用AI构建马拉莫尔潟湖数字孪生平台，模拟生态响应。
Advancing Towards a Marine Digital Twin Platform: Modeling the Mar Menor Coastal Lagoon Ecosystem in the South Western Mediterranean
- 用AI模拟水文与生态模型，实现多情景推演。
- 整合公开数据构建完整动态数字映射。
- 支持实时互动，适合海洋管理者使用。
沿海海洋生态系统正面临人类活动与气候变化的日益加剧的压力，亟需先进的监测与建模方法以实现有效管理。本文首次提出面向穆尔西亚地区马拉莫尔潟湖生态系统的海洋数字孪生平台，利用人工智能技术模拟复杂的水文与生态模型，支持对不同压力源下生态系统响应的‘假设性’情景模拟。平台整合了来自公开渠道的多种数据集，构建了该潟湖动态的全面数字化表征。其模块化设计支持实时利益相关方参与，助力海洋管理中的科学决策。本工作推动了海洋科学通过创新数字孪生技术的发展进程。
原文摘要 · Abstract (English)
Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective management. This paper pioneers the development of a Marine Digital Twin Platform aimed at modeling the Mar Menor Coastal Lagoon Ecosystem in the Region of Murcia. The platform leverages Artificial Intelligence to emulate complex hydrological and ecological models, facilitating the simulation of what-if scenarios to predict ecosystem responses to various stressors. We integrate diverse datasets from public sources to construct a comprehensive digital representation of the lagoon's dynamics. The platform's modular design enables real-time stakeholder engagement and informed decision-making in marine management. Our work contributes to the ongoing discourse on advancing marine science through innovative digital twin technologies.
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