Feedback loops and temporal misalignment in component‐based hydrologic modeling

Abstract

[1] In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that componentbased modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

Advancing the Open Modeling Interface (OpenMI) for integrated water resources modeling

“…For example, Elag et al (2011) assessed the mass-balance errors of a hypothetical coupling scenario involving the coupling of simplified solute transport models including a surface and a sediment media model that were temporally misaligned. Bulatewicz et al (2010) successfully coupled agricultural, groundwater, and economic models to evaluate the impacts of alternative water use policies for a major aquifer in the US.…”

Models as web services using the Open Geospatial Consortium (OGC) Web Processing Service (WPS) standard

“…This enables components to transfer values back and forth to resolve dynamic system interactions (Elag et al, 2011). During this phase, a method named PerformTimeStep (defined in the OpenMI Standard Development Kit, SDK) is called on every time-step of the simulation (Fig.…”

An ontology for component‐based models of water resource systems

“…While there are obvious benefits to using a component‐based approach for water resources modeling, there are also challenges that must be overcome in order to encourage broad adoption of the approach. One important challenge associated with the component‐based modeling approach is that model integration is not simply the proper assemblage of components from a technical standpoint, rather it also requires scientific knowledge of the underlying coupling between each component [ Athanasiadis et al ., ; Voinov and Shugart , ; Elag et al ., ; Castronova et al ., ]. Coupled model components often exchange values based on a message‐passing scheme where one component requests a particular variable from a second component.…”

“…Scientists wanting to couple components across disciplinary boundaries or modeling frameworks face challenges that extend beyond simply ensuring variable units are consistent across coupled models. They must also consider (i) semantic heterogeneity across disciplines due to the variety of terminology used to describe the equations, variables, parameters, and units within models, (ii) diversity of concepts used to define component's functionality and relationships, which results in overwhelming complexity for linked model compositions, (iii) syntactic heterogeneity in metadata structure used to describe a component across modeling frameworks, which hinders a component's reusability, and (iv) coupling inconsistency resulting from mismatched spatial or temporal data exchanges, or from incompatible semantics used by different models [ Argent , ; Voinov and Shugart , ; Peckham et al ., ; Rizzoli et al ., ; Elag et al ., ; Janssen et al ., ; Argent et al ., ]. These issues collectively result in a lack of shared understanding and poor communication within and between users of the component‐based modeling framework.…”