| ARCH Resilience Pathways Visualization Tool |
The RPVT provides a user-friendly graphical interface to create and visualize resilience pathways. It allows users to select, prioritize, and sequence different possible measures over time, which can be deployed as circumstances evolve. Measures can be selected and prioritized according to various performance metrics, primarily addressing floods and heatwaves, but also earthquakes and drought/water scarcity. |
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| Adaptation Catalyst |
The Adaptation Catalyst is a software tool designed to help overcome the ‘implementation gap’ in realizing adaptive capacity, to get from research and design to actual realization of measures. The AC does this by offering the possiblity to assemble primary information about climate pressure and the adaptive capacity of measures into one overview. This is the information that usually results from climate effect and adaptation options research projects. Added to this is functionality to interactively vary climate pressure and characteristics of measures, and instantly view what the result of these changes are on adaptive capacity, co-benefits and costs. This will help create awareness, help with chosing and planning of measures and support decision making about adaptation strategies. |
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| Colorado River Basin Post-2026 Operations Exploration Tool |
This is a flexible, powerful platform designed to allow Colorado River Basin stakeholders and the public to explore operational strategies for Lake Powell and Lake Mead as part of the Post-2026 National Environmental Policy Act (NEPA) Process. This tool is intended to support early-stage exploration of operational strategies that may eventually be incorporated into the Post-2026 NEPA alternatives. For more information on this NEPA process, see Colorado River Post-2026 Operations. |
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| Colorado River Robustness Tradeoffs |
This app is a decision support dashboard for the Bureau of Reclamation to identify robust water management policies in the Colorado River Basin. Water managers filter policies by performance objectives, robustness metrics, and decision variables. |
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| EMA Workbench |
Exploratory Modeling and Analysis (EMA) is a research methodology that uses computational experiments to analyze complex and uncertain systems (Bankes, 1993). That is, exploratory modeling aims at offering computational decision support for decision making under deep uncertainty and Robust Decision Making. |
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| OpenMOLE |
OpenMOLE has been developed since 2008 as a free and open-source platform. It offers tools to run, explore, diagnose and optimize your numerical model, taking advantage of distributed computing environments. With OpenMOLE you can explore your already developed model, in any language (Java, Binary exe, NetLogo, R, SciLab, Python, C++, etc.) |
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| PRIM (Python package) |
Prim's algorithm is a greedy algorithm used to find the Minimum Spanning Tree (MST) of a connected, undirected graph. The MST is a subset of the edges that connects all vertices in the graph with the minimum possible total edge weight. |
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| Pathways Generator |
The Pathways Generator Tool (PG) develops pathways maps to define the solution for space and allow comparison of alternative pathways into the future, via evaluations of costs, benefits and co-benefits. Together, DAPP and the PG have been used for flood risk in Miami, water supply in San Francisco and coastal flooding in Aveiro, Portugal, among others. |
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| Rhodium |
Rhodium is an open source Python library for robust decision making (RDM), many-objective robust decision making (MORDM), and exploratory modeling. These decision-support frameworks enable the identification of robust strategies for the management of complex environmental systems, by evaluating the tradeoffs among candidate strategies, and characterizing their vulnerabilities. Robust strategies refer to management options that perform sufficiently well or acceptably under a range of potential system conditions, rather than optimally in a single, nominal state of the world. Exploratory modeling allows for the simulation of the system under an ensemble of states of the world, so as to discover the ones with consequential effects on the system. Rhodium facilitates rapid application of the RDM and MORDM frameworks by providing a suite of optimization, visualization, scenario discovery, and sensitivity analysis functions. Rhodium is written in Python and can interface with models written in Python, C and C++, Fortran, R, and Excel. |
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| Robustness Analysis Producing Intelligent Decisions (RAPID) |
To aid decision making about environmental systems under deep uncertainty, robustness metrics are commonly used to represent system performance over a number of scenarios. However, there are many robustness metrics and many ways of generating scenarios, making it difficult to know which to choose in order to quantify system robustness and to make robust decisions. To address this shortcoming, we introduce a generic guidance framework to assist with the identification of the most robust decision alternatives, as well as the RAPID (Robustness Analysis Producing Intelligent Decisions) software package which is a consistent and easy-to-use implementation of the framework. |
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| SALib |
Python implementations of commonly used sensitivity analysis methods, including Sobol, Morris, and FAST methods. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest. |
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| ScenarioWizard |
The ScenarioWizard software was developed to perform CIB analysis and has been used, tested and further developed in numerous application projects and method experiments. It is provided in two versions: ScenarioWizard for Windows and ScenarioWizard Online. Both versions can be used free of charge. The data formats of both versions are compatible so that the project files can be shared between the two versions. |
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| TMIP-EMAT |
TMIP-EMAT is a methodological approach to exploratory modeling and analysis. It provides a window to rigorous analytical methods for handling uncertainty and making well informed decisions using travel forecasting models of all types. It is designed to integrate with an existing transportation model or tool to perform exploratory analysis of a range of possible scenarios. |
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| mDSS |
mDSS is a Decision Support System tool to facilitate participatory processes for the sustainable and integrated – economic, social and environmental – management of natural resources. |
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| openMORDM |
OpenMORDM is an open-source R library for Multiobjective Robust Decision Making (MORDM). The design of OpenMORDM and a walkthrough of applying MORDM to an environmental model is detailed in the following journal article: Hadka, D., Herman, J., Reed, P.M., Keller, K. An Open Source Framework for Many-Objective Robust Decision Making. Environmental Modelling & Software, 74:114-129, 2015. DOI:10.1016/j.envsoft.2015.07.014. |
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| scikit-learn |
Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities. |
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| sdtoolkit |
The package provides interactive functions for scenario discovery, stepping the user through the use of PRIM. PRIM identifies "boxes" in parameter space with "interesting" scenarios, i.e. bounds on parameters where scenarios meets some pre-defined criteria. |
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