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Updated: Aug 23, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Application of decision analysis to forest road deactivation in unstable terrain
Clay Allison1, Roy C Sidle, David Tait
1Allison and Associates Consultants Ltd., Vancouver, British Columbia, Canada.
Abstract:
Resource managers require objective methodologies to optimize decisions related to forest road deactivation and other aspects of road management, especially in steep terrain, where road-related slope failures inflict extensive environmental damage. Decision analysis represents a systematic framework that clearly identifies real options and critical decision points. This framework links current decisions with expected future outcomes and provides advantages such as a common currency to systematically explore the liability consequences of limited budget expenditures to road deactivation and other road-related activities. Furthermore, the decision framework prevents the analysis from becoming hopelessly entangled by the vast number of possibilities generated by the alternative occurrences, magnitudes, and consequences of landslide/debris flow events and provides the information required for the first step of an adaptive management process. Here, a structured analysis of potential environmental risks for a road deactivation project in coastal British Columbia, Canada is presented. The application of decision analysis generates a ranking of the expected benefits of proposed deactivation activities on various road sections. The ranking distinguishes between road sections that offer high expected benefit from those that offer moderate to low expected benefit. Seventeen of 171, 100-m road segments accounted for 18% of the cumulative cost and 98% of the cumulative expected net benefits from road deactivation. Furthermore, the cost of deactivating a section of road is related to the expected benefit from such deactivation, thus providing the basis for more effective resource allocation and budgeting decisions.
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