Can we scale Digital Twins of Nature-based Solutions for stormwater and transboundary water security projects?

Abstract

Nature-based Solutions (NbS) are presented as an alternative and decentralized solutions with different application scales for problems addressed to urban expansion as water quality reduction and floods. The usage of control strategies and mathematical modeling techniques has shown promising results for optimizing hydraulic and water treatment processes. The Digital Twins (DT) as process integration technology are widely used in industry, and recently these technique usages in urban water systems are showing effective results in both management and planning. However, there is a lack of proper literature definition for DT applied to NbS, especially for stormwater and transboundary water security projects. Thus, this paper sought through a literature review to access the existing conceptual challenges and the DT definition as a framework, identify how the mathematical modeling reported in the literature can improve the DT development, and evaluate the potential benefits associated with the application of DT in NbS.

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review

“…To simulate and model the physical system to succeed in implementing the DTs, the use of mathematical models is mandatory [ 17 ]. Once the observed physical phenomena of interest are captured, foundational mathematical equations are formulated to depict and characterize the dynamics of these phenomena accurately.…”

“…Furthermore, DTs address optimization solutions regarding water flow and treatment processes related to water quality reduction following floods and stormwater within transboundary water security projects due to urban expansion [ 17 ]. DT models are employed to monitor the quality of urban water by integrating physical entities and utilizing sensors in urban drainage systems.…”

“…Furthermore, the interconnections among these entities play a vital role as they are essential for the functioning of the DT system in an integrated manner, as emphasized by Pedersen et al in their research [ 17 ].…”

“…A DT could be addressed as a tight combination of (i) an object model, in conjunction with (ii) an expansive set of data that is directly following the object that may evolve, and finally, (iii) a method for modifying and refining the model based on the available data [ 17 , 62 ]. The experts decide the need and selection of the training, validation and verification data concerning specific case studies, types of soil, plant types, leaf area, plant height, regarding the Physical Twin, or technological use cases.…”

Digital Twins in Agriculture: Orchestration and Applications

“…This iterative process of "continuous monitoring−model update−prediction−validation" allows deep learning, as predictions become more and more accurate. Pedersen et al highlighted the relevance of interconnections among these steps for the proper functionality of the DT 16.…”