Should and can hybrid models for contaminant transport be developed?

Globally rising numbers of contaminated sites, in millions that are yet to undergo an initial assessment, highlight the limitations of currently available models, as well as signify the need for the development of more practical application models, such as Hybrid models. These hybrid models can be a combination of available models, e.g., combining solutions provided by currently available numerical and analytical models. Effectively this can use the complexity of numerical models and the simplicity of analytical models and yet efficiently provide the required practical solution. However, the hybrid combination may not be limited to available numerical and analytical models, but they could also include Machine Learning (ML)-based surrogate models or much simpler ones based on the Analytic Element Method, which can provide more flexibility with respect to, for example, source and domain complexities. The literature already provides several attempts showcasing the importance of combining different (numerical and analytical) modelling methods, but these efforts have been rather limited and not appropriately defined for example as Hybrid Models. This work attempts to more appropriately define hybrid models and the associated terminologies, and demonstrate with examples that such (hybrid) models can and should be developed.