one that is the least well understood. However, it also represents the toolkit
that may have the greatest impact on environmental management, given its
nature as the “glue” between the other three toolkits.
The overarching, common requirements of the toolkits may warrant a
toolkit development approach that builds and shares modules-meeting
these common requirements while providing specific modules to meet
the more focused requirements of the modeler, stakeholder, and decision
maker. Given such commonality, especially that noted between the stakeholder’s and decision maker’s toolkits, we believe that one adaptive toolkit,
with modules that meet the specific needs of stakeholders and decision
makers, may be an effective paradigm for toolkit development.
As alluded to in Sidebar 12.1, several federal agencies in the United
States and many international organizations have expressed interest in the
development of such toolkits. There is significant potential for synergism
between these individual initiatives, so collaboration among these differing
groups in the development of toolkits should be formalized and expanded.
This partnering is particularly important in developing standards and protocols (common linkages among different models, assessment tools, and
databases). The ability of components within a given toolkit to communicate, the opportunity for new components to join and function within a
toolkit, and the effectiveness of virtual development teams to build new
tools in a distributed fashion are all directly and specifically related to the
establishment and acceptance of a single set of standards and protocols in
environmental management.
The utility of the toolkit concept must be more formally documented in
real-world problem solving. In this regard, Case et al. (2000) recommend
that a series of demonstrations be conducted that exercise and build upon
the different toolkits discussed in this chapter. We strongly endorse this
recommendation.
References
Babovic, V. and V.H. Bojkov. 2001. Runoff Modeling with Genetic Programming and
Artificial Neural Networks. D2K Technical Report 0401-1. Danish Hydraulics
Institute (DHI) Water and Environment, Copenhagen, Denmark.
Case, M.P., T. Gunther, W.D. Goran, J.P. Holland, D. Johnston, G. Lessard, and W.J.
Schmidt. 2000. Decision Support Capabilities for Future Technology Requirements. ERDC TR-01-2. U.S. Army Corps of Engineers, Engineer Research and
Development Center, Champaign, Illinois, USA.
Committee of Scientists. 1999. Sustaining the People’s Lands: Recommendations for
Stewardship of the National Forests and Grasslands into the Next Century. U.S.
Department of Agriculture, Washington, District of Columbia, USA.
Crowe, S. 2000. Spatial modeling environments: Integration of GIS and conceptual
modeling frameworks. Presented at the Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and
Research Needs, Banff, Alberta, Canada, 2–8 September, 2000.
12. Role of Computational Toolkits in Environmental Management
243
that may have the greatest impact on environmental management, given its
nature as the “glue” between the other three toolkits.
The overarching, common requirements of the toolkits may warrant a
toolkit development approach that builds and shares modules-meeting
these common requirements while providing specific modules to meet
the more focused requirements of the modeler, stakeholder, and decision
maker. Given such commonality, especially that noted between the stakeholder’s and decision maker’s toolkits, we believe that one adaptive toolkit,
with modules that meet the specific needs of stakeholders and decision
makers, may be an effective paradigm for toolkit development.
As alluded to in Sidebar 12.1, several federal agencies in the United
States and many international organizations have expressed interest in the
development of such toolkits. There is significant potential for synergism
between these individual initiatives, so collaboration among these differing
groups in the development of toolkits should be formalized and expanded.
This partnering is particularly important in developing standards and protocols (common linkages among different models, assessment tools, and
databases). The ability of components within a given toolkit to communicate, the opportunity for new components to join and function within a
toolkit, and the effectiveness of virtual development teams to build new
tools in a distributed fashion are all directly and specifically related to the
establishment and acceptance of a single set of standards and protocols in
environmental management.
The utility of the toolkit concept must be more formally documented in
real-world problem solving. In this regard, Case et al. (2000) recommend
that a series of demonstrations be conducted that exercise and build upon
the different toolkits discussed in this chapter. We strongly endorse this
recommendation.
References
Babovic, V. and V.H. Bojkov. 2001. Runoff Modeling with Genetic Programming and
Artificial Neural Networks. D2K Technical Report 0401-1. Danish Hydraulics
Institute (DHI) Water and Environment, Copenhagen, Denmark.
Case, M.P., T. Gunther, W.D. Goran, J.P. Holland, D. Johnston, G. Lessard, and W.J.
Schmidt. 2000. Decision Support Capabilities for Future Technology Requirements. ERDC TR-01-2. U.S. Army Corps of Engineers, Engineer Research and
Development Center, Champaign, Illinois, USA.
Committee of Scientists. 1999. Sustaining the People’s Lands: Recommendations for
Stewardship of the National Forests and Grasslands into the Next Century. U.S.
Department of Agriculture, Washington, District of Columbia, USA.
Crowe, S. 2000. Spatial modeling environments: Integration of GIS and conceptual
modeling frameworks. Presented at the Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and
Research Needs, Banff, Alberta, Canada, 2–8 September, 2000.
12. Role of Computational Toolkits in Environmental Management
243