Articles | Volume 20, issue 12
https://doi.org/10.5194/hess-20-4731-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-4731-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Using rainfall thresholds and ensemble precipitation forecasts to issue and improve urban inundation alerts
Taiwan Typhoon and Flood Research Institute (TTFRI), National Applied
Research Laboratories (NARLabs), Taipei, 10093, Taiwan
Gong-Do Hwang
Taiwan Typhoon and Flood Research Institute (TTFRI), National Applied
Research Laboratories (NARLabs), Taipei, 10093, Taiwan
Department of Atmospheric Science, National Taiwan University, Taipei,
10617, Taiwan
Chin-Cheng Tsai
Taiwan Typhoon and Flood Research Institute (TTFRI), National Applied
Research Laboratories (NARLabs), Taipei, 10093, Taiwan
Jui-Yi Ho
Taiwan Typhoon and Flood Research Institute (TTFRI), National Applied
Research Laboratories (NARLabs), Taipei, 10093, Taiwan
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Cited
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- Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons S. Yang et al. 10.3390/su12104258
- Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns Z. Wang & Q. Li 10.3390/rs16050755
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. 10.1016/j.uclim.2023.101573
- A decision-making model for flood warning system based on ensemble forecasts L. Goodarzi et al. 10.1016/j.jhydrol.2019.03.040
- A rainfall threshold‐based approach to early warnings in urban data‐scarce regions: A case study of pluvial flooding in Alexandria, Egypt A. Young et al. 10.1111/jfr3.12702
- Heavy precipitation forecasts over Switzerland – An evaluation of bias-corrected ECMWF predictions S. Schauwecker et al. 10.1016/j.wace.2021.100372
- Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China Q. Ke et al. 10.1016/j.advwatres.2020.103719
- Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds F. Marra et al. 10.5194/hess-21-4525-2017
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- A review of advances in China’s flash flood early-warning system C. Liu et al. 10.1007/s11069-018-3173-7
- Dependence of Probabilistic Quantitative Precipitation Forecast Performance on Typhoon Characteristics and Forecast Track Error in Taiwan H. Teng et al. 10.1175/WAF-D-19-0175.1
- Global changes in the spatial extents of precipitation extremes X. Tan et al. 10.1088/1748-9326/abf462
29 citations as recorded by crossref.
- An Overview of Flood Concepts, Challenges, and Future Directions A. Mishra et al. 10.1061/(ASCE)HE.1943-5584.0002164
- Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique M. Wu et al. 10.3390/w9110836
- Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons S. Yang et al. 10.3390/su12104258
- Towards Improved Satellite Data Utilization in China: Insights from an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns Z. Wang & Q. Li 10.3390/rs16050755
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. 10.1016/j.uclim.2023.101573
- A decision-making model for flood warning system based on ensemble forecasts L. Goodarzi et al. 10.1016/j.jhydrol.2019.03.040
- A rainfall threshold‐based approach to early warnings in urban data‐scarce regions: A case study of pluvial flooding in Alexandria, Egypt A. Young et al. 10.1111/jfr3.12702
- Heavy precipitation forecasts over Switzerland – An evaluation of bias-corrected ECMWF predictions S. Schauwecker et al. 10.1016/j.wace.2021.100372
- Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China Q. Ke et al. 10.1016/j.advwatres.2020.103719
- Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds F. Marra et al. 10.5194/hess-21-4525-2017
- Bayesian network model for flood forecasting based on atmospheric ensemble forecasts L. Goodarzi et al. 10.5194/nhess-19-2513-2019
- Evaluation of TRMM 3B43 V7 precipitation data in varied Moroccan climatic and topographic zones M. Aqnouy et al. 10.1007/s42990-024-00116-8
- Application of hybrid machine learning model for flood hazard zoning assessments J. Wang et al. 10.1007/s00477-022-02301-3
- Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany O. Seleem et al. 10.1080/19475705.2022.2097131
- Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean F. Marra et al. 10.5194/hess-21-2389-2017
- A Bernoulli-Gamma hierarchical Bayesian model for daily rainfall forecasts C. Lima et al. 10.1016/j.jhydrol.2021.126317
- Regional-scale evaluation of 14 satellite-based precipitation products in characterising extreme events and delineating rainfall thresholds for flood hazards G. Moura Ramos Filho et al. 10.1016/j.atmosres.2022.106259
- Urban hydrological model (UHM) developed for an urban flash flood simulation and analysis of the flood intensity sensitivity to urbanization H. Hu et al. 10.1080/19475705.2024.2302561
- Urban flood forecasting based on the coupling of numerical weather model and stormwater model: A case study of Zhengzhou city H. Wang et al. 10.1016/j.ejrh.2021.100985
- Using Tabu Search Adjusted with Urban Sewer Flood Simulation to Improve Pluvial Flood Warning via Rainfall Thresholds H. Liao et al. 10.3390/w11020348
- Spatial connections in extreme precipitation events obtained from NWP forecasts: A complex network approach A. Singhal et al. 10.1016/j.atmosres.2022.106538
- Spatiotemporal Variations in Agricultural Flooding in Middle and Lower Reaches of Yangtze River from 1970 to 2018 S. Wu et al. 10.3390/su11236613
- A General Overview of the Risk-Reduction Strategies for Floods and Droughts T. Yang & W. Liu 10.3390/su12072687
- Probabilistic flood prediction for urban sub-catchments using sewer models combined with logistic regression models X. Li & P. Willems 10.1080/1573062X.2020.1726409
- Critical rainfall thresholds for urban pluvial flooding inferred from citizen observations X. Tian et al. 10.1016/j.scitotenv.2019.06.355
- A literature review: rainfall thresholds as flash flood monitoring for an early warning system W. Qatrinnada et al. 10.2166/wpt.2024.271
- A review of advances in China’s flash flood early-warning system C. Liu et al. 10.1007/s11069-018-3173-7
- Dependence of Probabilistic Quantitative Precipitation Forecast Performance on Typhoon Characteristics and Forecast Track Error in Taiwan H. Teng et al. 10.1175/WAF-D-19-0175.1
- Global changes in the spatial extents of precipitation extremes X. Tan et al. 10.1088/1748-9326/abf462
Latest update: 14 Dec 2024
Short summary
Taiwan continues to suffer from floods. This study proposes the integration of rainfall thresholds and ensemble precipitation forecasts to provide probabilistic urban inundation forecasts. Utilization of ensemble precipitation forecasts can extend forecast lead times to 72 h, preceding peak flows and allowing response agencies to take necessary preparatory measures. This study also develops a hybrid of real-time observation and rainfall forecasts to improve the first 24 h inundation forecasts.
Taiwan continues to suffer from floods. This study proposes the integration of rainfall...