Parameter Estimation and Uncertainty Analysis: A Comparison between Continuous and Event-Based Modeling of Streamflow Based on the Hydrological Simulation Program–Fortran (HSPF) Model

• Published in: Water (Basel) 2019-01, Vol.11 (1), p.171
• Main Authors: Xie, Hui, Shen, Zhenyao, Chen, Lei, Lai, Xijun, Qiu, Jiali, Wei, Guoyuan, Dong, Jianwei, Peng, Yexuan, Chen, Xinquan
• Format: Article
• Language: English
• Subjects: Base flow; Climate change; Computer simulation; FORTRAN; Gravity; Groundwater; Hydrologic models; Hydrology; Laboratories; Land use; Modelling; Nonpoint source pollution; Outflow; Parameter estimation; Parameter sensitivity; Parameter uncertainty; Precipitation; Rain and rainfall; Rainfall; Runoff; Sensitivity analysis; Simulation; Stormwater management; Stream discharge; Stream flow; Streamflow; Topography; Uncertainty analysis; Water outflow; Watershed management; Watersheds
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w11010171

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.