We present the design of a Digital Twin for the natural resources of the Loire Valley, one of the most emblematic natural environments in central Europe. A conceptual approach to the data architecture and component integration is shown by describing represented resources, data sources, use cases and functionalities. Such a holistic approach enables easier study, management, understanding and prediction of natural resources and their relationship with human activity.
1. Introduction
Methodology cases. nEvelop-O The introduced DT is supported by an existing sensory base. Figure 1 shows its constituent parts with a focus on targeted resources, data sources, functional objects and built models, and a set of aimed use
To satisfy interoperability and standardization, the DT architectural design is consistent with the Environmental Research Infrastructures Reference Model (ENVRI RM) [12]. From an operational perspective, the DT has two parts: (a) DT Front End with three layers: visualization (main dashboards and representative services), applications (collection of workflows and use-case applications), and data
ceur-ws.org functional objects
models - water-level models - water-level maps - water-level hist. and KB - pollutants/soil prop. KB - pollutant trans. models - AQ and poll. models - AQ and poll. maps - AQ and poll. hist. and KB - GHG emissions models - GHG emissions maps - GHG emissions hist. and KB use cases - prediction and simulation of global warming effects - prediction of landslides and avanche hazards - viability of farming - prediction of droughts - prediction of floods - viability of forest extension - understanding pollutant migration - pollutant migration models and simulations - test of pollutant removal techniques - evaluation of ecological products - impact of NH3 on atmosphere - correlation of NH3 measures and emissions - health damage by PM10 and ozone - understanding nitrous oxide emissions - hypothesis for reducing GHG - evaluation of strategies for GHG reduction - modeling reactive nitrogen losses data sources
Lig'Air ERA5
FR
water-levels of the Beauce Aquifer transfer of water and contaminants through regional soil regional air quality, climate and meteorology regional GHG emissions and soil properties 3. Conclusions Acknowledgments Centre-Val de Loire (France)
* KB: Knowldge Base, hist.: historical, poll.: pollutants, prop.: properties, trans.: transportation, AQ: Air Quality, GHG: GreenHouse Gases (N2O, CO2, CH4) data and main services), limbs (access to raw data and non-essential services) and back (system updates). A proof of concept that emulates some parts of DT, data exchange protocols and communication processes is accessible through a doi-citable repository [13]. It shows analysis and visualization of multivariate time series of 255 measurement points in France by combining data from three diferent external sources (ERA5, ADES, Folium).
[1] D. Jones, C. Snider, A. Nassehi, J. Yon, B. Hicks, Characterising the digital twin: A systematic literature review, CIRP Journal of Manufacturing Science and Technology 29 (2020) 36–52. doi:10.