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Multi-Source Uncertainty Analysis in Simulating Floodplain Inundation under Climate Change

机译:气候变化模拟洪泛区淹没的多源不确定性分析

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Floodplains are highly complex and dynamic systems in terms of their hydrology. Thus, they harbor highly specialized floodplain plant species depending on different inundation characteristics. Climate change will most likely alter those characteristics. This study investigates the potential impact of climate change on the inundation characteristics of a floodplain of the Rhine River in Hesse, Germany. We report on the cascading uncertainty introduced through climate projections, climate model structure, and parameter uncertainty. The established modeling framework integrates projections of two general circulation models (GCMs), three emission scenarios, a rainfall–runoff model, and a coupled surface water–groundwater model. Our results indicate large spatial and quantitative uncertainties in the simulated inundation characteristics, which are mainly attributed to the GCMs. Overall, a shift in the inundation pattern, possible in both directions, and an increase in inundation extent are simulated. This can cause significant changes in the habitats of species adapted to these highly-endangered ecosystems.
机译:就水文而言,洪泛区是高度复杂和动态的系统。因此,根据不同的淹没特征,它们藏有高度专业的洪泛区植物物种。气候变化很可能会改变这些特征。这项研究调查了气候变化对德国黑森州莱茵河泛滥区的淹没特征的潜在影响。我们报告了通过气候预测,气候模型结构和参数不确定性引入的级联不确定性。建立的建模框架集成了两个通用循环模型(GCM),三个排放情景,降雨径流模型以及地表水-地下水耦合模型的预测。我们的结果表明,模拟淹没特征存在较大的空间和数量不确定性,这主要归因于GCM。总体而言,模拟了在两个方向都可能发生的淹没模式的转变以及淹没程度的增加。这可能会导致适应这些高度濒危生态系统的物种的栖息地发生重大变化。

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