气候变化领域集成服务门户(CCPortal): On water level forecasting using artificial neural networks: the case of the Río de la Plata Estuary, Argentina

CCPortal

DOI	10.1007/s11069-024-06585-2
	On water level forecasting using artificial neural networks: the case of the Río de la Plata Estuary, Argentina
	Dato, Jonathan Fabian; Dinapoli, Matias Gabriel; D'Onofrio, Enrique Eduardo; Simionato, Claudia Gloria
发表日期	2024
ISSN	0921-030X
EISSN	1573-0840
英文摘要	The Rio de la Plata Estuary (RdP) is frequently affected by large storm surges that have historically caused social and economic losses. According to recent research, the number and strength of surge events have been increasing over time as a result of climate change. Although process-based models have been widely used for the storm surge prediction, their high computational demand may be a significant disadvantage in some applications, such as rapid or neartime forecasting. Artificial neural network (ANN) becomes an alternative tool to forecast the water level, taking into account meteorological and astronomical forcing as numerical models also do. In this work, an ANN model performance was evaluated to hindcast and forecast water levels in the RdP. Several combinations of lead times and inputs were assessed in order to find the best configuration. The resulting model provides 4-day forecasts for Buenos Aires and Torre Oyarvide stations (located at the upper and intermediate estuary, respectively), using observed water levels, meteorological inputs and predicted astronomical tides. Results also support the ANN model's ability to simulate even extreme events. For instance, for a 12 h-forecast, the RMSE is about 20 cm. Finally, we conclude that the model developed here can effectively complement the empirical and numerical forecasts executed by Naval Hydrographic Service, reducing computational costs and leveraging available datasets.
英文关键词	Storm surge; Forecasting; Artificial neural networks; Rio de la Plata
语种	英语
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences ; Water Resources
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS记录号	WOS:001200378800001
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/297420
作者单位	University of Buenos Aires; University of Buenos Aires; University of Buenos Aires; University of Buenos Aires; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
推荐引用方式 GB/T 7714	Dato, Jonathan Fabian,Dinapoli, Matias Gabriel,D'Onofrio, Enrique Eduardo,et al. On water level forecasting using artificial neural networks: the case of the Río de la Plata Estuary, Argentina[J],2024.
APA	Dato, Jonathan Fabian,Dinapoli, Matias Gabriel,D'Onofrio, Enrique Eduardo,&Simionato, Claudia Gloria.(2024).On water level forecasting using artificial neural networks: the case of the Río de la Plata Estuary, Argentina.NATURAL HAZARDS.
MLA	Dato, Jonathan Fabian,et al."On water level forecasting using artificial neural networks: the case of the Río de la Plata Estuary, Argentina".NATURAL HAZARDS (2024).