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Watershed Planning within a Quantitative Scenario Analysis Framework
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在流域建模和管理中充分利用"低质量"数据集:从参数校准的角度来看
Yi Rong1, Chengxin Qin2, Haw Yen3
1Tsinghua University, China; Chinese Academy of Environmental Planning, China.
Journal of environmental management
|January 3, 2024
概括
校准数据集质量显著影响模型可靠性. 有缺陷的数据集仍然可以对模型校准有价值,这取决于水文过程,建议仔细选择数据并进行一致性检查.
科学领域:
- 水文学和环境建模环境建模
- 水资源管理 水资源管理
背景情况:
- 模型校准在很大程度上依赖于数据质量,但缺陷数据集的影响仍未得到充分探索.
- 现有的研究对使用不完整或错误的校准数据提供了不足的指导.
研究的目的:
- 建立一个评估框架,评估校准数据质量对参数识别性,灵敏性和不确定性 (ISU) 的影响.
- 使用案例研究量化各种数据缺陷对模型校准的影响.
主要方法:
- 开发了一个框架,用三个定量指标来衡量ISU.
- 在大庆河流域使用SWAT模型对79个有缺陷的数据集 (观测错误,低频/持续/分辨率) 进行了理想数据集的评估.
主要成果:
- 确定了4个关键参数 (天花板,地下水,通道),具有高的ISU.
- 短的数据持续时间造成了最大的ISU差距 (0.61),而低监测频率造成了最小的差距 (-0.28).
- 一些有缺陷的数据集产生了可接受的校准,这取决于水文过程和数据的统计特性.
结论:
- 有缺陷的数据集可以用于模型校准,如果根据水文过程和决策目标仔细选择.
- 建议的做法包括与流程相关的数据选择,数据集重组和低质量的数据的风险自我报告,以提高流域管理的可靠性.
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