A machine learning approach for forecasting and visualising flood inundation information

IF 1.1 4区工程技术 Q3 ENGINEERING, CIVIL

Proceedings of the Institution of Civil Engineers-Water Management Pub Date : 2020-05-26 DOI:10.1680/jwama.20.00002

Syed Kabir, S. Patidar, G. Pender

引用次数: 13

Abstract

This paper presents a new data-driven modelling framework for forecasting probabilistic flood inundation maps for real-time applications. The proposed end-to-end (rainfall–inundation) method combin...

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用于预测和可视化洪水淹没信息的机器学习方法

本文提出了一种新的数据驱动模型框架，用于预测概率洪水淹没图的实时应用。提出的端到端(降雨-淹没)方法结合了…

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来源期刊

Proceedings of the Institution of Civil Engineers-Water Management 工程技术-工程：土木

CiteScore

2.10

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Water Management publishes papers on all aspects of water treatment, water supply, river, wetland and catchment management, inland waterways and urban regeneration. Topics covered: applied fluid dynamics and water (including supply, treatment and sewerage) and river engineering; together with the increasingly important fields of wetland and catchment management, groundwater and contaminated land, waterfront development and urban regeneration. The scope also covers hydroinformatics tools, risk and uncertainty methods, as well as environmental, social and economic issues relating to sustainable development.