Method of hierarchical global sensitivity analysis and its application in groundwater models
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摘要:
在地下水建模中, 为了更好地利用有限的资金和资源去最优化地降低预测结果的不确定性, 需要使用敏感性分析来测算各个模型输入因素的重要性。提出了改进的层级制全局敏感性分析方法来量化不同类型的输入不确定性对输出结果不确定性的贡献, 并以此评估地下水模型中各个不确定性过程对输出结果的影响程度; 使用一个理想的地下水污染运移模拟模型作为算例对该新方法进行了测试和展示。结果表明, 模型的不确定性是该案例预测结果不确定性的主要来源, 而且地质模型的不确定性相较于其他模型更为重要。该方法能够为地下水模型提供更加全面的敏感性分析, 相较于传统的参数敏感性分析, 新方法能够考虑的不确定性输入因素更多, 计算效率明显提升, 可为模型使用者和管理者提供更有用的敏感性信息。
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关键词:
- 地下水模型 /
- 不确定性 /
- 全局敏感性分析 /
- 层级制全局敏感性分析
Abstract:Objective Sensitivity analysis is an crucial tool in groundwater modelling for measuring the importance of various model inputs, enabling better allocation of limited funds and resources to reduce predictive uncertainty.
Methods In this paper, we propose an enhanced hierarchical global sensitivity analysis method to quantify contribution of different types of input uncertainty to model outputs, and to assess the impact of each uncertain process on groundwater model predictions. To test and demonstrate the new method, a hypothetical case study of groundwater flow and contaminant transport is used to validate.
Results The results indicate that model uncertainty is the main source of prediction uncertainty in this case, and uncertainty from the geological model is more important than that of other models.
Conclusion The proposed method offers a more comprehensive sensitivity analysis for groundwater models. Compared with traditional parameter sensitivity analysis, the new method can consider more uncertain input factors, significantly improve computational efficiency, and provide more useful sensitivity information for model users and managers.
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