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利用机器学习评估气候变化对地下水资源的影响:全面审查

Apoorva Bamal^1,2,3,4, Md Galal Uddin^1,2,3,4, Agnieszka I Olbert^1,2,3,4

¹School of Engineering, University of Galway, Galway, Ireland.

|September 17, 2024

概括

气候变化对地下水水平和质量产生重大影响. 先进的机器学习 (ML) 和人工智能 (AI) 模型在预测这些变化和识别关键气候驱动因素方面表现出极高的准确性.

科学领域:

环境科学环境科学
水文学的水文学
气候科学气候科学
数据科学数据科学数据科学

背景情况:

气候变化对全球水资源,特别是地下水系统构成重大威胁.
温度和降水等气候因素直接影响地下水变量,包括水位,排放,储存和质量.
机器学习 (ML) 和人工智能 (AI) 越来越多地被用来理解和预测这些影响.

研究的目的:

对用于评估气候变化对地下水变量影响的ML/AI模型进行深入审查.
评估各种ML/AI技术在不断变化的气候条件下预测地下水参数的有效性.
综合近期 (2017-2023) 的ML/AI应用在气候变化和地下水研究方面的进展.

主要方法:

2017年至2023年间发表的65篇研究论文的系统文献综述.
专注于利用ML/AI模型分析气候变化对地下水位,排放,储存和质量的影响的研究.
基于类型,分辨率和时间尺度等数据属性的模型性能分析.

主要成果:

神经网络,随机森林 (RF),决策树 (DT) 和支持矢量机器 (SVM) 在预测地下水变化方面表现出高准确性.
混合和整体ML方法进一步提高了地下水变量预测的准确性.
确定了气候变化对地下水数量和质量的重大风险,但对爱尔兰环境的研究有限.

结论:

机器学习/人工智能模型是理解气候变化和地下水资源之间的复杂相互作用的强大工具.
该审查强调了特定的ML/AI算法的有效性,用于预测关键的地下水参数.
研究结果强调需要进一步的研究,特别是在爱尔兰等地区,以应对气候变化相关的地下水挑战.

关键词:

人工智能的人工智能是人工智能.气候变化气候变化气候变化地下水的变量是什么爱尔兰爱尔兰爱尔兰爱尔兰爱尔兰爱尔兰机器学习是机器学习.

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