Best Practice in Conceptual Modelling for Environmental Software Development

Conceptual modelling is used in many fields with a varying degree of formality. In environmental applications, conceptual models are used to express relationships, explore and test ideas, check inference and causality, identify knowledge and data gaps, synchronize mental models and build consensus, and to highlight key or dominant processes. Conceptual model representations range from simple box and line interaction diagrams, through interaction representations and causal models, to complicated formal representations of the relationships between actors or entities, or between states and processes. Due to their sometimes apparent simplicity, the development and use of a conceptual model is often an attractive option when tackling an environmental problem where the system is either not well understood, or where the understanding of the system is not shared amongst stakeholders. However, we have experienced many examples where conceptual modelling has failed to live up to the promises of managing complexity and aiding decision making. This paper explores the development and application of conceptual modelling to environmental problems, and identifies a range of best practices for environmental scientists and managers that include considerations of stakeholder participation, model development and representation, integration of different and disparate conceptual models, model maturation, testing, and transition to application within the problem situation

Integrated Modelling Frameworks for Environmental Assessment and Decision Support

Modern management of environmental resources defines problems from a holistic and integrated perspective, imposing strong requirements to Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs), which tend to be increasingly complex in terms of software architecture and computational power in order to cope with the type of problems they must solve. Such systems need to support methodologies and techniques ranging from agent-based modelling to participatory decision-making. Sometimes EDSSs and IATs are built from scratch, often with limited resources, by non-programmers. The disadvantages of this approach, which can quickly become overly expensive in terms of delivery time and resources required, have been addressed by the development of suites of software engineering tools called Environmental Integrated Modelling Frameworks (EIMFs). EIMFs have typically been designed as a response to the increasing complexity of building and delivering EDSSs and IATs. Modelling and simulation tools and frameworks have been adopted at a large scale in the management science and operations research disciplines, and standards for developing and expanding them have been developed. In contrast, no modelling framework has been universally adopted within the environmental modelling domain, and the number of environmental modelling frameworks is still growing. In this book chapter, we strive to address the above issues and clearly identify the essential characteristics of an EIMF. This book chapter also advocates the development of open standards for the exchange and re-use of modelling knowledge, including data sets, models, and procedures in order to facilitate improved communication among the leading EIMF