Groundwater Decision Support System (GWDSS) has been designed for integrated systems approaches to water management. GWDSS supports participatory processes and advanced computational approaches to test scientific uncertainty and communicate about water management alternatives with stakeholders, citizens and policy makers.
The GWDSS system has been used in a number of mixed human–machine approaches to link the inter-related parts of water resource challenges. GWDSS provides an accessible and open source application for science-based management of groundwater.
Multi-criteria decision analysis (MCDA) represents an emerging decision aid tool in the field of natural resource decision-making. This thesis involves research into the application of a multi-criteria spatial decisions support system (MOSDSS) to support favorability mapping of geothermal resource potential. The main goal is to provide proof of concept of a tool that can facilitate multi-stakeholder engagement during site selection of a potential power generation facility. It presents information on the history and development of spatial decision support systems in the field of environmental and natural resource decision-making, as well as a case study of a MC-SDSS tool—entitled the "Heatseeker" application— developed and applied to geothermal resource potential in the Eastern Snake River Plain, Idaho.
This research was first conducted under a grant from the U.S. Department of Energy National Geothermal Student Competition, The Heatseeker application and supporting infrastructure utilizes a client/server system architecture that provides users with access to spatial and tabular data with low bandwidth requirements. Client-side scripting is used to execute a weighted linear combination (WLC) model and provide users with display and report functionality. Additionally, the tool is optimized for use with a gesture-enabled touch device that serves as a boundary object to facilitate participatory stakeholder engagement. The result of this research is a proof of concept in supporting future MC-SDSS design that can be applied both to geothermal favorability mapping and other natural resource management processes.
This work draws upon the research traditions of multiple academic disciplines, including operations research, computer science, cognitive and behavioral psychology, economics, and public policy. The initial development and application of the MC-SDSS tool involved a team of graduate and undergraduate students from geoscience and social science disciplines. Transdisciplinary approaches to problem structuring and decision-making such as this are an increasingly common approach to natural resource issues.
Multi-criteria decision analysis (MCDA) represents an emerging decision aid tool in the field of natural resource decision-making. This work draws upon the research traditions of multiple academic disciplines, including operations research, computer science, cognitive and behavioral psychology, economics, and public policy. Transdisciplinary approaches to problem structuring and decision-making such as this are an increasingly common approach to natural resource issues.
The use of multi-criteria spatial decision support systems (MCSDSS)— an integration of geographical information systems (GIS), decision support systems (DSS), and multiple criteria decision analysis (MCDA) — has emerged as a decision aid approach for evaluating conflicting objectives and stakeholder preferences in the implementation of spatial decision models.
This research presents an open-source tool that supports a spatial decision-making process by providing better access to information, increased ease of public participation, and support for distributed collaboration amongst various groups of stakeholders in remote environments.
Geoscientists are confronted with the need to evaluate complex information that is of interest to other researchers, as well as potentially useful to non-scientific audiences. Handling the dynamic problem structures, disparate data types, and a broad range of stakeholder perspectives present daunting transdisciplinary challenges.The developing Watermark application devises reusable workflows, and accessible computational tools for connecting data, models, and interactive decision support dashboards.
Watermark is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, Watermark offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics.