The Common Modelling Protocol: A hierarchical framework for simulation of agricultural and environmental systems

Abstract A modular approach to simulation modelling offers significant advantages for its application to agricultural and environmental questions, including re-use of model equations in different contexts and with different user-interfaces; configuration of model structures that are most appropriate to a given problem; and facilitation of collaboration between modelling teams. This paper describes the Common Modelling Protocol (CMP), a generic, open and platform-independent framework for modular simulation modelling that is in widespread use. The CMP is distinguished from existing simulation frameworks by taking an explicitly hierarchical view of the biophysical system being simulated and by representing continuous and discontinuous processes equally naturally. Modules of model logic are represented in the CMP by entities known as “components”. Each component may possess “properties” that convey the value of the quantities in its equations and “event handlers” that compute model logic. Low-level information-transfers in the CMP are carried out by means of a message-passing system. Co-ordinated sequences of messages carry out tasks such as initialization, exchange of variable values and the control of computation order. Extensible Markup Language (XML) is used in the protocol for tasks such as denoting data types, submitting simulations for execution and describing components to user-interface software. Examples are presented showing how the CMP can be used to couple modules developed by different teams and to configure a complex model structure. The choices and trade-offs encountered when building a framework for modular simulation are analyzed, using the CMP and other simulation frameworks as examples. The kinds of scientific issues that arise when the CMP is used to realize collaboration between modelling groups are discussed.

[1]  Anthony M. Whitbread,et al.  Simulation modelling of lablab (Lablab purpureus) pastures in northern Australia , 2006 .

[2]  R. L. McCown,et al.  Changing systems for supporting farmers' decisions: problems, paradigms, and prospects , 2002 .

[3]  Basil Acock,et al.  Modularity and genericness in plant and ecosystem models , 1997 .

[4]  Frits K. van Evert,et al.  The ModCom modular simulation system , 2003 .

[5]  C. M. Sperberg-McQueen,et al.  Extensible Markup Language (XML) , 1997, World Wide Web J..

[6]  Graeme L. Hammer,et al.  Assessing climatic risk to sorghum production in water-limited subtropical environments. I.Development and testing of a simulation model , 1994 .

[7]  M. J Shaffer,et al.  Rule-based management for simulation in agricultural decision support systems , 1998 .

[8]  Senthold Asseng,et al.  An overview of APSIM, a model designed for farming systems simulation , 2003 .

[9]  Andrew D. Moore,et al.  GRAZPLAN: Decision support systems for Australian grazing enterprises. III. Pasture growth and soil moisture submodels, and the GrassGro DSS , 1997 .

[10]  M. Frissel,et al.  Simulation of nitrogen behaviour in soils , 1973 .

[11]  L. Ahuja,et al.  Agricultural System Models in Field Research and Technology Transfer , 2002 .

[12]  Ivar Jacobson,et al.  The Unified Modeling Language User Guide , 1998, J. Database Manag..

[13]  L. A. Richards Capillary conduction of liquids through porous mediums , 1931 .

[14]  R. Dalal,et al.  APSIM's water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems , 1998 .

[15]  D. Mladenoff,et al.  A spatially interactive simulation of climate change, harvesting, wind, and tree species migration and projected changes to forest composition and biomass in northern Wisconsin, USA , 2005 .

[16]  George H. Leavesley,et al.  A modular approach to addressing model design, scale, and parameter estimation issues in distributed hydrological modelling , 2002 .

[17]  R. O'Neill A Hierarchical Concept of Ecosystems. , 1986 .

[18]  J. Donnelly,et al.  GRAZPLAN: Decision support systems for Australian grazing enterprises—II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS , 1997 .

[19]  Holger Meinke,et al.  Potential soil water extraction by sunflower on a range of soils , 1993 .

[20]  Petraq J. Papajorgji,et al.  An architecture for developing service-oriented and component-based environmental models , 2004 .

[21]  N. Huth,et al.  Simulation of growth and development of diverse legume species in APSIM , 2002 .

[22]  R. Simpson,et al.  Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia , 2002 .

[23]  Neil I. Huth,et al.  A framework for simulating agroforestry options for the low rainfall areas of Australia using APSIM , 2002 .