Temporal and spatial resolution of rainfall measurements required for urban hydrology

Berne, Alexis; Delrieu, Guy; Creutin, Jean‐Dominique; Obled, Charles

doi:10.1016/s0022-1694(04)00363-4

Cited by 321 publications

(225 citation statements)

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“…The event rainfall depth ranges from 5.5 mm to 196.3 mm, peak rainfall intensity varies from 0.10 mm·min −1 to 4.08 mm·min −1 , and the duration spans from 100 min to 4613 min, covering the high temporal variability of actual rainfall in this region [1]. Compared with the observations from the rain gauge 350 m away (Figures 1 and 2), the measurements by this disdrometer were then used as the representative rainfall data of the entire study area, in particular considering the small size of the area [10] and immediate proximity of the disdrometer site to the center of the study area. Hydrological observations were carried out at three sections on the river, i.e., the inlet, the rear of the branch junction, and the outlet ( Figure 1).…”

Section: Rainfall and Hydrological Data Of High Temporal Resolutionmentioning

confidence: 99%

“…The 30 events with 1-min resolution rainfall were aggregated to obtain rainfall data at other resolutions, including 5 min, 10 min, 15 min, 20 min, 30 min, 60 min, and the whole duration [6,10,17,21]. Particularly, for the rainfall with the resolution of whole duration, it means the original rainfall process was replaced with the stable average rainfall intensity.…”

Section: Characteristics Of Rainfall Data and Upscalingmentioning

confidence: 99%

“…Variogram analysis was conducted theoretically to describe temporal (or spatial) variability as the characteristic scale, which was defined as the temporal (or spatial) distance by which two individual points show statistical independence [3]. Based on this method, Berne et al [10] proposed the relationship between the required characteristic scales of rainfall and urban catchments, and then derived the required rainfall resolution for urban hydrological applications. Emmanuel et al [11] summarized the characteristic scales of rainfall of different types.…”

Section: Introductionmentioning

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: Rainfall and Hydrological Data Of High Temporal Resolutionmentioning

confidence: 99%

Section: Characteristics Of Rainfall Data and Upscalingmentioning

confidence: 99%

Section: Introductionmentioning

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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“…However, the use of spatial rainfall is severely restricted by the absence of suitable high-resolution rainfall data [32] and so in this study we have used uniform rainfall. Spatial rainfall effects could be assessed by running simulations for each city driven by an ensemble of stochastic rainfall model scenarios [33,34] but with major implications for computational cost.…”

Section: Urban Hydrodynamic Modelmentioning

confidence: 99%

Pluvial Flooding in European Cities—A Continental Approach to Urban Flood Modelling

Guerreiro

Glenis

Dawson

et al. 2017

Water

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Pluvial flooding is caused by localized intense rainfall and the flood models used to assess it are normally applied on a city (or part of a city) scale using local rainfall records and a high resolution digital elevation model (DEM). Here, we attempt to model pluvial flooding on a continental scale and calculate the percentage of area flooded for all European cities for a 10-year return period for hourly rainfall (RP10). Difficulties in obtaining hourly rainfall records compromise the estimation of each city RP10 and the Europe-wide DEM spatial resolution is low relative to those typically used for individual case-studies. Nevertheless, the modelling capabilities and necessary computing power make this type of continental study now possible. This is a first attempt at continental city flooding modelling and our methodology was designed so that our results can easily be updated as better/more data becomes available. The results for each city depend on the interplay of rainfall intensity, the elevation map of the city and the flow paths that are created. In general, cities with lower percentage of city flooded are in the north and west coastal areas of Europe, while the higher percentages are seen in continental and Mediterranean areas.

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“…A irregularidade na distribuição temporal da chuva afeta fortemente a produção agrícola e o abastecimento deágua a população (SIDERIUS et al, 2015;TONGWANE e MOELETSI, 2015;NOBRE et al, 2016). Além disso, o conhecimento do regime hidrológicoé fundamental para modelagem de vários fenômenos como inundações, erosão do solo, transporte de poluentes e infiltração (BERNE et al, 2004;MORIASI e STARKS, 2010).…”

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Análise da variabilidade espaço temporal da chuva mensal no estado de Pernambuco utilizando o método entropia de permutação

et al. 2018

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RESUMO: Neste artigo analisou-se a variabilidade espacial da dinâmica da chuva em escala mensal no estado de Pernambuco, utilizando o método entropia de permutação. Este método foi desenvolvido como uma medida da complexidade de séries temporais, considerando as correlações temporais entre os valores da série utilizando uma representação simbólica baseada nas comparações dos valores consecutivos. Os resultados mostraram que os valores da entropia diminuem com a distância do litoral, indicando maior variabilidade e menor previsibilidade das chuvas mensais nas regiões da zona da Mata e Agreste e menor variabilidade e maior previsibilidade das chuvas mensais nas regiões do Sertão Pernambucano. PALAVRAS-CHAVE: Complexidade; precipitação; Pernambuco. IntroduçãoA precipitação pluviométrica tem grande importância na caracterização do clima de uma região. O conhecimento da variabilidade espacial e temporal da precipitação

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Temporal and spatial resolution of rainfall measurements required for urban hydrology

Cited by 321 publications

References 0 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

Pluvial Flooding in European Cities—A Continental Approach to Urban Flood Modelling

Análise da variabilidade espaço temporal da chuva mensal no estado de Pernambuco utilizando o método entropia de permutação

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