dc.contributor.author |
Musau, J. |
|
dc.contributor.author |
Sang, J. |
|
dc.contributor.author |
Gathenya, J. |
|
dc.contributor.author |
Luedeling, E. |
|
dc.contributor.author |
Home, P. |
|
dc.date.accessioned |
2016-10-03T11:47:33Z |
|
dc.date.available |
2016-10-03T11:47:33Z |
|
dc.date.issued |
2016-10-03 |
|
dc.identifier.uri |
www.jkuat-sri.com/ojs/index.php/sri/index |
|
dc.identifier.uri |
http://hdl.handle.net/123456789/2286 |
|
dc.description.abstract |
The parameter uncertainty in hydrological modelling has been accorded much attention in the recent past. Parameter
uncertainty is a major source of overall model unreliability. In this study, the HydroPSO R package was used to assess parameter
identification and uncertainty for the Soil and Water Assessment Tool (SWAT) model applied in the upper reaches of Nzoia River
Basin. Fourteen parameters were selected based on previous studies and parameter sensitivity analysis using the Latin Hypercube
Sampling method. Based on the optimum parameter set, the simulated flow corresponded well with the observed flow with daily
Percent Bias (PBIAS), coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) of -1.4, 0.73 and 0.72, respectively.
For monthly calibration, these values were -1.4, 0.78 and 0.77, respectively. The results of this study showuncertainty in parameter
identification. The posterior distributions of the parameter values were not normally distributed and the uncertainty ranges of the parameters varied widely. The low flows (Q5) were overestimated with a 13.8% bias while the Q50 and Q95 flows were
underestimated with -4.2% and -13.1% biases respectively. Further analysis indicated that the contribution of parameter uncertainty to stream flow simulation was substantial with 35% of the observed flow data falling within the 95% simulation confidence interval
for the calibration period. Different parameter sets gave the same correlation between the simulated and observed flows. A multiobjective analysis of the hydrological modeling uncertainties emanating from model selection, calibration procedure and
calibration data errors in the basin is therefore recommended. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
JKUAT |
en_US |
dc.relation.ispartofseries |
Journal of Sustainable Research in Engineering;Vol. 1 (3) 2014, 17-29 |
|
dc.subject |
hydroPSO |
en_US |
dc.subject |
parameter identification |
en_US |
dc.subject |
uncertainty analysis |
en_US |
dc.subject |
Nzoia Basin |
en_US |
dc.subject |
hydrological models |
en_US |
dc.title |
SWAT model parameter calibration and uncertainty analysis using the HydroPSO R package in Nzoia Basin, Kenya |
en_US |
dc.type |
Article |
en_US |