Project Description

Abstract

The Dam Toolbox, collaboratively developed by researchers on the NSF-EPSCoR Future of Dams project, is designed to: a) support user learning about a set of specific dam sites on the Penobscot River;  b) capture user preference information about decision criteria (e.g., annuitized project cost, sea-run fish habitat area, annual hydropower generation, etc.) and decision alternatives (e.g., remove dam, increase hydropower capacity, etc.); c) rank potential decision alternatives at each dam site based on the combination of user-defined preference information and site-specific data; d) explore multi-dam decision scenarios based on site-specific data and user preferences; and e) visually represent the user’s decision recommendation with graphs. We envision the Dam Decision Support Tool supporting multiple decision makers (e.g., regulators, municipalities, NGOs) in a participatory setting to identify a shared set of priorities independently of (but possibly complementary to) the Federal Energy Regulatory Commission’s Hydropower Dam Licensing Progress.

Project Description

The Dam Toolbox was developed and tested as part of the Participatory Multi-Criteria Decision Analysis (MCDA) Workshop with dam decision makers in Maine. Components of this toolbox include: Dam Factsheets, Dam Datasheets, Dam Decision Support Tool.

  • Dam Decision Support Tool: an interactive web-based application that uses Multi-Criteria Decision Analysis (MCDA) to support individual and group decision processes. MCDA is a structured decision making resulting in a ranked set of decision alternatives achieved by comparing and then weighting the performance of decision criteria with preference values. The Dam Decision Support Tool asks the user to specify numeric preference values for each decision criterion at each dam site within the given set. For each dam site, the sum of all preferences for any dam site must equal 1, so changes in one decision criterion preference value (e.g., increase preference for sea-run fish habitat area) must be compensated for by changes in another decision criterion preference value (e.g., decrease preference for annual hydropower generation). Then, preference ratings are combined with decision criteria performance data for a series of decision alternatives  (e.g., remove dam, improve hydropower generation) at each dam site. The results of the tool include: (a) a graph of decision alternatives for an individual dam; (b) a graph of decision alternatives at each dam broken down by decision criteria, based on user-defined preferences and data; (c) multi-dam graphed results, based on the highest ranked decision alternatives at each individual dam site ; and (c) a CSV file of the user preference ratings. Emma Fox describes the development of and implementation of the Dam Decision Support Tool in a series of workshops in her video-recorded dissertation defense.
  • Dam Factsheets: a brief packet of information for each dam including ownership history, site characteristics, and technical specifications, in addition to decision criteria performance data for all decision alternatives. We have compiled and defined this set of decision alternatives and decision criteria identified through interviews with decision makers and relevant to the Penobscot River watershed. The Dam Factsheets include site-specific data about the performance of each decision criterion under each decision alternative to help the user make choices in the Dam Decision Support Tool.
  • Dam Datasheets: a table of site-specific decision criteria information for each dam represented in the Dam Decision Support Tool. Data are quantitative and qualitative, collected or calculated for use in the Dam Decision Support Tool.
  • Supporting Documentation: a Google drive folder with additional background reading (publicly available documents only) and user support, including step-by-step video tutorial and an Advanced User Guide that briefly covers how to get started in modifying the source code to develop your own version of the web-based app in R Shiny. Other supporting documentation includes another Google Drive folder of evaluative rubrics and post- survey questions.