USE OF RADAR RAINFALL ESTIMATE FOR HYDROLOGICAL APPLICATIONS: PREPROCESSING AND VALIDATION

2004 ◽  
pp. 692-699
Author(s):  
MASSIMILIANO CANNATA ◽  
ANDREA SALVETTI ◽  
MARIA ANTONIA BROVELLI
Keyword(s):  
Radar Rainfall ◽  
Radar Rainfall Estimate ◽  
Hydrological Applications

scholarly journals Radar Rainfall Estimation in Morocco: Quality Control and Gauge Adjustment

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 41 ◽  
Author(s):  
Zahra Sahlaoui ◽  
Soumia Mordane
Keyword(s):  
Positive Impact ◽  
Radar Reflectivity ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
Impact Bias ◽  
African Rainfall ◽  
Precipitation Structure ◽  
Radar Rainfall Estimate ◽  
The Impact

This study focused on investigating the impact of gauge adjustment on the rainfall estimate from a Moroccan C-band weather radar located in Khouribga City. The radar reflectivity underwent a quality check before deployment to retrieve the rainfall amount. The process consisted of clutter identification and the correction of signal attenuation. Thereafter, the radar reflectivity was converted into rainfall depth over a period of 24 h. An assessment of the accuracy of the radar rainfall estimate over the study area showed an overall underestimation when compared to the rain gauges (bias = −6.4 mm and root mean square error [RMSE] = 8.9 mm). The adjustment model was applied, and a validation of the adjusted rainfall versus the rain gauges showed a positive impact (bias = −0.96 mm and RMSE = 6.7 mm). The case study conducted on December 16, 2016 revealed substantial improvements in the precipitation structure and intensity with reference to African Rainfall Climatology version 2 (ARC2) precipitations.

scholarly journals The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1703 ◽  
Author(s):  
Shakti P. C. ◽  
Tsuyoshi Nakatani ◽  
Ryohei Misumi
Keyword(s):  
River Basin ◽  
Spatial Resolution ◽  
Hydrological Modeling ◽  
Distribution Patterns ◽  
Rainfall Data ◽  
Model Parameters ◽  
Radar Rainfall ◽  
Rain Events ◽  
The Impact ◽  
Hydrological Applications

Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.

Error influence of radar rainfall estimate on rainfall-runoff simulation

2015 ◽  
Vol 30 (1) ◽  
pp. 283-292 ◽  
Author(s):  
Taewoong Park ◽  
Taesam Lee ◽  
Sora Ahn ◽  
Dongryul Lee
Keyword(s):  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Radar Rainfall ◽  
Radar Rainfall Estimate

scholarly journals Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

2015 ◽  
Vol 12 (2) ◽  
pp. 1855-1900 ◽  
Author(s):  
L.-P. Wang ◽  
S. Ochoa-Rodríguez ◽  
C. Onof ◽  
P. Willems
Keyword(s):  
Singularity Analysis ◽  
Hydrological Modelling ◽  
Adjustment Process ◽  
Urban Drainage ◽  
Gaussian Field ◽  
Radar Rainfall ◽  
Sensitive Technique ◽  
Hydrological Applications ◽  
Rainfall Estimates ◽  
Sensitive Method

Abstract. Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly-used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently-calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.

scholarly journals Weather radar rainfall data in urban hydrology

2017 ◽  
Vol 21 (3) ◽  
pp. 1359-1380 ◽  
Author(s):  
Søren Thorndahl ◽  
Thomas Einfalt ◽  
Patrick Willems ◽  
Jesper Ellerbæk Nielsen ◽  
Marie-Claire ten Veldhuis ◽  
...  
Keyword(s):  
Urban Areas ◽  
Numerical Models ◽  
Climate Change Impacts ◽  
Weather Radar ◽  
Radar Data ◽  
Rainfall Data ◽  
Urban Hydrology ◽  
Radar Rainfall ◽  
The Past ◽  
Hydrological Applications

Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

scholarly journals Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

2013 ◽  
Vol 17 (6) ◽  
pp. 2195-2208 ◽  
Author(s):  
N. Peleg ◽  
M. Ben-Asher ◽  
E. Morin
Keyword(s):  
Temporal Variability ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
Daily Scale ◽  
Rain Gauge Network ◽  
Hydrological Applications

Abstract. Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.

scholarly journals X-band dual-polarized radar quantitative precipitation estimate analyses in the Midwestern United States

2017 ◽  
Author(s):  
Micheal J. Simpson ◽  
Neil I. Fox
Keyword(s):  
Ground Truth ◽  
Cost Effective ◽  
Radar Data ◽  
Radar Rainfall ◽  
Differential Phase Shift ◽  
Weather Radars ◽  
X Band ◽  
Precipitation Estimation ◽  
Estimate Quality ◽  
Radar Rainfall Estimate

Abstract. Over the past decade, polarized weather radars have been at the forefront of the search for a replacement of estimating precipitation over the spatially, and temporally inferior tipping buckets. However, many radar-coverage gaps exist within the Continental US (CONUS), proposing a dilemma in that radar rainfall estimate quality degrades with range. One possible solution is that of X-band weather radars. However, the literature as to their long-term performance is lacking. Therefore, the overarching objective of the current study was to analyze two year’s worth of radar data from the X-band dualpolarimetric MZZU radar in central Missouri at four separate ranges from the radar, utilizing tippingbuckets as ground-truth precipitation data. The conventional R(Z)-Convective equation, in addition to several other polarized algorithms, consisting of some combinations of reflectivity (Z), differential reflectivity (ZDR), and the specific differential phase shift (KDP) were used to estimate rainfall. Results indicated that the performance of the algorithms containing ZDR were superior in terms of the normalized standard error (NSE), missed and false precipitation amounts, and the overall precipitation errors. Furthermore, the R(Z,ZDR) and R(ZDR,KDP) algorithms were the only ones which reported NSE values below 100 %, whereas R(Z) and R(KDP) equations resulted in false precipitation amounts equal to or greater than 65 % of the total gauge recorded rainfall amounts. The results show promise in the utilization of the smaller, more cost-effective X-band radars in terms of quantitative precipitation estimation at ranges from 30 to 80 km from the radar.

Evaluating the effects of image filtering in short-term radar rainfall forecasting for hydrological applications

2006 ◽  
Vol 13 (03) ◽  
pp. 289 ◽  
Author(s):  
Matthew P. Van Horne ◽  
Enrique R. Vivoni ◽  
Dara Entekhabi ◽  
Ross N. Hoffman ◽  
Christopher Grassotti
Keyword(s):  
Image Filtering ◽  
Rainfall Forecasting ◽  
Short Term ◽  
Radar Rainfall ◽  
Hydrological Applications

scholarly journals Comparison of Rain Gauge Measurements in the Mid-Atlantic Region

2010 ◽  
Vol 11 (2) ◽  
pp. 553-565 ◽  
Author(s):  
Ali Tokay ◽  
Paul G. Bashor ◽  
Victoria L. McDowell
Keyword(s):  
High Performance ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Monthly Rainfall ◽  
The Other ◽  
Reference Network ◽  
Atlantic Region ◽  
Radar Rainfall ◽  
Radar Rainfall Estimate ◽  
Observing Systems

Abstract A comparative study of daily and monthly rainfall between research and operational gauges was conducted at the mid-Atlantic region. Fifty research tipping-bucket gauges were deployed to 20 sites where each site had dual or triple gauges. The gauges were in place to validate the National Aeronautics and Space Administration’s newly developed polarimetric radar rainfall estimate. For logistic purposes, these research gauges were collocated with operational gauges and were operated over a year at each site. Therefore, this is an experimental study, which involves a mixture of one to five sites of seven operational gauge networks. A very good to excellent agreement between the two collocated research gauges at daily time scale raised the authors’ confidence to consider them as a reference before comparing with the operational gauges. Among operational networks, the National Weather Service’s (NWS) Automated Surface Observing Systems (ASOS) weighing bucket and the Climate Reference Network and Forest Services tipping-bucket gauges demonstrated high performance for both daily and monthly rainfall, while the Federal Aviation Administration’s Automated Weather Observing Systems (AWOS) tipping-bucket gauges performed poorly. Among the other networks, the ASOS tipping-bucket and Cooperative observer program’s stick gauges seemed to be reliable for monthly rainfall, but not always for daily rainfall. The Virginia Agricultural Experimental Station (VAES) tipping-bucket gauges, on the other hand, had a mixture of high and low performance for daily and monthly rainfall. Unlike other gauge networks, VAES gauges were in place for long-term research applications.

scholarly journals Weather radar rainfall data in urban hydrology

2016 ◽  
Author(s):  
Søren Thorndahl ◽  
Thomas Einfalt ◽  
Patrick Willems ◽  
Jesper Ellerbæk Nielsen ◽  
Marie-Claire ten Veldhuis ◽  
...  
Keyword(s):  
Numerical Models ◽  
Climate Change Impacts ◽  
Weather Radar ◽  
Radar Data ◽  
Rainfall Data ◽  
Urban Hydrology ◽  
Urban Resilience ◽  
Radar Rainfall ◽  
The Past ◽  
Hydrological Applications

Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology, necessitate an updated review of the state of the art in radar rainfall for urban hydrological applications. Three key areas of research have been identified as especially important in application of radar data in urban hydrology, given their significant advances over the past decade: 1) Temporal and spatial resolution of rainfall data required for different hydrological applications, 2) Rainfall estimation, radar data adjustment and data quality, and 3) Nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper reviews how the focus in urban hydrology as a field of research has shifted over the last decade to fields such as urban resilience to hydrological extremes, climate change impacts, and on-line warning/prediction systems. It is discussed how radar rainfall data can contribute to existing hydrological fields and add value to the aforementioned emerging fields in current and future applications.

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