Flood Forecasting Using Machine Learning Methods

Dear Colleagues,

The degree and scale of flood hazards, nowadays, increases massively with the changing climate, and large-scale floodings jeopardize lives and property, accompanied by great economic losses, in inundation-prone areas of the world. Early flood warning systems with different lead times are promising countermeasures against flood hazards and losses. A collaborative assessment from multiple disciplines, comprising hydrology, remote sensing and meteorology, of the magnitude and impacts of flood hazards on inundation areas beneficially contributes to model integrity and the precision of flood forecasting. Emerging advances in computing technologies, coupled with big-data mining, have boosted data-driven applications, among which Machine Learning (ML) technology bearing flexibility and scalability in pattern extraction has modernized not only scientific thinking but also predictive applications.

In the context of flood hazard mitigation, methodologically-oriented countermeasures may involve forecasting on reservoir inflow, river flow, tropical cyclone track, and flooding at different lead times and/or scales through modern technologies such as, but not limited to, MLs, big-data mining, multiple data aggregation/ensembling, and model ensembling. Analyses of impacts, risks, uncertainty, vulnerability, resilience and scenarios coupled with policy-oriented suggestions will give insight into flood hazard mitigation. A geological information system (GIS) for visual presentation of inundation is also essential and helpful in decision-making.

This Special Issue of Water aims at exploring recent advances on flood management in a timely manner, and interdisciplinary approaches to modelling the complexity of flood hazards-related issues are welcomed. We also encourage contributions in integrative solutions at local, regional or global perspectives.

Prof. Fi-John Chang
Prof. Kuolin Hsu
Prof. Li-Chiu Chang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.