The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Sensitivity and identifiability of stream flow generation parameters of the SWAT model
Abstract
Implementation of sensitivity analysis (SA) procedures is helpful in calibration of models and also for their transposition to different watersheds. The reported studies on SA of Soil and Water Assessment Tool (SWAT) model were mostly focused on identifying parameters for pruning or modifying during the calibration process. This paper presents a sensitivity and identifiability analysis of model parameters that influence stream flow generation in SWAT. The analysis was focused on evaluating the sensitivity of the parameters in different climatic settings, temporal scales and flow regimes. The global sensitivity analysis (GSA) technique based on classical decomposition of variance, Sobol', was employed in this study. The results of the study indicate that modeled stream flow show varying sensitivity to parameters in different climatic settings. The results also suggest that the identifiability of a parameter for a given watershed is a major concern in calibrating the model for the specific watershed, as it might lead to equifinality of parameters. The SWAT model parameters show varying sensitivity in different years of simulation suggesting the requirement for dynamic updation of parameters during the simulation. The sensitivity of parameters during various flow regimes (low, medium and high flow) is also found to be uneven, which suggests the significance of a multi‐criteria approach for the calibration of models. Copyright © 2010 John Wiley & Sons, Ltd.
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
River flow forecasting through conceptual models part I — A discussion of principles
Nash, J. E., & Sutcliffe, J. V. (1970) · Journal of Hydrology · doi:10.1016/0022-1694(70)90255-6 · Cited by 23,674
LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1
Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998) · JAWRA Journal of the American Water Resources Association · doi:10.1111/j.1752-1688.1998.tb05961.x · Cited by 7,945
McKay, M. D., Beckman, R. J., & Conover, W. J. (2000) · Technometrics · doi:10.2307/1271432 · Cited by 7,415
Global sensitivity indices for nonlinear mathematical models and their monte carlo estimates
Sobol′, I. M. (2001) · Mathematics and Computers in Simulation · doi:10.1016/s0378-4754(00)00270-6 · Cited by 6,389
The future of distributed models: model calibration and uncertainty prediction
Beven, K., & Binley, A. (1992) · Hydrological Processes · doi:10.1002/hyp.3360060305 · Cited by 4,527
McKay, M. D., Beckman, R. J., & Conover, W. J. (1979) · Technometrics · doi:10.2307/1268522 · Cited by 3,757
Computer Models of Watershed Hydrology
Singh, V. P. (1995) · Medical Entomology and Zoology · Cited by 3,273
Gassman, P. W., Reyes, M. R., Green, C. H., & Arnold, J. G. (2007) · Transactions of the ASABE · doi:10.13031/2013.23637 · Cited by 3,040
Importance measures in global sensitivity analysis of nonlinear models
Homma, T., & Saltelli, A. (1996) · Reliability Engineering & System Safety · doi:10.1016/0951-8320(96)00002-6 · Cited by 2,011
SWAT2000: current capabilities and research opportunities in applied watershed modelling
Arnold, J. G., & Fohrer, N. (2005) · Hydrological Processes · doi:10.1002/hyp.5611 · Cited by 1,336
Metadata
- Authors
- Cibin, R., Sudheer, K. P., & Chaubey, I.
- Venue
- Hydrological Processes
- Publisher
- Wiley
- Published
- 2010-01-13
- Volume
- 24
- Issue
- 9
- Pages
- 1133-1148
- ISSN
- 0885-6087 (ISSN-L)
- 1099-1085
- OpenAlex
- W2088876159
- Cited by
- 309
- References
- 44
- FWCI
- 10.82
- Type
- journal article
- Language
- en
- Open access
- closed
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: Sensitivity and identifiability of stream flow generation parameters of the SWAT model. https://app.cochat.ai/papers/10.1002/hyp.7568
- The paper
- Cibin, R., Sudheer, K. P., & Chaubey, I. (2010). Sensitivity and identifiability of stream flow generation parameters of the SWAT model. Hydrological Processes. https://doi.org/10.1002/hyp.7568
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.