Sensitivity analysis of the hydrological response of the Gaping River basin to radar-raingauge quantitative precipitation estimates

Pan, Tsung-Yi; Li, Mengying; Lin, Yong-Jun; Chang, Tsang‐Jung; Lai, Jihn‐Sung; Tan, Yih–Chi

doi:10.1080/02626667.2014.923969

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…It has been demonstrated that radar QPE can be a useful and reliable forcing for flood/streamflow forecasting in poorly gauged or ungauged regions [61,65]. For gauged areas, radar precipitation can be merged with gauged precipitation to generate a more accurate QPE product with a good spatiotemporal coverage and resolution, so as to benefit rainfall-runoff modelling and flood simulation [61,[67][68][69][70][71].…”

Section: Implementation Of Weather Radar Precipitationmentioning

confidence: 99%

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

Grimaldi

Walker

et al. 2016

Remote Sensing

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Abstract:Fluvial flooding is one of the most catastrophic natural disasters threatening people's lives and possessions. Flood forecasting systems, which simulate runoff generation and propagation processes, provide information to support flood warning delivery and emergency response. The forecasting models need to be driven by input data and further constrained by historical and real-time observations using batch calibration and/or data assimilation techniques so as to produce relatively accurate and reliable flow forecasts. Traditionally, flood forecasting models are forced, calibrated and updated using in-situ measurements, e.g., gauged precipitation and discharge. The rapid development of hydrologic remote sensing offers a potential to provide additional/alternative forcing and constraint to facilitate timely and reliable forecasts. This has brought increasing interest to exploring the use of remote sensing data for flood forecasting. This paper reviews the recent advances on integration of remotely sensed precipitation and soil moisture with rainfall-runoff models for rainfall-driven flood forecasting. Scientific and operational challenges on the effective and optimal integration of remote sensing data into forecasting models are discussed.

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Section: Implementation Of Weather Radar Precipitationmentioning

confidence: 99%

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

Grimaldi

Walker

et al. 2016

Remote Sensing

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“…Further research requires further acquisitions of sub-daily discharges with high temporal resolution to en-able more accurate flood warning modeling. Meanwhile, it has also been indicated that the spatial characteristics of rainfall could significantly affect the flooding process and further enhance the model results based on finer spatial resolution of radar precipitation data [49].…”

Section: The 24 H Critical Areal Rainfall Thresholds For Early Flood ...mentioning

confidence: 99%

Impact-Based Critical Areal Rainfall for Early Flood Warning: A Case Study of Zhulong River Watershed in the Upper Reaches of the Xiong’an New Area

Zhao

Chen

et al. 2023

Atmosphere

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In this work, the largest tributary of the South Branch in the upper reaches of the Xiong’an New Area is selected as the study area. The impact-based critical areal rainfall indices for early flood warnings are proposed from the perspective of the impacts of floods on socio-economic factors. Specifically, four steps, including the determination of the damage-causing discharges, the establishment of the rainfall–discharge relationship, the computation of the critical areal rainfall and the validation of the early warning indices, were used to determine the critical areal rainfall for early flood warnings in the watershed. The results showed that the 1-day critical areal rainfall amounts were 31 mm, 63 mm, 92 mm and 160 mm for early flood warning levels 4, 3, 2 and 1, respectively, when the 1-day antecedent areal rainfall was ≤10 mm. The critical areal rainfall amounts were 20 mm, 54 mm, 87 mm and 160 mm for early flood warning levels 4, 3, 2 and 1, respectively, when the 1-day antecedent areal rainfall was >10 mm. The early warning effectiveness of the proposed critical indices was validated with historical catastrophic flood events and precipitation data during recent flood seasons. The results demonstrated that the impact-based critical indices had a high accuracy and could release warnings 1–2 days in advance, which could effectively avoid the occurrence of missed and underestimated warnings.

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“…The first two papers (Harrison et al 2014, Yeung et al 2014 concern radar-rainfall estimation and quality control, while uncertainty aspects of radar-rainfall estimation, including reduction through merging with raingauge data, are covered by Delrieu et al (2014), Seo et al (2014) and Pan et al (2014). Morin and Yakir (2014) and Nikolopoulos et al (2014) exploit radar rainfall to gain a deeper understanding of the impact of spatial rainfall on catchment flood response, including consideration of localized convective rain in semi-arid environments and the interplay of storm velocity and orography on flood magnitude.…”

Section: Weather Radar and Hydrology: Prefacementioning

confidence: 99%

Weather Radar and Hydrology: Preface

Moore

2014

Hydrological Sciences Journal

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Sensitivity analysis of the hydrological response of the Gaping River basin to radar-raingauge quantitative precipitation estimates

Cited by 5 publications

References 32 publications

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

Impact-Based Critical Areal Rainfall for Early Flood Warning: A Case Study of Zhulong River Watershed in the Upper Reaches of the Xiong’an New Area

Weather Radar and Hydrology: Preface

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