Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models

The CRANE Framework for Simulation Model Workflows

CRANE is presented as a flexible framework for linking simulation models and model support tools to form integrated modelling systems for engineering and scientific applications, evaluated using the scientific workflow approach. CRANE was written using an object-oriented programming language; the separation of its core processing component from its user interface; support for plugins that can be updated and enhanced independent of the framework; and with intuitive user-friendly features and human-readable configuration files. Its strength is its ability to connect to legacy simulation models, whose code cannot be modified, through structured and/or free-format text files. The framework contains an engine that interprets the requirements of simulation models and modelling support tools, and facilitates the flow of data between these components in a simulation workflow. In addition, a user interface provides a familiar graphic interface through which the engine can be configured and monitored during the evaluation of the simulation workflow. A case study was undertaken to demonstrate the ability of CRANE to wrap around, configure, and evaluate two versions of a hydrologic simulation model. Using the default parameter configuration, both versions of the model failed to capture the hydrologic regime of the basin; the modified version of the model only marginally improved the results by redistributing excess meltwater in a presumably more physically based way. The modified version of the model allowed excess meltwater to contribute to ponded storage and infiltrate into soil. By contrast, the original version of the model increased the evaporation rate to account for the excess meltwater. Given the poor overall performance of the model in this particular modelling scenario, the contribution of the modification could not be definitively commented upon. It was concluded that further assessment would be improved by better parameterization of the model. CRANE was used to configure the input files for the model, as well as to execute a simple simulation workflow. Unfortunately, the relative simplicity of the case study did not highlight the more advanced features of the framework. As this is a preliminary introduction of the framework, additional and different types of case studies are recommended, the results from which would identify areas where the framework can continue to be developed and enhanced

Space transportation system and associated payloads: Glossary, acronyms, and abbreviations

A collection of some of the acronyms and abbreviations now in everyday use in the shuttle world is presented. It is a combination of lists that were prepared at Marshall Space Flight Center and Kennedy and Johnson Space Centers, places where intensive shuttle activities are being carried out. This list is intended as a guide or reference and should not be considered to have the status and sanction of a dictionary

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling and Software Vol. 62 (2014), DOI: 10.1016/j.envsoft.2014.09.013The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts

Portuguese SKA white book

Sem resumo disponível.publishe

A selective list of acronyms and abbreviations

A glossary of acronyms, abbreviations, initials, code words, and phrases used at the John F. Kennedy Space Center is presented. The revision contains more than 12,100 entries

Space Transportation System and associated payloads: Glossary, acronyms, and abbreviations

A collection of acronyms now in everyday use in the Shuttle world are listed. It is a combination of lists that were prepared at the Kennedy and Johnson Space Centers and by the Air Force

Space Transportation System and associated payloads: Glossary, acronyms, and abbreviations

A collection of acronyms in everyday use concerning shuttle activities is presented. A glossary of terms pertaining to the Space Transportation System is included