A framework to resolve spatio-temporal misalignment in component-based modelling

Process-based spatio-temporal component models simulate real world processes, using encapsulated process representations that operate at individual spatial and temporal discretisations. These component models act as building blocks in the construction of multi-disciplinary, multi-scale integrated models. Coupling these independent component models, however, involves aggregation or disaggregation of the exchanged variables at model runtime, since each of the component models exposes potentially different spatial and temporal discretisations. Although conceptual methodologies for spatial and temporal scaling are available, dedicated tools that assist modellers to implement dynamic spatial and temporal scaling operations are rare. We present the accumulator, a programmable general-purpose model building block executing custom scaling operations at model runtime. We therefore characterise runtime information of input and output variables required for the implementation of scaling operations between component models with different discretisations. The accumulator is a component of an integrated modelling framework and can be completed by the modeller with custom operations for spatial and temporal scaling. To illustrate the applicability of the accumulators an integrated model is developed that couples an existing land use change model and hydrological component models at different spatial and temporal scales. The accumulators as building blocks allow modellers to construct multi-scale integrated models in a flexible manner.

Publication year:2014

Keywords:spatio-temporal misalignment, component-based modelling, hydrology, Integrated Modelling, interdisciplinary modelling, land use change, Python

CSS-citation score:1

Accessibility:Open