Temporal and spatial resolution of rainfall measurements required for urban hydrology

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

doi:10.1016/j.jhydrol.2004.08.002

Cited by 191 publications

(227 citation statements)

References 17 publications

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“…Critical to this exercise is the availability of forcing data, such as precipitation, radiation, humidity, temperature, and wind speed, that have sufficient information content on the scale being evaluated such that it can adequately characterize the variable (e.g., soil moisture) or process (e.g., evapotranspiration, runoff) being studied (e.g., Berne et al, 2004). Similarly, the parameters provided to the model must also contain information about the variable or process being studied on a particular spatial and temporal scale.…”

Section: Scaling and Similarity Hypothesesmentioning

confidence: 99%

Scaling, similarity, and the fourth paradigm for hydrology

Peters‐Lidard

Clark

Samaniego

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm) and assert that it is time for hydrology to embrace a fourth paradigm of dataintensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing; describe a mutual information framework for testing these hypotheses; describe boundary condition, state, flux, and parameter data requirements across scales to support testing these hypotheses; and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.

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Section: Scaling and Similarity Hypothesesmentioning

confidence: 99%

Scaling, similarity, and the fourth paradigm for hydrology

Peters‐Lidard

Clark

Samaniego

et al. 2017

Hydrol. Earth Syst. Sci.

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“…Several studies have shown that drainage area is one of the dominating factors affecting the variation in urban hydrological re-25 sponses resulting from using rainfall at different spatial and temporal resolutions as input (Berne et al, 2004;Ochoa-Rodriguez et al, 2015;Yang et al, 2016). Considering a bigger drainage area implies aggregating and averaging rainfall and consequently smoothing rainfall peaks, with the result of having big areas that are less sensitive to high resolution measurements.…”

Section: Models' Spatial Scalesmentioning

confidence: 99%

“…Several authors have proposed different time scale characteristics (see for a review), but no unique formulation has been chosen yet, especially for urban areas. Time of concentration (McCuen et al, 1984;Singh, 1997;Musy and Higy, 2010) and lag time (Berne et al, 2004;Marchi et al, 2010) are the most commonly used temporal model scales, but other time length have 20 been proposed in the literature (Ogden et al, 1995;Morin et al, 2001). In this study, temporal variability of the three models was classified using lag time t lag , which describes the runoff delay compared to rainfall input.…”

Section: Models' Temporal Scalesmentioning

confidence: 99%

“…Finding a proper match between rainfall resolution and hydrological model structure and complexity is important for reliable flow prediction (Berne et al, 2004;Ochoa-Rodriguez et al, 2015;Pina et al, 2016;Rafieeinasab et al, 2015;Yang et al, 2016). High resolution rainfall data are required to reduce errors in estimation of hydrological responses in small urban catchments (Niemczynowicz, 1988;Schilling, 1991;Berne et al, 2004;Bruni et al, 2015;Yang et al, 2016). New technologies and instruments have been developed in 20 order to improve rainfall measurements and capture its spatial and temporal variability (Einfalt et al, 2004;Thorndahl et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Critical scales to explain urban hydrological response

Cristiano

Veldhuis

Gaitan

et al. 2018

Preprint

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Abstract. Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a Dual polarimetric X-Band radar at the CAESAR Site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution 5 combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this study 10 case, (4) scaling factors allow to select the adequate rainfall resolution to obtain a given level of accuracy in the calculation of hydrological response.

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“…To account for the temporal and spatial variability of precipitation, there are several advanced approaches such as weather radar, satellite rainfall estimation algorithms, and numerical weather models. However, most cases require a validation and calibration process with measured rainfall data from existing rain gauges to reduce the measurement errors (Frei and Schär 1998;Pardo-Igúzquiza 1998;Adler et al 2001;McCollum et al 2002;Berne et al 2004;Xie et al 2007;Chen et al 2008;Piman and Babel 2013). In addition, some studies combined the remotely sensed data with rain-gauge measurements for better estimates of point or areal rainfalls (Krajewski 1987;North et al 1991).…”

Section: Introductionmentioning

confidence: 99%

Rain-Gauge Network Evaluations Using Spatiotemporal Correlation Structure for Semi-Mountainous Regions

Jung¹,

Kim²,

Baik³

et al. 2014

Terr. Atmos. Ocean. Sci.

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A reliable network of rain gauges is a crucial component of rainfall estimation in a watershed. To provide a better evaluation method for rain-gauge networks, a new evaluation method using average inter-gauge correlation coefficients (averaged CC) for estimating an effective radius for each rain gauge was developed. In this study, averaged CCs were obtained from the values of inter-gauge correlation coefficients after choosing a minimum number of rainfall data sets as a threshold. The Nam River Basin (2400 km 2 ) and its 24 rain gauges were selected with 8 years (2003 -2010) rainfall data to validate a new evaluation method. In the spatial correlation coefficient fitting process for generating correlation distances, averaged CCs increased fitness accuracy (maximum 37%) in terms of coefficient of determination (R 2 ) compared with a commonly used method (the last value of the inter-gauge correlation coefficient as the number of data sets is increased: last CC). In the evaluation of effective radii for 8 years, the robustness of the averaged CCs was supported by lower standard deviations for all rain gauges. For the optimum coverage of rainfall estimation in terms of effective radius, the Nam River Basin requires 20 rain gauges. Investigation of altitude effects presented that the effective radii were minimally influenced by the altitude of rain-gauge locations for this area.

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Temporal and spatial resolution of rainfall measurements required for urban hydrology

Cited by 191 publications

References 17 publications

Scaling, similarity, and the fourth paradigm for hydrology

Scaling, similarity, and the fourth paradigm for hydrology

Critical scales to explain urban hydrological response

Rain-Gauge Network Evaluations Using Spatiotemporal Correlation Structure for Semi-Mountainous Regions

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