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Analyses et simulations multifractales pour une meilleure gestion des eaux pluviales en milieu urbain et péri-urbain

机译:多重分形分析和模拟,以更好地管理城市和城市周边地区的雨水

摘要

The Universal Multifractals (UM) are a powerful tool which has been extensively used to analyze and simulate geophysical fields, such as rainfall, that are extremely variable over wide range of scales. It is based on the concept of cascade phenomenology that relies on the physical notion of scale invariance to explore the fundamental phenomenon of intermittency. In this framework the whole variability of a field is characterized with the help of only three parameters that are furthermore physically meaningful. In this PhD thesis we use this theoretical framework to quantify the impacts of small scale rainfall variability in urban hydrology. The first step consists in analysing radar rainfall space-time variability with the help of a simple anisotropic multifractal model. A variety of rainfall events are analyzed. It appears that a scaling behaviour was observed on two distinct ranges of scales separated by a break at roughly 16 km that is discussed. These data sets are in overall agreement with a simple space-time scaling model relying on single anisotropy exponent between space and time. The results hint at a possible universality of the UM parameters for rainfall. This thesis also explores another facet of intermittency, which is particularly important for long time series of precipitation, that of numerous zero rainfall measurements (a pixel or a time step with no recorded rainfall), i. e. long “dry” periods. We revisit the long lasting discussion on the source of this intermittency, e.g. whether it requires a specific modelling. First the effects of a threshold on a universal multifractal field are investigated and second a toy model that introduces some zeros within the cascade process conditioned by the field value is developed. This enables to explain most of the observed behaviour, e.g. the difference between event statistics and overall statistics. The impact of rainfall variability is investigated through the analysis of the sensitivity to the rainfall input of urban hydrologic-hydraulic models. Two predominantly urban catchments (a 3 400 ha one in Seine-Saint-Denis near Paris, and a 900 ha one in London) modelled with the help of operational semi-distributed models are used as case studies. The fully distributed model Multi-Hydro (under development at LEESU) is also tested on a 147 ha portion of the Paris case study. First the impact of unmeasured small scale rainfall variability (i.e. occurring at scales smaller than 1 km in space and 5 min in time which are available with C-band radar data) is evaluated. This is achieved by generating an ensemble of realistic downscaled rainfall fields by continuing the stochastic cascade process below the observation scale and then simulating the corresponding ensemble of hydrographs. It appears that the small scale rainfall variability generates significant hydrological variability that should not be neglected. Furthermore the Multi-Hydro model generates a larger variability not only during the peak flow, but during the whole event, i.e. for moderate rain rates. These findings highlight the need to implement X-band radars (whose resolution is hectometric) in urban areas. In a second part multifractal tools are used on both rainfall and simulated discharges that also exhibit a scaling behaviour. It appears that the rainfall drainage system basically transmits the rainfall variability without damping it, at least in terms of multifractal statistics
机译:通用多重分形(UM)是一种功能强大的工具,已广泛用于分析和模拟地球物理场(例如降雨),这些场在很大范围内变化很大。它基于级联现象学的概念,该级联现象依赖于尺度不变性的物理概念来探究间歇性的基本现象。在此框架中,仅通过三个在物理上有意义的参数来描述整个场的可变性。在本博士学位论文中,我们使用这一理论框架来量化小尺度降雨变化对城市水文学的影响。第一步是借助简单的各向异性多重分形模型来分析雷达降雨的时空变化。分析了各种降雨事件。似乎在讨论的大约16 km处的一个断裂分开的两个不同尺度范围上观察到了尺度变化行为。这些数据集与一个简单的时空缩放模型完全一致,该模型依赖于时空之间的单个各向异性指数。结果暗示了降雨的UM参数可能具有普遍性。本论文还探讨了间歇性的另一个方面,这对于长时间的降水序列来说尤其重要,即大量零降雨测量(一个像素或一个没有记录到的降雨的时间步长),即。 e。较长的“干燥”时期。我们重新讨论了有关这种间歇性来源的长期讨论,例如是否需要特定的建模。首先,研究了阈值对通用多重分形场的影响,其次,建立了一个玩具模型,该玩具模型在以场值为条件的级联过程中引入了一些零。这可以解释大多数观察到的行为,例如事件统计信息与总体统计信息之间的差异。通过分析城市水文水力模型对降雨输入的敏感性,研究了降雨变化的影响。案例分析以两个主要城市集水区为例(在巴黎附近的塞纳-圣但尼地区为3 400公顷,在伦敦为900公顷)。全分布式模型Multi-Hydro(由LEESU开发)也已在巴黎案例研究的147公顷部分中进行了测试。首先,评估未经测量的小尺度降雨变化性的影响(即,发生在小于1 km的尺度和5分钟的时间尺度上,这是C波段雷达数据可得的)。这是通过在观测范围以下继续随机级联过程并模拟水文图的相应集合来生成现实的按比例缩小的降雨场的集合而实现的。看来小规模的降雨变化会产生明显的水文变化,这一点不容忽视。此外,Multi-Hydro模型不仅在峰值流量期间,而且在整个事件期间(即适中的降雨率)都产生较大的变化性。这些发现强调了在城市地区实施X波段雷达(其分辨率为公制)的必要性。在第二部分中,在降雨和模拟流量上都使用了多重分形工具,它们也表现出水垢行为。看来,至少在多重分形统计方面,降雨排水系统基本上在不减弱降雨的情况下传递了降雨变异性

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    Gires Auguste;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 fr
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