English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Physically-based overland flow models are computationally demanding,hindering their use for real-time applications. Therefore, the development offast (and reasonably accurate) overland flow models is needed if they are to beused to support flood mitigation decision making. In this study, we investigatethe potential of Self-Organizing Maps to rapidly generate water depth and floodextent results. To conduct the study, we developed a flood-simulation specificSOM, using cellular automata flood model results and a synthetic DEM and inflowhydrograph. The preliminary results showed that water depth and flood extentresults produced by the SOM are reasonably accurate and obtained in a veryshort period of time. Based on this, it seems that SOMs have the potential toprovide critical flood information to support real-time flood mitigationdecisions. The findings presented would however require further investigationsto obtain general conclusions; these further investigations may include theconsideration of real terrain representations, real water supply networks andrealistic inflows from pipe bursts.

Modeling overland flow from local inflows in almost no-time, using Self Organizing Maps