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|Title:||Integrated Modelling Frameworks for Environmental Assessment and Decision Support|
|Authors:||RIZZOLI Andrea; LEAVESLEY G.; DONATELLI Marcello; ASCOUGH II J.c.; ARGENT R.m.; ATHANASIADIS I.n.; BRILHANTE V.; CLAEYS F.h.a.; DAVID O.; GIJSBERSJ P.; HAVLIK D.; KASSAHUN A.; KRAUSE P.; QUINN N.w.t.; SCHOLTEN H.; SOJDA R.s.; VILLA F.|
|Type:||Articles in books|
|Abstract:||As argued in Chapter 1 modern management of environmental resources defines problems from a holistic and integrated perspective, imposing strong requirements on Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs). These systems and tools 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. For instance, the discipline of Integrated Assessment (IA) needs tools that are able to span a wide range of disciplines, from socio-economics to ecology to hydrology. Such tools need to support a wide range of methodologies and techniques like agent-based modelling, Bayesian decision networks, optimisation, multicriteria analyses and visualisation tools, to name a few. Sometimes EDSSs and IATs are built from scratch, often with limited resources, by non-programmers. From a software point of view, these applications are custommade, by craftspeople rather than industrially developed by professionals. More recently, 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 frameworks are not a novelty per se, having made a first appearance in the management science field towards the end of the 1980s (Dolk and Kottemann, 1993; Geoffrion, 1987). The framework concept later found its way into commercial packages such as MATLAB for scientific computing, GAMS and AMPL for management science and operations research applications. Moreover, modelling and simulation tools and frameworks have been taken up on a large scale in other disciplines, and standards for developing and expanding them have been adopted. As a result, electrical circuit design toolkits and printed circuit board simulators have contributed significantly to the advancement of electronics in science and industry. The same holds for many other sectors, from the automotive industry to mechanical systems design. In contrast, no modelling framework has been universally adopted within the environmental modelling domain, and the number of environmental modelling frameworks is still growing. A frequently asked question is: ¿why do we need yet another modelling framework?¿ The reasons why MATLAB (http://www.mathworks.com), MathCAD (http://www.mathsoft.com), Mathematica (http://www.wolfram.com) and similar software environments are not up to the task of deploying effective and usable EDSSs are often unclear, and there is always the option of re-using an existing EIMF. Yet, this option is often disregarded, again without clear reasoning behind it. In this chapter, we strive to address the above issues and clearly identify the essential characteristics of an EIMF. Moreover, we wish to: (1) point out the main differences among the leading EIMFs present on the (scientific) market; and (2) assess which characteristics justify the differences, and which characteristics are artificial and should be ignored to better facilitate interchange of knowledge and experiences in EIMF development. Finally, this 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 EIMFs.|
|JRC Institute:||Institute for the Protection and Security of the Citizen|
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