Konferenzposter

Erschienen in: AGU Fall Meeting : San Francisco, 12-16 December 2016

Jahr der Veröffentlichung: 2016

Seiten: B13E-0672-

URL: https://agu.confex.com/agu/fm16/meetingapp.cgi/Paper/1474769

Abstract: 

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Advances in uncertainty propagation analysis and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the ‘spup’ package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo techniques, as well as several uncertainty visualization functions.
Here we will demonstrate that the ’spup’ package is an effective and easy-to-use tool to be applied even in a very complex study case, and that it can be used in multi-disciplinary research and model-based decision support. As an example, we use the ecological LandscapeDNDC model to analyse propagation of uncertainties associated with spatial variability of the model driving forces such as rainfall, nitrogen deposition and fertilizer inputs. The uncertainty propagation is analysed for the prediction of emissions of N₂O and CO₂ for a German low mountainous, agriculturally developed catchment. The study tests the effect of spatial correlations on spatially aggregated model outputs, and could serve as an advice for developing best management practices and model improvement strategies.

Harvard-Zitierstil: Sawicka, K., Breuer, L., Houska, T., Santabarbara Ruiz, I. and Heuvelink, G. (2016) spup - An R Package for Analysis of Spatial Uncertainty Propagation and Application to Trace Gas Emission Simulations [Poster], in AGU Fall Meeting : San Francisco, 12-16 December 2016. AGU. p. B13E-0672. https://agu.confex.com/agu/fm16/meetingapp.cgi/Paper/1474769

APA-Zitierstil: Sawicka, K., Breuer, L., Houska, T., Santabarbara Ruiz, I., & Heuvelink, G. (2016). spup - An R Package for Analysis of Spatial Uncertainty Propagation and Application to Trace Gas Emission Simulations. In AGU Fall Meeting : San Francisco, 12-16 December 2016. (p. B13E-0672). AGU. https://agu.confex.com/agu/fm16/meetingapp.cgi/Paper/1474769