Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin)

Hans Jørgen Henriksen
* ORCID logo ,
Raphael Schneider
ORCID logo ,
Julian Koch
ORCID logo ,
Maria Ondracek
,
Lars Troldborg
ORCID logo ,
Ida K. Seidenfaden
,
Søren Julsgaard Kragh
,
Eva Bøgh
,
Simon Stisen
ORCID logo
Version 1 : Received: 21 November 2022 / Approved: 23 November 2022 / Online: 23 November 2022 (02:36:58 CET)
Version 2 : Received: 23 November 2022 / Approved: 24 November 2022 / Online: 24 November 2022 (02:47:00 CET)

A peer-reviewed article of this Preprint also exists.

Henriksen, H.J.; Schneider, R.; Koch, J.; Ondracek, M.; Troldborg, L.; Seidenfaden, I.K.; Kragh, S.J.; Bøgh, E.; Stisen, S. A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin). Water 2023, 15, 25. Henriksen, H.J.; Schneider, R.; Koch, J.; Ondracek, M.; Troldborg, L.; Seidenfaden, I.K.; Kragh, S.J.; Bøgh, E.; Stisen, S. A New Digital Twin for Climate Change Adaptation, Water Management, and Disaster Risk Reduction (HIP Digital Twin). Water 2023, 15, 25.

Abstract

The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback to a national real-time risk knowledge base during extreme events (flooding and drought) is also discussed. Under climate change conditions, Denmark is likely to experience more rain in winter, more evapotranspiration in summer, intensified cloudbursts, drought, and sea level rise. These challenges have been addressed as part of the Joint Governmental Digitalization Strategy 2016-2020 for better use and sharing of public data about the terrain, water, and climate to support climate adaptation, water management, and disaster risk reduction. This initiative included the development of a new web-based data portal (HIP portal) developed by the Danish Agency for Data Supply and Infrastructure (SDFI). GEUS delivered 5 terra-byte of hydrological model data to the portal with robust calibration methods and hybrid Machine Learning (ML) being key parts of the deliverables. The paper discusses the challenges and potentials of further developing the HIP Digital Twin with ‘plug-in Digital Twins’ for local river basins including feedback to the national level.

Keywords

Digital Twin; hazard; vulnerability; resilience; adaptive climate adaptation; groundwater; DK-model HIP

Subject

Environmental and Earth Sciences, Environmental Science

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Comments (1)

Comment 1
Received: 24 November 2022
Commenter: Hans Henriksen
Commenter's Conflict of Interests: Author
Comment: Dear Editor
New version updated with a few minor 'errata' corrections (text ref. to references), + updated figure 2 + updated reference (now published in HESS ref. /8/ Scheider et al. 2022).
Minor changes:
- Figure 2 Box 'ML-GB downscaling 100m > 10m'  GEUS corrected to 'ML-RF downscaling 500m > 100m'
- line 246: /8/ corrected to /7/
- line 256: /9/ corrected to /8/
- line 259: /9/ corrected to /8/
- line 404: ´..´corrected to ´.´
- line 408: _ inserted in front of 'urbanisation'
- line 642: /8/ corrected to /7/
ref. list: /8/ updated (changed from preprint to final publication today 23/11 2022 in HESS with 'doi'

best regards
Hans Jørgen Henriksen
GEUS


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