Toolcatalogus

Introduction

This document provides an overview of a selection of tools for uncertainty assessment that can be applied to gain insights in nature and size of different sorts of uncertainties in environmental assessments that may occur at different locations.

The tools covered in this document are:

• Sensitivity Analysis (screening, local, global)
• Error propagation equations ("Tier 1")
• Monte Carlo Analysis ("Tier 2")
• Expert Elicitation
• NUSAP (Numeral Unit Spread Assessment Pedigree)
• Scenario Analysis
• PRIMA (Pluralistic fRamework of Integrated uncertainty Management and risk Analysis)
• Checklist for Model Quality Assistance
• Critical Review of Assumptions

This toolbox is under development and does not pretend to be exhaustive. The tools described may in literature and practice exist in many different flavours, not all of them being covered in this document. The selection is made in such a way that the set of tools covers all sorts and locations of uncertainties distinguished in the uncertainty typology presented in the guidance. Also it matches current practice and recent Research and Development and Demonstration activities within RIVM in the fields of uncertainty assessment and management.

To assist in selecting tools for conducting uncertainty assessment in a given case, table 1 presents the uncertainty typology used in the guidance and shows what tools can be used to address each of the sorts and locations of uncertainty distinguished.

Some of the tools are hard to map. For instance, the PRIMA approach is a meta-method for uncertainty assessment integrating many of the other tools depending on its particular implementation, and hence covering much more of the table than is suggested at first glance. We have listed the PRIMA in those boxes of the table where we consider it particularly strong. The same holds true for the NUSAP method, which generally includes some quantitative tool (sensitivity analysis or Monte Carlo analysis) in combination with systematic critical review and pedigree analysis.

Further it should be noted that the use of many of the tools is not limited to the boxes in which they are listed. For instance, sensitivity analysis could also be applied to assess sensitivity to different model structures and scenario analysis and sensitivity analysis (screening) may overlap. In a Monte Carlo assessment one could address model structure uncertainty by introducing a switch-parameter to switch between different model equations representing different conceivable model structures and sample for that switch-parameter from for instance a uniform distribution. So the table should not be interpreted too strict, it gives a rough overview of the basic scope of application of each tool.

The remainder of this document provides a tool-by-tool description. For each tool we give a brief description of what it does and how it works and we provide the following information:

• What sorts and locations of uncertainty does this tool address?
• What resources are required to use the tool?
• Strengths and limitations of each tool
• Some guidance on the application of the tools and hints on complementarity with other tools
• Typical pitfalls of each tool
• References to handbooks, user-guides, example case studies, web sites and in-house and external experts who have knowledge on and experience with each tool and who may be consulted by RIVM for further advice.

Table 1 Correspondence of the tools with the sorts and locations of uncertainty distinguished in the uncertainty typology from the hints and actions section of the quick scan. Entries printed in italics are not described in this toolbox because there are no standard methods to perform these tasks.