A Visual-Scenario-Based Environmental Analysis Approach to the Model-Based Management of Water Extremes in Urban Regions

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

Due to the present climate crisis, the increasing frequency of the water extreme events around urban regions in river basins may result in drastic losses. One of the most effective preventive measures is a prior analysis of the eventual effects to comprehend the future risks of such water extremes. As well as analysis of historical impacts, the model-based management of water extremes have also a crucial role. Therefore, we present a 3-dimensional visual-scenario-based environmental analysis framework by utilising a Virtual Geographic Environment for the visualisation and the exploration of model-based management of hydrological events in urban regions. Within the study, we focused on the City of Dresden in eastern Germany located in the basin of the Elbe River. We integrated a large set of historical observation data and the results of numerical simulations to explore the consequences of modelled heavy precipitation events within different scenarios. Utilising a framework developed in Unity, the resulting visualisation of different scenarios dealing with water extremes simulated with coupled numerical models constitute the overall focus of this particular study. The resulting application is intended as a collaboration platform in terms of the knowledge transfer among domain scientists, stakeholders and the interested public.

Details

Original languageEnglish
Title of host publicationEuroVis 2023
PublisherThe Eurographics Association
ISBN (electronic)978-3-03868-223-3
Publication statusPublished - 12 May 2023
Peer-reviewedYes

Conference

TitleEuroVis 2023
Subtitle25th EG Conference on Visualization
Conference number25
Duration12 - 16 June 2023
Website
Degree of recognitionInternational event
LocationLeipzig
CityLeipzig
CountryGermany

External IDs

ORCID /0000-0002-3729-0166/work/142248446
ORCID /0000-0002-8675-2304/work/146644489