Environmental Data Science in Environmental Systems Under the Background of Climate Risk
DOI:
https://doi.org/10.54097/nwcz2n38Keywords:
Climate risk, Environmental data science, Environmental system, Intelligent modeling, Digital twins, Ecological resilience governanceAbstract
Global climate change grows increasingly severe, with compound climate risks repeatedly disrupting natural ecosystems and urban living environments. Applying targeted technologies to strengthen risk prevention mechanisms stands as a key priority in environmental governance. Drawing on the WMO 2024 Global Climate Report, key findings from the IPCC Sixth Assessment, and the ongoing operations of 33,000 national ecological monitoring stations, this paper explores the technical framework and practical applications of environmental data science. The article elaborates on the practical value of this discipline in the fields of watershed ecological governance, urban environmental operation and maintenance, and regional ecological protection, and identifies prominent practical problems such as data resource fragmentation and insufficient model regional adaptability in industry development. Based on the actual development of ecological governance in China, this article proposes feasible improvement ideas with targeted measures. These findings offer robust theoretical and practical insights for strengthening climate risk resilience, enhancing environmental systems’ ecological carrying capacity, and advancing refined ecological governance based on environmental data science.
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