Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

Fletcher, Tim D.; Andrieu, Hervé; Hamel, Perrine

doi:10.1016/j.advwatres.2012.09.001

Cited by 772 publications

(490 citation statements)

References 200 publications

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“…Unlike traditional 1D-1D or 2D-1D (surface and pipe) models [25], REDUS model can be regarded as a 1D-1D-1D (surface, road ,and pipe) model, which finds a balance between accuracy and efficiency and is easy to be popularized. One advantage of the REDUS model is the detailed formulation of urban hydrodynamic process with the help of high resolution data of underlying surfaces.…”

Section: Model Frameworkmentioning

confidence: 99%

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Effect of Temporal Resolution of Rainfall on Simulation of Urban Flood Processes

Lyu

Cao

et al. 2018

Water

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Rainfall exhibits substantial variability, and its temporal resolution considerably affects simulation of hydrological processes. This study aims to investigate the effect of the temporal resolution of rainfall (TRR) on urban flood modeling and to explore how high TRR is required. A routing-enhanced detailed urban stormwater (REDUS) model, which has four layers and accounts for complex urban flow paths, was developed and then applied to the campus of Tsinghua University, Beijing, China. For 30 rainfall events at 1-min resolution, the rainfall accuracy index (RAI) was used to describe the discrepancy of rainfall patterns by upscaling. Through hydrodynamic modelling, the effect of TRR was quantified by the relative error of flood volume and peak in typical areas. The results show that (1) flood peak is sensitive to TRR while flood volume is generally not; (2) with lower TRR, discharge peak is underestimated, and a power function is proposed to express the relationship between the effect of TRR and the characteristics of rainfall and underlying surfaces; and (3) rainfall data of 5-min resolution for urban areas smaller than 1 km 2 , or at least 15-min resolution for larger areas, are required to constrain the relative biases of flood peak within 10%.

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Section: Model Frameworkmentioning

confidence: 99%

“…Urban hydrologic or hydrodynamic models are essential in investigations of the effect of TRR [25,26]. These models act as filters, that is, they can smooth the influence of temporal and spatial variability of rainfall forcing [27].…”

Section: Introductionmentioning

confidence: 99%

Effect of Temporal Resolution of Rainfall on Simulation of Urban Flood Processes

Lyu

Cao

et al. 2018

Water

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“…There have been many urban waterlogging mitigation measures worldwide such as the Low Impact Development in USA, Water Sensitive Urban Design in Australia and Sponge City in China [10][11][12]. However, the influence mechanisms behind urban waterlogging, as a premise of taking actions, have not yet been fully understood [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Among these factors, the impervious surface was easily obtained by remote sensing images and studied extensively. For example, many studies have been conducted to explore the relationship between impervious surface area and hydrological response (i.e., runoff and peak discharge), which are closely associated with urban waterlogging from the local scale to the watershed scale [11,24]. A few studies explored the relationship between the impervious surface area and the spatial pattern of urban waterlogging risk spots in urban regions [25,26].…”

Section: Introductionmentioning

confidence: 99%

Effects of Impervious Surface on the Spatial Distribution of Urban Waterlogging Risk Spots at Multiple Scales in Guangzhou, South China

Zhang

Cheng

et al. 2018

Sustainability

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An impervious surface is considered one of main factors affecting urban waterlogging. Previous studies found that spatial pattern (composition and configuration) of impervious surfaces affected urban waterlogging. However, their relative importance remains unknown, and the scale-effect of the spatial pattern on urban waterlogging has been ignored. To move forward, our research studied the relationship between spatial patterns on the impervious surface and its subcategories (building and pavement) on urban waterlogging risk spots using Pearson correlation, partial redundancy analysis and performed at three grid scales (1 km × 1 km, 3 km × 3 km, 5 km × 5 km) and the catchment scale based on different spatial resolution land cover maps (2 m, 10 m and 30 m). We identified positively-correlated metrics with urban waterlogging risk spots, such as the composition of impervious surface (i.e., total impervious surface, building, pavement) and the aggregation metric of the total impervious surface at most scales, as well as two negatively correlated metrics (i.e., proximity metric of building, fragmentation metric of total impervious surface). Furthermore, the total variance of urban waterlogging risk spots explained by the spatial pattern of the total impervious surface and its subcategories increased with studied grid and catchment scales while decreasing from a fine to a coarse resolution. The relative contribution of the impervious surface composition and configuration to the variation of urban waterlogging risk spots varied across scales and among impervious surface types. The composition contributed more than the configuration did for the total impervious surface at both grid and catchment scales. Similar to total impervious surface, the composition of buildings was more important than its configuration was at all the grid scales, while the configuration of buildings was more important at the catchment scale. Contrary to the total impervious surface, the configuration of pavement at both the grid and catchment scales mattered more than their compositions did. Furthermore, the composition of the building was more important than that of pavement, but its configuration mattered less. Our study could provide a multi-scale landscape perspective with detailed suggestions for controlling the area of impervious surface and optimizing its spatial configuration in urban waterlogging risk mitigation and urban planning.

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“…On the other hand, the population growth in cities has required an increase in the construction of buildings, roads, and other civil infrastructures. As a result, the soil in these areas has lost rainwater absorption capacity, making cities more vulnerable to flooding in the presence of heavy rain events [3,4]. Additionally, weather phenomena such as global warming have increased the frequency, intensity, and duration of rain events in many areas [2,5].…”

Section: Introductionmentioning

confidence: 99%

Modeling and real-time control of urban drainage systems: A review

Garcia¹,

Barreiro-Gómez

Escobar³

et al. 2015

Advances in Water Resources

201

113

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Urban drainage systems (UDS) may be considered large-scale systems given their large number of associated states and decision actions, making challenging their real-time control (RTC) design. Moreover, the complexity of the dynamics of the UDS makes necessary the development of strategies for the control design. This paper reviews and discusses several techniques and strategies commonly used for the control of UDS. Moreover, the models to describe, simulate, and control the transport of wastewater in UDS are also reviewed.

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Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

Cited by 772 publications

References 200 publications

Effect of Temporal Resolution of Rainfall on Simulation of Urban Flood Processes

Effect of Temporal Resolution of Rainfall on Simulation of Urban Flood Processes

Effects of Impervious Surface on the Spatial Distribution of Urban Waterlogging Risk Spots at Multiple Scales in Guangzhou, South China

Modeling and real-time control of urban drainage systems: A review

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