Parameter Estimation and Uncertainty Analysis for Rainfall Infiltration in Unsaturated Soils Using a Bayesian Approach

2011 ◽  
Author(s):  
L. L. Zhang ◽  
J. Zhang ◽  
B. Gao
2019 ◽  
Vol 151 ◽  
pp. 170-182 ◽  
Author(s):  
Long T. Ho ◽  
Andres Alvarado ◽  
Josue Larriva ◽  
Cassia Pompeu ◽  
Peter Goethals

2018 ◽  
Vol 48 (10) ◽  
pp. 2459-2482 ◽  
Author(s):  
Hoa Pham ◽  
Darfiana Nur ◽  
Huong T. T. Pham ◽  
Alan Branford

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 171 ◽  
Author(s):  
Hui Xie ◽  
Zhenyao Shen ◽  
Lei Chen ◽  
Xijun Lai ◽  
Jiali Qiu ◽  
...  

Hydrologic modeling is usually applied to two scenarios: continuous and event-based modeling, between which hydrologists often neglect the significant differences in model application. In this study, a comparison-based procedure concerning parameter estimation and uncertainty analysis is presented based on the Hydrological Simulation Program–Fortran (HSPF) model. Calibrated parameters related to base flow and moisture distribution showed marked differences between the continuous and event-based modeling. Results of the regionalized sensitivity analysis identified event-dependent parameters and showed that gravity drainage and storage outflow were the primary runoff generation processes for both scenarios. The overall performance of the event-based simulation was better than that of the daily simulation for streamflow based on the generalized likelihood uncertainty estimation (GLUE). The GLUE analysis also indicated that the performance of the continuous model was limited by several extreme events and low flows. In the event-based scenario, the HSPF model performances decreased as the precipitation became intense in the event-based modeling. The structure error of the HSFP model was recognized at the initial phase of the rainfall-event period. This study presents a valuable opportunity to understand dominant controls in different hydrologic scenario and guide the application of the HSPF model.


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