Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds

Wijayarathne, Dayal; Coulibaly, Paulin; Boodoo, Sudesh; Sills, David

doi:10.3390/w12051494

Cited by 13 publications

(5 citation statements)

References 97 publications

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“…At the scale of urban hydrology applications, the role of measurement biases is particularly important since the high-intensity/short-duration events producing the most relevant urban floods are also the most affected by instrumental sources of error. This is confirmed in the paper by Wijayarathne et al [12], where the performance of all methods used are shown to deteriorate with increasing the severity of rainfall events.…”

supporting

confidence: 63%

“…As a third example of the impact of measurement accuracy on the hydrological applications, Wijayarathne et al [12] contribute a study of radar-gauge merging techniques for use in operational flood forecasting in urban watersheds. Indeed, after adjusting radar estimates with gauge observations by combining their advantages while minimizing their weaknesses, the authors manage to increase their accuracy and reliability.…”

mentioning

confidence: 99%

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Precipitation Measurement Instruments: Calibration, Accuracy and Performance

Lanza

Cauteruccio

2022

Water

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confidence: 63%

mentioning

confidence: 99%

Precipitation Measurement Instruments: Calibration, Accuracy and Performance

Lanza

Cauteruccio

2022

Water

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“…Different methodologies of applying areal precipitation may also affect the final rain distribution per sub-watershed. In a recent study regarding the Humber River basin, various radar-gauge merging techniques were applied to ensure optimum rainfall evaluation [67]. In this research paper, we proposed certain values of parameters regarding two applied hydrological models for precipitation events with different characteristics that decision-makers and policy planners should take into account to adapt to the consequences of future extreme events, especially in the residential areas towards the basin's outlet.…”

Section: Discussionmentioning

confidence: 99%

Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin

2021

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The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis of the hydrometric features of the precipitation events was conducted by comparing the different rainfall time intervals, the total volume of water, and the precedent soil moisture. Parameter model calibration and validation were performed for rainfall events under similar conditions, examined in pairs, in order to verify two hydrological models, the lumped HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System model) and the semi-distributed HBV-light (a recent version of Hydrologiska Byråns Vattenbalansavdelning model), at the exit of six individual gauged sub-basins. Model verification was achieved by using the Nash–Sutcliffe efficiency and volume error index. Different time of concentration (Tc) formulas are better applied to the sub-watersheds with respect to the dominant land uses, classifying the Tc among the most sensitive parameters that influence the time of appearance and the magnitude of the peak modeled flow through the HEC-HMS model. The maximum water content of the soil box (FC) affects most the peak flow via the HBV-light model, whereas the MAXBAS parameter has the greatest effect on the displayed time of peak discharge. The modeling results show that the HBV-light performed better in the events that had less precipitation volume compared to their pairs. The event with the higher total precipitated water produced better results with the HEC-HMS model, whereas the rest of the two high precipitation events performed satisfactorily with both models. April to July is a flood hazard period that will be worsened with the effect of climate change. The suggested calibrated parameters for severe precipitation events can be used for the prediction of future events with similar features. The above results can be used in the water resources management of the basin.

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“…Several studies have presented different techniques for accomplishing this data merging task for rainfall map production [8][9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A GIS-Based Methodology to Combine Rain Gauge and Radar Rainfall Estimates of Precipitation Using the Conditional Merging Technique for High-Resolution Quantitative Precipitation Forecasts in Țibleș and Rodnei Mountains

et al. 2022

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Rain gauges provide accurate rainfall amount data; however, the interpolation of their data is difficult, especially because of the high spatial and temporal variability. On the other hand, a high-resolution type of information is highly required in hydrological modeling for discharge calculations in small catchments. This problem is partially solved by meteorological radars, which provide precipitation data with high spatial and temporal distributions over large areas. The purpose of this study is to validate a conditional merging technique (CMT) for 15 rainfall events that occurred on the southern slope of the Tibleș and Rodnei Mountains (Northern Romania). A Geographic Information System (GIS) methodology, based on three interpolation techniques—simple kriging, ordinary kriging, and cokriging—were utilized to derive continuous precipitation fields based on discrete rain gauge precipitation data and to derive interpolated radar data at rain gauge locations, and spatial analysis tools were developed to extract and analyze the optimal information content from both radar data and measurements. The dataset contains rainfall events that occurred in the period of 2015–2018, having 24 h temporal resolution. The model performance accuracy was carried out by using three validation metrics: mean bias error (MBE), mean absolute error (MAE), and root mean square error (RMSE). The validation stage showed that our model, based on conditional merging technique, performed very well in 11 out of 15 rainfall events (approximate 78%), with an MAE under 0.4 mm and RMSE under 0.7 mm.

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Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds

Cited by 13 publications

References 97 publications

Precipitation Measurement Instruments: Calibration, Accuracy and Performance

Precipitation Measurement Instruments: Calibration, Accuracy and Performance

Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin

A GIS-Based Methodology to Combine Rain Gauge and Radar Rainfall Estimates of Precipitation Using the Conditional Merging Technique for High-Resolution Quantitative Precipitation Forecasts in Țibleș and Rodnei Mountains

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