气候变化领域集成服务门户(CCPortal): Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model

CCPortal

DOI	10.1007/s11069-021-04582-3
	Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model
	Hussain F.; Wu R.-S.; Wang J.-X.
发表日期	2021
ISSN	0921030X
起始页码	249
结束页码	284
卷号	107 期号:1
英文摘要	Reliable hourly flood forecasting using weather radar rainfall data for early warning system is essential for reducing natural disaster risk during extreme typhoon events. This study proposed a novel approach integrated with physics-based WASH123D and HEC-HMS models to forecast 1 h ahead flood level in the Fengshan Creek basin, northern Taiwan. The comparison was done with data-driven support vector machine (SVM) model, and performances were assessed by using statistical indicators (root mean square error, correlation coefficient, the error of time to peak flood level, the error of peak flood). Four typhoons and two plum rain events (with 620 data sets) were selected for the process of model calibration and validation. The model performs better when it used quantitative precipitation estimate radar data rather than rain gauge data. Results of using 1 h ahead quantitative precipitation forecast (QPF) as input for flood forecasting were encouraging but not feasible to use directly for early flood warning system due to errors in peak flood levels and timing. Therefore, the improvement in accuracy of 1 h ahead flood forecasting was done using physics-based approach and SVM model. The systematic comparison revealed that the SVM model is an attractive way out to improve the accuracy of QPF forecasted flood levels but unable to fully describe the flood level patterns in terms of timings and flood peaks, while the results obtained by the physics-based approach were accurate and much better than the SVM model. The approach fully described the physics of hydrograph patterns and outputs have exactly the same 1 h ahead predictions, in excellent agreement with observations. The reliable and accurate reflections of timing and amount of flood peaks in all selected typhoons by a newly developed physics-based approach with its operational nature are recommended to use by the government in the future for early warning to reduce the flood impacts during typhoon events. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
关键词	Early warning Flood forecasting HEC-HMS Radar rainfall SVM model WASH123D
英文关键词	comparative study; early warning system; flood forecasting; hydrological modeling; numerical model; prediction; rainfall; support vector machine; water level; Taiwan
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206286
作者单位	Department of Civil Engineering, National Central University, Taoyuan City, Taiwan; Department of Agricultural Engineering, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan
推荐引用方式 GB/T 7714	Hussain F.,Wu R.-S.,Wang J.-X.. Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model[J],2021,107(1).
APA	Hussain F.,Wu R.-S.,&Wang J.-X..(2021).Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model.Natural Hazards,107(1).
MLA	Hussain F.,et al."Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model".Natural Hazards 107.1(2021).