Presenter/Author Information

Vikas Kumar
A. Holzkämper
D. N. Lerner

Keywords

bayesian networks, decision support, integrated catchment management, meta-modelling, water framework directive

Start Date

1-7-2010 12:00 AM

Abstract

Developing supporting models for multidisciplinary, uncertain and complex Integrated Catchment Management (ICM) is a highly challenging task. Knowledge from multiple disciplines must be integrated, and the process is compounded by significant uncertainty. The key gap that provides the research context is the need for a holistic modelling framework to support ICM, able to capture system complexities and interrelationships, and identify long-term solutions to catchment management problems. In this paper, we present the feasibility study of a new framework for developing an integrated meta-model for decision-support in ICM. The study undertaken by the Catchment Science Centre at the University of Sheffield in a project called the Macro-Ecological Model (MEM) in collaboration with the Environment Agency of UK. The MEM is developed as a consistent framework for the integration of knowledge and information about environmental, social and economic processes and process-interactions that are affected by management actions and have impacts on multiple management objectives. The MEM combines the advantages of “soft” techniques of stakeholder participation for problem structuring, interdisciplinary communication and negotiation with the “hard” predictive capabilities for analysing the likely outcomes of different management scenarios. The metamodel could serve as a learning and decision-support tool to be applied within a group of decision-makers and stakeholders.

COinS
 
Jul 1st, 12:00 AM

Integrated Meta-Modelling for Decision Support in Integrated Catchment Management

Developing supporting models for multidisciplinary, uncertain and complex Integrated Catchment Management (ICM) is a highly challenging task. Knowledge from multiple disciplines must be integrated, and the process is compounded by significant uncertainty. The key gap that provides the research context is the need for a holistic modelling framework to support ICM, able to capture system complexities and interrelationships, and identify long-term solutions to catchment management problems. In this paper, we present the feasibility study of a new framework for developing an integrated meta-model for decision-support in ICM. The study undertaken by the Catchment Science Centre at the University of Sheffield in a project called the Macro-Ecological Model (MEM) in collaboration with the Environment Agency of UK. The MEM is developed as a consistent framework for the integration of knowledge and information about environmental, social and economic processes and process-interactions that are affected by management actions and have impacts on multiple management objectives. The MEM combines the advantages of “soft” techniques of stakeholder participation for problem structuring, interdisciplinary communication and negotiation with the “hard” predictive capabilities for analysing the likely outcomes of different management scenarios. The metamodel could serve as a learning and decision-support tool to be applied within a group of decision-makers and stakeholders.