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The Application of Extreme Stochastic Inputs to a Transport Model in the Context of Global Climate Change.

机译:在全球气候变化的背景下,极端随机输入在运输模型中的应用。

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摘要

Global climate is predicted to have significant impacts on the chemical, biological, and physical characteristics of wetlands and the watersheds in which they are contained. In particular, climate prediction models suggest a significant increase in extreme precipitation events - both more frequent and more intense flood and drought occurrences. A wetland model that incorporates surfacewater-groundwater interactions (WETSAND2.0) was used to investigate the potential impacts of these stochastically generated extreme events on wetland flow regimes in an urban watershed. The results predict increases in streamflow and flooding as well as drought conditions on a near yearly basis. However, the model also shows that the impact on the Sandy Creek-Duke University watershed will not be as extreme as many suggest. Although flooding will occur, it will be relatively minor and comparable to historic flows. And although droughts are also predicted, the balance of wet and dry in this wetland watershed can actually be a positive for the environment. Therefore watersheds, no matter the spatial scale, must be analyzed individually. Although some comparisons can be made between similar regions, the effects of extreme precipitation events vary greatly depending on watershed characteristics.
机译:预计全球气候将对湿地及其所包含的流域的化学,生物和物理特征产生重大影响。特别是,气候预测模型表明极端降水事件显着增加-洪水和干旱的发生频率更高,强度更大。结合地表水与地下水相互作用的湿地模型(WETSAND2.0)用于研究这些随机产生的极端事件对城市流域内湿地流态的潜在影响。结果预测,水流和洪水以及干旱情况将在近一年的基础上增加。但是,该模型还表明,对桑迪克里克-杜克大学分水岭的影响不会像许多人所说的那样极端。尽管会发生洪水,但洪水相对较小,可与历史流量相媲美。尽管也预言会发生干旱,但这个湿地流域的干湿平衡实际上对环境有利。因此,无论空间尺度如何,都必须对流域进行单独分析。尽管可以在相似区域之间进行一些比较,但极端降雨事件的影响会根据流域特征而有很大不同。

著录项

  • 作者

    Haerer, Drew M.;

  • 作者单位

    Duke University.;

  • 授予单位 Duke University.;
  • 学科 Hydrology.;Engineering Environmental.;Water Resource Management.
  • 学位 M.S.
  • 年度 2011
  • 页码 70 p.
  • 总页数 70
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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