The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
An introduction to sensitivity assessment of simulation models
Open accessAbstract
In view of increasing application of sensitivity assessment (SA) to environmental simulation models, a relatively short, informal introduction to aims and methods of SA is given. Their variety, motivation and scope are illustrated by outlines of a broad selection of approaches. Methods based on derivatives, algebraic analysis, sparse sampling, variance decomposition, Fourier analysis and binary classification are included. A concise introductory overview of sensitivity assessment (SA) methods for simulation models is given.A broad selection of methods is introduced informally and with no more mathematics than necessary.The motivation of the methods, their scope and their limitations are discussed.Derivative-based SA, algebraic SA, SA of dynamical models, sampled SA, regional SA and SA by emulation are outlined.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Global Sensitivity Analysis. The Primer
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2007) · doi:10.1002/9780470725184 · Cited by 6,430
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output
Saltelli, A., Tarantola, S., & Chan, K. P.-S. (1999) · Technometrics · doi:10.1080/00401706.1999.10485594 · Cited by 2,275
Cited by
Flood inundation modelling: A review of methods, recent advances and uncertainty analysis
Teng, J., Jakeman, A. J., Vaze, J., Croke, B. F. W., Dutta, D., & Kim, S. (2017) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2017.01.006 · Cited by 1,456
Global Sensitivity Analysis of environmental models: Convergence and validation
Sarrazin, F., Pianosi, F., & Wagener, T. (2016) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2016.02.005 · Cited by 391
A Bayesian Belief Network to assess rate of changes in coral reef ecosystems
Franco, C., Hepburn, L. A., Smith, D. J., Nimrod, S., & Tucker, A. (2016) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2016.02.029 · Cited by 25
Metadata
- Authors
- Norton, J.
- Venue
- Environmental Modelling & Software
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 69
- Pages
- 166-174
- ISSN
- 1364-8152 (ISSN-L)
- OpenAlex
- W2054740476
- Cited by
- 186
- References
- 2
- FWCI
- 15.25
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An introduction to sensitivity assessment of simulation models. https://app.cochat.ai/papers/10.1016/j.envsoft.2015.03.020
- The paper
- Norton, J. (2015). An introduction to sensitivity assessment of simulation models. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2015.03.020
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
