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Disentangling the effects of climate and urban growth on streamflow for sustainable urban development: A stochastic approach to flow regime attribution

机译:剥夺气候和城市增长对可持续城市发展流流的影响:流动制度归因的随机方法

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In urban watersheds, climate variability and change, urban growth, and stormwater management can act concurrently over time to shape and alter the streamflow dynamics. Yet, when assessing the impacts of urbanization on streamflow, these factors are rarely taken simultaneously into consideration. There is thus an emerging need for approaches that allow disentangling the hydrological impacts of land cover change from those due to climate, in the context of long-term, historical changes in urban landscapes. This is here termed flow regime attribution. We demonstrate in this study the ability of a stochastic mechanistic model to perform flow regime attribution. The modeling approach is applied to the Watts Branch watershed, located in metropolitan Washington D.C., United States. To carry out the flow regime attribution, the model is used to compute streamflow indicators of hydrological alteration and perform parameter sensitivity analysis. The application of the model shows that in Watts Branch urban growth drives the long-term temporal trend in streamflow. The mean and variance of streamflow increase at the end of the gauging period by 2 and 7 times, respectively, their value relative to an only climate (no urban growth) scenario. The results show that climate mainly amplifies or dampens the temporal trend according to wet/dry variations in annual rainfall. Further, the model facilitates the attribution process by allowing the derivation of streamflow indicators that directly depend on the model parameters. The proposed modeling approach may be useful for assessing the long-term flow behavior of urban watersheds, and informing sustainable urban development decisions.
机译:在城市流域,气候变化和变化,城市成长和雨水管理可以随着时间的推移而塑造和改变流流动态。然而,在评估城市化对流出的影响时,很少考虑这些因素。因此,在长期历史变化的情况下,允许解除陆地覆盖陆地覆盖变化的水文影响的方法的新兴需求。这在此处称为流动制度归因。我们在这研究中表明了随机机械模型进行流动制度归因的能力。建模方法适用于美国大都会华盛顿大都会的瓦特分公司。要执行流动制度归因,该模型用于计算水文改变的流流量指标并执行参数灵敏度分析。该模型的应用表明,瓦特分公司城市增长推动了流流中的长期时间趋势。流出时期末端的流流量的平均值和变化分别在2和7次的情况下,其值相对于唯一的气候(无城市增长)情景。结果表明,根据年降雨量的湿润/干法,气候主要放大或抑制时间趋势。此外,该模型通过允许直接取决于模型参数的StreamFlow指示符来促进归因过程。拟议的建模方法可用于评估城市流域的长期流动行为,并告知可持续的城市发展决策。

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