Effects of model segmentation approach on the performance and parameters of the Hydrological Simulation Program – Fortran (HSPF) models

2014 ◽  
Vol 45 (6) ◽  
pp. 893-907 ◽  
Author(s):  
Changan Yan ◽  
Wanchang Zhang
Keyword(s):  
Model Performance ◽  
Meteorological Station ◽  
Simulation Program ◽  
Hydrological Simulation ◽  
Hspf Model ◽  
Simulation Efficiency ◽  
Model Segmentation ◽  
Segmentation Approach ◽  
Static Sensitivity ◽  
Sensitivity Method

Although models are one of the most powerful tools for watershed management, their effectiveness is limited by prediction uncertainties resulting from not only model input data but also spatial discretization. In this paper, Hydrological Simulation Program – Fortran (HSPF) models were constructed for the Linyi watershed according to three segmentation approaches including model segments based on differences in: (1) sub-watershed, (2) meteorological station, and (3) physical characteristics. Then the static sensitivity method and dynamic sensitivity method were employed to evaluate the effect of the segmentation approach on model performance and parameters of HSPF. The main conclusions were: (1) modeling with 12 segments had the best simulation efficiency and the corresponding estimated parameters had a certain representation within the Linyi watershed; (2) HSPF model performance was significantly affected by the segmentation approach, especially by the model segmentation construction process which considering a meteorological station or not; (3) parameters INTFW (interflow inflow parameter), lower zone nominal storage, and upper zone nominal storage (UZSN) were most affected by the model segmentation approach, while parameter AGWRC (groundwater recession coefficient) changed indistinctly; (4) parameters UZSN and INTFW had the same variation tendency whenever the segmentation approach changed.

scholarly journals Hydrological Modeling of the Paligad Watershed (India) Using HSFP Model

2019 ◽  
pp. 217-228
Author(s):  
Aamir Ishaq Shah ◽  
Sumit Sen ◽  
Anurag Mishra
Keyword(s):  
Hydrological Modeling ◽  
Simulation Program ◽  
Expert Advice ◽  
Coefficient Of Determination ◽  
Hydrological Simulation ◽  
Hspf Model ◽  
Hydrological System ◽  
Set Up

For hydrological studies, it is well known that each hydrological system behaves differently and in order to effectively manage those systems, it is necessary to understand their behavior. The hydrological component of Hydrological Simulation Program – FORTRAN (HSPF) model was set up and calibrated for Paligad watershed which is a sub-basin of Aglar watershed in the Uttarakhand state of India. The calibration of the model was done manually and an expert advice system called as HSPEXP+ was used to aid calibration. The values of evaluation indicators such as coefficient of determination (

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

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 171 ◽  
Author(s):  
Hui Xie ◽  
Zhenyao Shen ◽  
Lei Chen ◽  
Xijun Lai ◽  
Jiali Qiu ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Uncertainty Analysis ◽  
Continuous Model ◽  
Base Flow ◽  
Moisture Distribution ◽  
Simulation Program ◽  
Runoff Generation ◽  
Hydrological Simulation ◽  
Hspf Model ◽  
Event Based

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.

scholarly journals Hydrologic sensitivity of the Upper San Joaquin River Watershed in California to climate change scenarios

2012 ◽  
Vol 44 (4) ◽  
pp. 723-736 ◽  
Author(s):  
Zili He ◽  
Zhi Wang ◽  
C. John Suen ◽  
Xiaoyi Ma
Keyword(s):  
Climate Change ◽  
Sierra Nevada ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Hydrological Simulation ◽  
River Watershed ◽  
System Sensitivity ◽  
Hspf Model ◽  
San Joaquin River ◽  
San Joaquin River Watershed

To examine the hydrological system sensitivity of the southern Sierra Nevada Mountains of California to climate change scenarios (CCS), five headwater basins in the snow-dominated Upper San Joaquin River Watershed (USJRW) were selected for hydrologic simulations using the Hydrological Simulation Program-Fortran (HSPF) model. A pre-specified set of CCS as projected by the Intergovernmental Panel on Climate Change (IPCC) were adopted as inputs for the hydrologic analysis. These scenarios include temperature increases between 1.5 and 4.5 °C and precipitation variation between 80 and 120% of the baseline conditions. The HSPF model was calibrated and validated with measured historical data. It was then used to simulate the hydrologic responses of the watershed to the projected CCS. Results indicate that the streamflow of USJRW is sensitive to the projected climate change. The total volume of annual streamflow would vary between −41 and +16% compared to the baseline years (1970–1990). Even if the precipitation remains unchanged, the total annual flow would still decrease by 8–23% due to temperature increases. A larger portion of the streamflow would occur earlier in the water year by 15–46 days due to the temperature increases, causing higher seasonal variability of streamflow.

scholarly journals Responses of hydrological model equifinality, uncertainty, and performance to multi-objective parameter calibration

2018 ◽  
Vol 20 (4) ◽  
pp. 864-885 ◽  
Author(s):  
Younggu Her ◽  
Chounghyun Seong
Keyword(s):  
Model Performance ◽  
Mathematical Representation ◽  
Objective Functions ◽  
Parameter Calibration ◽  
Hydrological Simulation ◽  
Multi Objective ◽  
Adequate Number ◽  
Hydrological System ◽  
And Performance ◽  
The Impact

Abstract Multi-objective calibration can help identify parameter sets that represent a hydrological system and enable further constraining of the parameter space. Multi-objective calibration is expected to be more frequently utilized, along with the advances in optimization algorithms and computing resources. However, the impact of the number of objective functions on modeling outputs is still unclear, and the adequate number of objective functions remains an open question. We investigated the responses of model performance, equifinality, and uncertainty to the number of objective functions incorporated in a hierarchical and sequential manner in parameter calibration. The Hydrological Simulation Program – FORTRAN (HSPF) models that were prepared for bacteria total maximum daily load (TMDL) development served as a mathematical representation to simulate the hydrological processes of three watersheds located in Virginia, and the Expert System for Calibration of HSPF (HSPEXP) statistics were employed as objective functions in parameter calibration experiments. Results showed that the amount of equifinality and output uncertainty overall decreased while the model performance was maintained as the number of objective functions increased sequentially. However, there was no further significant improvement in the equifinality and uncertainty when including more than four objective functions. This study demonstrated that the introduction of an adequate number of objective functions could improve the quality of calibration without requiring additional observations.

Comparison between dynamic and static sensitivity analysis approaches for impact assessment of different potential evapotranspiration methods on hydrological models performance

2021 ◽  
Author(s):  
Rodric Mérimé Nonki ◽  
André Lenouo ◽  
Christopher J. Lennard ◽  
Raphael M. Tshimanga ◽  
Clément Tchawoua
Keyword(s):  
Sensitivity Analysis ◽  
Impact Assessment ◽  
Hydrological Modeling ◽  
Potential Evapotranspiration ◽  
Model Performance ◽  
Estimation Methods ◽  
Model Parameters ◽  
Hydrological Models ◽  
Sensitivity Approach ◽  
Static Sensitivity

AbstractPotential Evapotranspiration (PET) plays a crucial role in water management, including irrigation systems design and management. It is an essential input to hydrological models. Direct measurement of PET is difficult, time-consuming and costly, therefore a number of different methods are used to compute this variable. This study compares the two sensitivity analysis approaches generally used for PET impact assessment on hydrological model performance. We conducted the study in the Upper Benue River Basin (UBRB) located in northern Cameroon using two lumped-conceptual rainfall-runoff models and nineteen PET estimation methods. A Monte-Carlo procedure was implemented to calibrate the hydrological models for each PET input while considering similar objective functions. Although there were notable differences between PET estimation methods, the hydrological models performance was satisfactory for each PET input in the calibration and validation periods. The optimized model parameters were significantly affected by the PET-inputs, especially the parameter responsible to transform PET into actual ET. The hydrological models performance was insensitive to the PET input using a dynamic sensitivity approach, while he was significantly affected using a static sensitivity approach. This means that the over-or under-estimation of PET is compensated by the model parameters during the model recalibration. The model performance was insensitive to the rescaling PET input for both dynamic and static sensitivities approaches. These results demonstrate that the effect of PET input to model performance is necessarily dependent on the sensitivity analysis approach used and suggest that the dynamic approach is more effective for hydrological modeling perspectives.

A Novel 3D Model Segmentation Approach

2010 ◽  
Author(s):  
Y. Wang ◽  
R. Liu ◽  
S. Endo ◽  
Y. Uehara
Keyword(s):  
3D Model ◽  
Model Segmentation ◽  
Segmentation Approach
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