Please use this identifier to cite or link to this item:
|Title:||Parameter Conditioning and Prediction Uncertainties of the LISFLOOD-WB Distributed Hydrological Model|
|Authors:||DE ROO ARIE|
|Citation:||HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES vol. 51 no. 1 p. 45-65|
|Publisher:||IAHS PRESS, INST HYDROLOGY|
|Type:||Articles in periodicals and books|
|Abstract:||Distributed hydrological models are considered to be a promising tool for predicting the impacts of global change on the hydrological processes at the basin scale. However, distributed modelstypically require values of many parameters to be specified or calibrated, which exacerbates modelprediction uncertainty. This study uses the generalized likelihood uncertainty estimation (GLUE) technique to analyse the parameter sensitivities of a distributed hydrological model, LISFLOOD-WB.Discharge time series and event volume data of the Luo River at upstream and downstream sites,Lingkou and Lushi, are used to analyse parameter uncertainty. Eight key parameters in the model areselected for conditioning and sampled using the Monte Carlo method under assumed prior distributions.The results show that maximum efficiency of model performance is lower and the number of behavioural parameter sets giving acceptable performance is fewer in the Lingkou sub-basin than in theLushi sub-basin with the same criteria of acceptability. For both sub-basins the distribution shape parameter B in the fast runoff generation scheme is the most sensitive in predicting both discharge timeseries and event volume at the outlet. It is also shown that the value of parameter B at which the highestefficiency is derived is shifted from a high value for Lushi to a low value for Lingkou, consistent withpast experience of model calibration that the larger the basin, the larger the B value is. The channel Manning coefficient Nc shows some sensitivity in the prediction of discharge time series, but less in the prediction of event volumes. The other key parameters show little sensitivity and good simulations are found across the full range of parameter values sampled. The uncertainty bounds of predicted dischargesat the Lushi sub-basin are broad in the peak and narrow in the recession. The normalized difference between the upper and lower uncertainty bounds for both discharge and evapotranspiration are broad insummer and narrow in winter and that of recharge is the opposite.|
|JRC Directorate:||Sustainable Resources|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.