论文语句摘录(一)

尽管洪水损失估算工具自1980年代以来取得进步,但其高不确定性与差异仍引发质量质疑。本文回顾了公共领域及专业来源的洪水损失模型,强调量化不确定性与模型验证的重要性。由于缺乏可靠数据,基准比较成为提升模型可信度的关键。

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来源:A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.(https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0159791

1.Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality.

翻译:尽管自20世纪80年代以来损失估计工具的开发取得了相当大的进展,但损失估计仍然反映出高度的不确定性和差异,这往往会导致对其质量的质疑。

2.more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential

翻译:需要更多的努力来量化不确定性并进行验证。由于缺乏详细可靠的洪水损失数据,一阶验证难以完成,因此在基准方面进行模型比较是必要的。

3.When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models.

翻译:当通过验证或基准测试确认了这种一致性时,用户就对模型有了信心。

4.this work presents a review of flood loss–or flood vulnerability–relationships collected from the public domain and some professional sources.

翻译:本文对从公共领域和一些专业来源收集的洪水损失(或洪水脆弱性)关系进行了回顾。

5.Flood loss models–or flood vulnerability models–describe the relationship between hazard intensity metrics such as flood depth, velocity, etc. and a damage ratio that can be translated into a monetary quantity. 

翻译:洪水损失模型——或洪水脆弱性模型——描述了洪水深度、速度等灾害强度指标与可转换为货币量的损害率之间的关系。

6.

 

 

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