Advances in Flood Early Warning: Ensemble Forecast, Information Dissemination and Decision-Support Systems

• Main Authors: Haiyun Shi, Erhu Du, Suning Liu, Kwok-Wing Chau
• Format: Article
• Language: English
• Published: MDPI AG 2020-08-01
• Series: Hydrology
• Subjects: flood early warning; ensemble flood forecast; numerical weather prediction; service-oriented architecture; social media; individual behaviors
• Online Access: https://www.mdpi.com/2306-5338/7/3/56

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.