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Pluvial flooding in urban regions is a natural hazard that has been rarely investigated. Here, we evaluate the utility of three radar (Stage IV, Multi-Radar Multi-Sensor or MRMS, and gauge-corrected MRMS or GCMRM) quantitative precipitation estimates (QPEs) and the Storm Water Management Model (SWMM) hydrologic–hydraulic model to simulate pluvial flooding during the North American monsoon in Phoenix. We focus on an urban catchment of 2.38 km2 and, for four storms, we simulate a set of flooding metrics using the original QPEs and an ensemble of 100 QPEs characterizing radar uncertainty through a statistical error model. We find that Stage IV QPEs are the most accurate, while MRMS QPEs are positively biased and their utility to simulate flooding increases with the gauge correction done for GCMRMS. For all radar products, simulated flood metrics have lower uncertainty than QPEs as a result of rainfall–runoff transformation. By relying on extensive precipitation and basin datasets, this work provides useful insights for urban flood predictions. [ABSTRACT FROM AUTHOR]

Multisource rainfall products can be used to overcome the absence of gauged precipitation data for hydrological applications. This study aims to evaluate rainfall estimates from the Chinese S-band weather radar (CINRAD-SA), operational raingauges, multiple satellites (CMORPH, ERA-Interim, GPM, TRMM-3B42RT) and the merged satellite–gauge rainfall products, CMORPH-GC, as inputs to a calibrated probability distribution model (PDM) on the Qinhuai River Basin in Nanjing, China. The Qinhuai is a middle-sized catchment with an area of 799 km2. All sources used in this study are capable of recording rainfall at high spatial and temporal resolution (3 h). The discrepancies between satellite and radar data are analysed by statistical comparison with raingauge data. The streamflow simulation results from three flood events suggest that rainfall estimates using CMORPH-GC, TRMM-3B42RT and S-band radar are more accurate than those using the other rainfall sources. These findings indicate the potential to use satellite and radar data as alternatives to raingauge data in hydrological applications for ungauged or poorly gauged basins. [ABSTRACT FROM AUTHOR]

The spread of impervious surfaces in urban areas combined with the rise in the intensity of rainfall events as a result of climate change has led to dangerous increases in storm water flows. This paper discusses a new implementation of the fully distributed hydrological model Multi-Hydro (developed at École des Ponts ParisTech), when operating storage basins, and its ability to deal with high-resolution radar rainfall data. The peri-urban area of Massy (south of Paris, France) was selected as a case study for having six of these drainage facilities, used extensively in flood control. Two radar rainfall datasets with different spatiotemporal resolutions were used: Météo-France’s PANTHER rainfall product (C-band) and ENPC’s X-band DPSRI. The rainfall spatiotemporal variability was analysed statistically using Universal Multifractals (UM). Finally, to validate the application, the water level simulations were compared with local measurements in the Cora storage basin located next to the catchment’s single outlet. [ABSTRACT FROM AUTHOR]

Knowledge of rainfall characteristics such as drop-size distribution is essential for the development of erosion-mitigation strategies and models. This research used an optical disdrometer to elucidate the relationships between raindrop-size distribution, median volume drop diameter (D50), kinetic energy and radar reflectivity (dBz) of simulated rainfall of different intensities. The D50 values were higher for the simulated rain than for natural rain at almost all rainfall intensities, perhaps due to variations in rainfall types and the turbulence in natural rain that breaks up large drops. The kinetic energy ranged from 26.67 to 5955.51 J m−2 h −1, while the median volume drop diameter (D50) was in the range 1.94-7.25 mm, for intensities between 1.5 and 202.6 mm h−1. The relationship between radar reflectivity (Z) and the intensity (R) of the simulated rain was best described by a power law function (Z = aRb), with a and b coefficients in the ranges 162-706 and 0.94-2.46, respectively, throughout the range of rainfall intensities (1.5-202.6 mm h−1). [ABSTRACT FROM AUTHOR]

This study is about use of spatially distributed rain in physically based hydrological models. In recent years, spatially distributed radar rainfall data have become available. The distributed radar rain is used to precisely model hydrologic processes and it is more realistic than the past practice of distribution methods like Thiessen polygons. Radar provides a highly accurate spatial distribution of rainfall and greatly improves the basin average rainfall estimates. However, quantification of the exact amount of rainfall from radar observation is relatively difficult. Thus, the fundamental idea of this study is to apply hourly gauge and radar rainfall data in a distributed hydrological model to simulate hydrological parameters. Hence the comparison is made between the outcomes of the WetSpa model from radar rainfall distribution and gauge rainfall distributed by the Thiessen polygon technique. The comparative plots of the hydrograph and the results of hydrological components such as evapotranspiration, surface runoff, soil moisture, recharge and interflow, reflect the spatially distributed radar input performing well for model outflow simulation. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR F. Pappenberger [ABSTRACT FROM AUTHOR]

Spatial variability of rainfall has been recognised as an important factor controlling the hydrological response of catchments. However, gauged daily rainfall data are often available at scattered locations over the catchments. This paper looks into how to capitalise on the spatial structure of radar rainfall data for improving kriging interpolation of limited gauge data over catchments at the 1-km2grid scale, using for the case study 117 gauged stations within the 128 km × 128 km region of the Mt Stapylton weather radar field (near Brisbane, Australia). Correlograms were developed using a Fast Fourier Transform method on the Gaussianised radar and gauged data. It is observed that the correlograms vary from day to day and display significant anisotropy. For the radar data, locally varying anisotropy (LVA) was examined by developing the correlogram centred on each pixel and for different radial distances. Cross-validation was carried out using the empirical correlogram tables, as well as different fitting strategies of a two-dimensional exponential distribution for both the gauged and the radar data. The results indicate that the correlograms based on the radar data outperform the gauged ones as judged by statistical measures including root mean square error, mean bias, mean absolute bias, mean standard deviation and mean inter-quartile range. While the radar data display significant LVA, it was observed that LVA did not significantly improve the estimates compared with the global anisotropy. This was also confirmed by conditional simulation of 120 rainfields using different options of correlogram development.EDITOR M.C. Acreman; ASSOCIATE EDITOR Q. Zhang [ABSTRACT FROM AUTHOR]

In this paper a universal multifractals comparison of the outputs of two types of collocated optical disdrometers installed on the roof of the Ecole des Ponts ParisTech is performed. A Campbell Scientific PWS100 which analyses the light scattered by the hydrometeors and an OTT Parsivel2which analyses the portion of occluded light are deployed. Both devices provide a binned distribution of drops according to their size and velocity. Various fields are studied across a range of scales: rain rate (R), liquid water content (ρ), polarimetric weather radar quantities such the horizontal reflectivity (Zh) and the specific differential phase (Kdp), and drop size distribution (DSD) parameters such as the total drop concentration (Nt) and the mass-weighted diameter (Dm). For both devices, good scaling is retrieved on the whole range of available scales (2 h–30 s), except for the DSD parameters for which the scaling only holds down to few minutes. ForR, the universal multifractal parameters are found to equal 1.5 and 0.2 forαandC1, respectively. Results are interpreted with the help of the classicalZh–RandR–Kdpradar relations.Editor D. Koutsoyiannis; Associate editor E. Volpi [ABSTRACT FROM AUTHOR]

Given that radar-based rainfall has been broadly applied in hydrological studies, quantitative modelling of its uncertainty is critically important, as the error of input rainfall is the main source of error in hydrological modelling. Using an ensemble of rainfall estimates is an elegant solution to characterize the uncertainty of radar-based rainfall and its spatial and temporal variability. This paper has fully formulated an ensemble generator for radar precipitation estimation based on the copula method. Each ensemble member is a probable realization that represents the unknown true rainfall field based on the distribution of radar rainfall (RR) error and its spatial error structure. An uncertainty model consisting of a deterministic component and a random error factor is presented based on the distribution of gauge rainfall conditioned on the radar rainfall (GR|RR). Two kinds of copulas (elliptical and Archimedean copulas) are introduced to generate random errors, which are imposed by the deterministic component. The elliptical copulas (e.g. Gaussian and t-copula) generate the random errors based on the multivariate distribution, typically of decomposition of the error correlation matrix using the LU decomposition algorithm. The Archimedean copulas (e.g. Clayton and Gumbel) utilize the conditional dependence between different radar pixels to obtain random errors. Based on those, a case application is carried out in the Brue catchment located in southwest England. The results show that the simulated uncertainty bands of rainfall encompass most of the reference raingauge measurements with good agreement between the simulated and observed spatial dependences. This indicates that the proposed scheme is a statistically reliable method in ensemble radar rainfall generation and is a useful tool for describing radar rainfall uncertainty.Editor D. Koutsoyiannis; Associate editor S. Grimaldi [ABSTRACT FROM AUTHOR]

The generation of reliable quantitative precipitation estimations (QPEs) through use of raingauge and radar data is an important issue. This study investigates the impacts of radar QPEs with different densities of raingauge networks on rainfall–runoff processes through a semi-distributed parallel-type linear reservoir rainfall–runoff model. The spatial variation structures of the radar QPE, raingauge QPE and radar-gauge residuals are examined to review the current raingauge network, and a compact raingauge network is identified via the kriging method. An analysis of the large-scale spatial characteristics for use with a hydrological model is applied to investigate the impacts of a raingauge network coupled with radar QPEs on the modelled rainfall–runoff processes. Since the precision in locating the storm centre generally represents how well the large-scale variability is reproduced; the results show not only the contribution of kriging to identify a compact network coupled with radar QPE, but also that spatial characteristics of rainfalls do affect the hydrographs.Editor Z.W. Kundzewicz; Guest editor R.J. MooreCitation Pan, T.-Y., Li, M.-Y., Lin, Y.-J., Chang, T.-J., Lai, J.-S., and Tan, Y.-C., 2014. Sensitivity analysis of the hydrological response of the Gaping River basin to radar-raingauge quantitative precipitation estimates. Hydrological Sciences Journal, 59 (7), 1335–1352. http://dx.doi.org/10.1080/02626667.2014.923969 [ABSTRACT FROM AUTHOR]

The societal impacts of flash floods are more significant than any other weather-related hazard. They are often manifested in the form of damage to infrastructure, flooding of roadways and bridges, creating deadly hazards to motorists and inundation of crops and pasture. Some of these hazards can be anticipated and thus mitigated given effective warning systems. This study describes the tools proposed over recent decades in the USA to predict flash flooding and evaluates them using a common observational data set. Design recommendations for flash-flood forecasting systems are provided, taking into account today's availability of high-resolution rainfall data at scales commensurate with flash flooding, their archives, spatial data sets to describe physiographic properties, and ever-increasing computational resources.Editor D. Koutsoyiannis; Guest editor R.J. MooreCitation Gourley, J.J., Flamig, Z.L., Hong, Y., and Howard, K.W., 2014. Evaluation of past, present and future tools for radar-based flash-flood prediction in the USA. Hydrological Sciences Journal, 59 (7), 1377–1389. http://dx.doi.org/10.1080/02626667.2014.919391 [ABSTRACT FROM AUTHOR]

Automatic raingauge data often serve as an important input to hydrological and weather warning operations. They are not only fundamental in quantitative rainfall analysis, but also act as the ground truth in warning operation and forecast validation. Quality control is required before the data can be used quantitatively due to systematic and random errors. Extremely large random errors and unreasonably small or false zero values can hamper effective monitoring of heavy rain. Yet both are difficult to detect in real-time by objective means. In an attempt to address these problems, a rainfall data quality-control scheme based on radar-raingauge co-kriging analysis was developed. The important threshold values required in the data quality control of 60-min raingauge rainfall were determined from a detailed analysis of the distributions of rainfall residuals defined as the arithmetic difference and the logarithm of the ratio between a raingauge measurement and its co-kriging estimate. The scheme has been developed and is in real-time use in Hong Kong, a coastal city of about 1100 km2area with more than 150 raingauges installed. Geographically, it is located in the subtropics and dominated by heavy convective rainfall in the summer. As a basis of the quality-control scheme, the co-kriging rainfall analysis was shown through a verification exercise to be superior to those obtained by the Barnes analysis and ordinary kriging of raingauge data. The performance of the quality-control algorithm was assessed using selected cases and controlled tests, and was found to be satisfactory, with a high error detection rate for the two targeted types of error. Limitations and operational issues identified during a real-time trial of the quality-control scheme are also discussed.Citation Yeung, H.Y., Man, C., Chan, S.T., and Seed, A., 2014. Development of an operational rainfall data quality-control scheme based on radar-raingauge co-kriging analysis. Hydrological Sciences Journal, 59 (7), 1285–1299. http://dx.doi.org/10.1080/02626667.2013.839873 [ABSTRACT FROM AUTHOR]

Quality is key to ensuring that the potential offered by weather radar networks is realized. To achieve optimum quality, a comprehensive radar data quality management system, designed to monitor the end-to-end radar data processing chain and evaluate product quality, is being developed at the UK Met Office. Three contrasting elements of this system are described: monitoring of key radar hardware performance indicators; generation of long-term integrations of radar products; and monitoring of radar reflectivity factor using synthesized observations from numerical weather prediction model fields. Examples of each component are presented and ways in which the different types of monitoring information have been used to both identify issues with the radar product data quality and help formulate solutions are given.Editor Z.W. Kundzewicz; Guest editor R.J. MooreCitation Harrison, D., Georgiou, S., Gaussiat, N., and Curtis, A., 2013. Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system. Hydrological Sciences Journal, 59 (7), 1327–1342. http://dx.doi.org/10.1080/02626667.2013.841316 [ABSTRACT FROM AUTHOR]

A methodology is proposed to compare radar reflectivity data obtained from two partially overlapping ground-based radars in order to explain relative differences in radar-rainfall products and establish sound merging procedures for multi-radar observing networks. To identify radar calibration differences, radar reflectivity is compared for well-matched radar sampling volumes viewing common meteorological targets. Temporal separation and three-dimensional matching of two different sampling volumes were considered based on the original polar coordinates of radar observation. Since the proposed method assumes radar beam propagation under standard atmospheric conditions, anomalous propagation cases were eliminated from the analysis. The reflectivity comparison results show systematic differences over time, but the variability of these differences is surprisingly large due to the sensitive nature of the radar reflectivity measurement.Editor D. Koutsoyiannis/Z.W. Kundzewicz; Guest editor R.J. MooreCitation Seo, B.-C., Krajewski, W.F., and Smith, J.A., 2013. Four-dimensional reflectivity data comparison between two ground-based radars: methodology and statistical analysis. Hydrological Sciences Journal, 59 (7), 1312–1326. http://dx.doi.org/10.1080/02626667.2013.839872 [ABSTRACT FROM AUTHOR]

Dans le cadre des multifractals universels, il est possible de caracteriser la variabilite spatio-temporelle de la pluie sur une grande gamme d'echelle a l'aide de trois parametres invariants d'echelles. Dans cette etude, nous avons estime ces parametres multifractals sur des simulations numeriques effectuees avec le modele meso-echelle Meso-NH, developpe par Meteo-France et le Laboratoire d'Aerologie (Univ. P. Sabatier, Toulouse, France), et des images radar composites, couvrant le meme evenement pluvieux, a savoir un orage particulierement violent, dit de type Cevenol, ayant eu lieu sur la partie sud de la France du 5 au 9 Septembre 2005. La comparaison des resultats montre que les deux types de donnees presentent des domaines d'invariance d'echelle relativement similaires, et dont les proprietes sont en accord avec les modeles de precipitation spatio-temporels unifies et scalants les plus simples. Neanmoins l'evaluation de leurs exposants conduit a des valeurs parfois fortement differentes. Citation Gires, A., Tchiguirinskaia, I., Schertzer, D. & Lovejoy, S. (2011) Analyses multifractales et spatio-temporelles des precipitations du modele Meso-NH et des donnees radar. Hydrol. Sci. J. 56(3), 380-396. [ABSTRACT FROM AUTHOR]

The South African Weather Service (SAWS) issues routine experimental, near real-time rainfall maps from daily raingauge networks, radar networks and satellite images, as well as merged rainfall fields. These products are potentially useful for near real-time forecasting, especially in areas of fast hydrological response, and also to simulate the “now state” of various hydrological state variables such as soil moisture content, streamflow, and reservoir inflows. The purpose of this paper is to evaluate their skill as inputs to hydrological simulations and, in particular, the skill of the merged field in terms of better hydrological results relative to the individual products. Rainfall fields derived from raingauge, radar, satellite, conditioned satellite and the merged (gauge/radar/satellite) were evaluated for two selected days with relatively high amounts of rainfall, as well as for a continuous period of 90 days in the Mgeni catchment, South Africa. Streamflows simulated with the ACRU model indicate that the use of raingauge as well as merged fields of satellite/raingauge and satellite/radars/raingauge provides relatively realistic rainfall results, without much difference in their hydrological outputs, whereas the radar and raw satellite information by themselves cannot be used in operational hydrological application in their current status. Citation Ghile, Y., Schulze, R. & Brown, C. (2010) Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective. Hydrol. Sci. J. 55(4), 497-511. [ABSTRACT FROM AUTHOR]

Satellite radar altimetry is complementary to in situ limnimetric surveys as a means of estimating the water height of large rivers, lakes and flood plains. Production of water height time series by satellite radar altimetry technology requires first the selection of radar ground target locations corresponding to water body surfaces under study, i.e. the definition of 'virtual limnimetric stations'. We propose to investigate qualitative and quantitative differences between three representative virtual station creation methodologies: (a) a fully manual method, (b) a semi-automatic method based on a land cover characterization that allows the water body surface under study to be located; and (c) an original fully automatic procedure that exploits a digital elevation model and an estimation of the river width. The results yielded by these three methods are comparable: maximum absolute magnitudes of water height differences being 0.46, 0.26 and 0.15 m for, respectively, 95, 90 and 80% of the water height values obtained. Moreover, more than 67% and 92% of time series jointly produced by the methods present root mean square differences lower than 20 and 50 cm, respectively. The results show that the fully automatic method developed herein provides as reliable results as the fully manual one. This opens the way to use of satellite radar altimetry for the generation of water height time series on a large scale, and considerably extends the applicability of satellite radar altimetry in hydrology. Citation Roux, E., Santos da Silva, J., Vieira Getirana, A. C., Bonnet, M.-P., Calmant, S., Martinez, J.-M. & Seyler, F. (2010) Producing time series of river water height by means of satellite radar altimetry-comparative study. Hydrol. Sci. J. 55(1), 104-120. [ABSTRACT FROM AUTHOR]