Advances in flood early warning: Ensemble forecast, information dissemination and decision-support systems

Shi，Haiyun1,2; Du，Erhu1,2; Liu，Suning1,2; Chau，Kwok Wing3

2020-09-01

Ensemble flood forecast Evacuation decisions Flood early warning Individual behaviors Numerical weather prediction Service-oriented architecture Social media

英语

Floods are usually highly destructive, which may cause enormous losses to lives and property. It is, therefore, important and necessary to develop effective flood early warning systems and disseminate the information to the public through various information sources, to prevent or at least mitigate the flood damages. For flood early warning, novel methods can be developed by taking advantage of the state-of-the-art techniques (e.g., ensemble forecast, numerical weather prediction, and service-oriented architecture) and data sources (e.g., social media), and such developments can offer new insights for modeling flood disasters, including facilitating more accurate forecasts, more efficient communication, and more timely evacuation. The present Special Issue aims to collect the latest methodological developments and applications in the field of flood early warning. More specifically, we collected a number of contributions dealing with: (1) an urban flash flood alert tool for megacities; (2) a copula-based bivariate flood risk assessment; and (3) an analytic hierarchy process approach to flash flood impact assessment.

10.3390/HYDROLOGY7030056

Hydrology

7

3

第一 ; 通讯

2-s2.0-85090034695

Scopus

2306-5338

1.State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.Department of Civil and Environmental Engineering,The Hong Kong Polytechnic University,Hunghom, Kowloon,Hong Kong

Shi，Haiyun,Du，Erhu,Liu，Suning,et al. Advances in flood early warning: Ensemble forecast, information dissemination and decision-support systems. 2020-09-01.