Web-based environmental simulation: bridging the gap between scientific modeling and decision-making.

Data availability in environmental sciences is growing rapidly. Conventional monitoring systems are collecting data at increasing spatial and temporal resolutions; satellites provide a constant stream of global observations, and citizen scientist generate local data with electronic gadgets and cheap devices. There is a need to process this stream of heterogeneous data into useful information, both for science and for decision-making. Advances in networking and computer technologies increasingly enable accessing, combining, processing, and visualizing these data. This Feature reflects upon the role of environmental models in this process. We consider models as the primary tool for data processing, pattern identification, and scenario analysis. As such, they are an essential element of science-based decision-making. The new technologies analyzed here have the potential to turn the typical top-down flow of information from scientists to users into a much more direct, interactive approach. This may accelerate the dissemination of environmental information to a larger community of users. It may also facilitate harvesting feedback, and evaluating simulations and predictions from different perspectives. However, the evolution poses challenges, not only to model development but also to the communication of model results and their assumptions, shortcomings, and errors.

[1]  Edward R. Tufte,et al.  The Visual Display of Quantitative Information , 1986 .

[2]  Jeffrey J. McDonnell,et al.  On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration , 2002 .

[3]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[4]  C. Walters Challenges in adaptive management of riparian and coastal ecosystems , 1997 .

[5]  W. Steffen,et al.  An Overview of the Implications of Global Change for Natural and Managed Terrestrial Ecosystems , 1997 .

[6]  B. Messerli Global Change and the World's Mountains , 2012 .

[7]  Hoshin Vijai Gupta,et al.  Do Nash values have value? , 2007 .

[8]  S. Lane,et al.  Doing flood risk science differently: an experiment in radical scientific method , 2011 .

[9]  Stefania Tamea,et al.  Verification tools for probabilistic forecasts of continuous hydrological variables , 2006 .

[10]  Keith Beven,et al.  On the colour and spin of epistemic error (and what we might do about it) , 2011 .

[11]  Tim Whiteaker,et al.  CUAHSI Web Services for Ground Water Data Retrieval , 2008 .

[12]  E. Tufte,et al.  The visual display of quantitative information , 1984, The SAGE Encyclopedia of Research Design.

[13]  G. Ottinger Buckets of Resistance: Standards and the Effectiveness of Citizen Science , 2010 .

[14]  Wim J. de Lange,et al.  Uncertainty Matters: Computer Models at the Science–Policy Interface , 2007 .

[15]  Jeffery S. Horsburgh,et al.  A first approach to web services for the National Water Information System , 2008, Environ. Model. Softw..

[16]  Keith Beven,et al.  Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process , 2007 .

[17]  Roger A. Pielke,et al.  Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends , 2011 .

[18]  J. Stedinger,et al.  Appraisal of the generalized likelihood uncertainty estimation (GLUE) method , 2008 .

[19]  Bryan N. Lawrence,et al.  A Flexible Component based Access Control Architecture for OPeNDAPServices , 2010 .

[20]  Jaroslav Mysiak,et al.  Bringing flood resilience into practice: the FREEMAN project , 2011 .

[21]  W. Buytaert,et al.  Potential impacts of climate change on the environmental services of humid tropical alpine regions , 2011 .

[22]  Dominik E. Reusser,et al.  Why can't we do better than Topmodel? , 2008 .

[23]  J. Palutikof,et al.  Climate change 2007 : impacts, adaptation and vulnerability , 2001 .

[24]  Anthony M. Castronova,et al.  Modeling water resource systems using a service-oriented computing paradigm , 2011, Environ. Model. Softw..

[25]  Mike Pearson,et al.  Visualizing Uncertainty About the Future , 2022 .

[26]  Alan S Kolok,et al.  Environmental scientists, biologically active compounds, and sustainability: the vital role for small-scale science. , 2011, Environmental science & technology.

[27]  P. Fayers,et al.  The Visual Display of Quantitative Information , 1990 .

[28]  Richard Washington,et al.  Issues in the interpretation of climate model ensembles to inform decisions , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[29]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[30]  Martyn P. Clark,et al.  Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models , 2008 .

[31]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[32]  Kirk Martinez,et al.  Environmental Sensor Networks: A revolution in the earth system science? , 2006 .

[33]  E. Sabine G. Schreiber,et al.  Adaptive management: a synthesis of current understanding and effective application , 2004 .

[34]  Johanna Alkan Olsson,et al.  Possibilities and problems with the use of models as a communication tool in water resource management , 2006 .

[35]  Dan Cornford,et al.  Automatic processing, quality assurance and serving of real-time weather data , 2011, Comput. Geosci..

[36]  J. Fogarty,et al.  Climate change, water resources and child health , 2010, Archives of Disease in Childhood.

[37]  Wouter Buytaert,et al.  Human impact on the hydrology of the Andean páramos , 2006 .

[38]  D. Hannah,et al.  Large‐scale river flow archives: importance, current status and future needs , 2011 .

[39]  J. E. Freera,et al.  Constraining dynamic TOPMODEL responses for imprecise water table information using fuzzy rule based performance measures , 2004 .

[40]  Peter Bajcsy,et al.  A Perspective on Cyberinfrastructure for Water Research Driven by Informatics Methodologies , 2008 .

[41]  Thomas Usländer,et al.  Designing environmental software applications based upon an open sensor service architecture , 2010, Environ. Model. Softw..