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Space variability impacts on hydrological responses of nature-based solutions and the resulting uncertainty: a case study of Guyancourt (France)

机译:空间变异性对自然基础解决方案水文反应的影响以及由此产生的不确定性 - 以Guyancourt(法国)为例

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During the last few decades, the urban hydrological cycle has been strongly modified by the built environment, resulting in fast runoff and increasing the risk of waterlogging. Nature-based solutions (NBSs), which apply green infrastructures, have been more and more widely considered as a sustainable approach for urban storm water management. However, the assessment of NBS performance still requires further modelling development because of hydrological modelling results strongly depend on the representation of the multiscale space variability of both the rainfall and the NBS distributions. Indeed, we initially argue this issue with the help of the multifractal intersection theorem. To illustrate the importance of this question, the spatial heterogeneous distributions of two series of NBS scenarios (porous pavement, rain garden, green roof, and combined) are quantified with the help of their fractal dimension. We point out the consequences of their estimates. Then, a fully distributed and physically based hydrological model (Multi-Hydro) was applied to consider the studied catchment and these NBS scenarios with a spatial resolution of 10?m. A total of two approaches for processing the rainfall data were considered for three rainfall events, namely gridded and catchment averaged. These simulations show that the impact of the spatial variability in rainfall on the uncertainty of peak flow of NBS scenarios ranges from about 8?% to 18?%, which is more significant than those of the total runoff volume. In addition, the spatial variability in the rainfall intensity at the largest rainfall peak responds almost linearly to the uncertainty of the peak flow of NBS scenarios. However, the hydrological responses of NBS scenarios are less affected by the spatial distribution of NBSs. Finally, the intersection of the spatial variability in rainfall and the spatial arrangement of NBSs produces a somewhat significant effect on the peak flow of green roof scenarios and the total runoff volume of combined scenarios.
机译:在过去几十年中,城市水文周期受到建筑环境强烈修改,导致快速径流,增加了涝渍的风险。适用绿色基础设施的基于自然的解决方案(NBSS)越来越被广泛地被视为城市灾害水管理的可持续方法。然而,由于水文建模的结果,对NBS性能的评估仍然需要进一步的建模发展,这强烈依赖于降雨量和NBS分布的多尺度空间变异性的代表性。实际上,我们最初在多分形交叉定理的帮助下争论这个问题。为了说明这个问题的重要性,在其分形尺寸的帮助下,两组NB场景(多孔路面,雨水花园,绿色屋顶和组合)的空间异质分布量。我们指出了估计的后果。然后,应用完全分布的和物理基础的水文模型(多氢),以考虑研究的集水区和这些NB场景,其空间分辨率为10?m。共有两种处理降雨数据的两种方法都被认为是三个降雨事件,即包装和集水区。这些模拟表明,NBS情景峰值流量不确定度的空间变异性的影响范围为约8?%至18倍,这比总径流量更大。此外,最大降雨峰值的降雨强度的空间变异几乎线性地响应了NB场景峰值流量的不确定性。然而,NBS情景的水文应答受到NBS的空间分布的影响。最后,降雨中的空间变异性和NBS的空间排列对绿色屋顶场景的峰值流和组合方案的总径流量产生了一些显着影响。

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