Estimation and Propagation of Parameter Uncertainty in Lumped Hydrological Models: A Case Study of HSPF Model Applied to Luxapallila Creek Watershed in Southeast USA

Díaz‐Ramirez, Jairo; Johnson, Billy E.; McAnally, William H.; Martin, James L.; Alarcon, Vladimir J.; Camacho, René A.

doi:10.4172/2325-9647.1000105

Cited by 6 publications

(4 citation statements)

References 33 publications

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“…Soil and Water Assessment Tool (SWAT) is currently linked with optimization technique, and has been used for automatic calibration [14][15][16]. Model-Independent Parameter Estimation and Uncertainty Analysis (PEST) is a nonlinear parameter estimation package, and widely used for automatic calibration tool of HSPF model [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Water Budget Components in Paddy Rice Field under the Asian Monsoon Climate: Application of HSPF-Paddy Model

Kim

Kim²,

Jeon

2014

Water

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Abstract:The HSPF-Paddy model was applied to the Bochung watershed in Korea to compare water budget components by the land use types under the Asian monsoon climate. The calibration of HSPF-Paddy during 1992-2001 with PEST, a package program to optimize HSPF, and validation during 1985-1991 were carried out. The model efficiencies for monthly stream flow are 0.85 for calibration and 0.84 for validation. The simulation of annual mean runoff met the criteria of water budget analysis with the acceptable error level (less than 10 percent mean error). The simulation of the movement of water from paddy rice field to watershed was successful, and application of HSPF-Paddy coupled with PEST was able to improve accuracy of model simulation with reduced time and efforts for model calibration. The results of water budget analysis show that most of the outflow (86%) for the urban area occurred through surface runoff, showing the highest rate among the land use types compared. Significant amounts of water are irrigated to paddy rice fields, and the runoff depth as well as evapotranspiration from paddy rice field is higher than other land use types. Hydrological characteristic of paddy rice field is that most of water movement occurred at the surface area, resulting from the low infiltration rate and manning's coefficient, as well as ponded water throughout the growing season. Major impact on input and output of water were precipitation and runoff, respectively, influenced by an Asian monsoon climate.

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Section: Introductionmentioning

confidence: 99%

Characteristics of Water Budget Components in Paddy Rice Field under the Asian Monsoon Climate: Application of HSPF-Paddy Model

Kim

Kim²,

Jeon

2014

Water

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“…While numerous past studies show satisfactory performance of simulated streamflow and water quality processes when evaluated on a continuous basis, the accuracy of HSPFmodeled concentration transport predictions shows to be (1) influenced by storm magnitude and frequency, (2) limited by the inability of ground-based meteorological stations to adequately cover the spatial extents and density necessary to represent watershed precipitation, and (3) seasonally dependent (Hayashi et al, 2004;Huo et al, 2015;Li et al, 2015;Stern et al, 2016). A few studies (Young et al, 2000;Wu et al, 2006;Diaz-Ramirez et al, 2013; and others) evaluated the propagation of errors in an HSPF model from input to output sugging that streamflow uncertainty is significantly impacted by precipitation patterns and magnitude, but may also be impacted by several other parameters and variables (e.g., land use classification, slope, infiltration capacity, soil moisture, groundwater recharge, and interflow recession) (Diaz-Ramirez et al, 2013). Additionally, Young et al (2000) noted that the uncertainty associated with sediment transport loads and water quality constituents are greatly impacted by the quality of precipitation input.…”

Section: Hydrologic Modelmentioning

confidence: 99%

On the Performance of Satellite-Based Precipitation Products in Simulating Streamflow and Water Quality During Hydrometeorological Extremes

Solakian

Maggioni

Godrej

2020

Front. Environ. Sci.

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This study provides a comprehensive evaluation of streamflow and water quality simulated by a hydrological model using three different Satellite Precipitation Products (SPPs) with respect to observations from a dense rain gauge network over the Occoquan Watershed, located in Northern Virginia, suburbs to Washington, D.C., U.S. Eight extreme hydrometeorological events within a 5-year period between 2008 and 2012 are evaluated using SPPs, TMPA 3B42-V7, CMORPH V1. 0, and PERSIANN-CCS, which are based on different retrieval algorithms with varying native spatial and temporal resolutions. A Hydrologic Simulation Program FORTRAN (HSPF) hydrology and water quality model was forced with the three SPPs to simulate output of streamflow (Q), stream temperature (TW), and concentrations of total suspended solids (TSS), orthophosphate phosphorus (OP), total phosphorus (TP), ammonium-nitrate (NH4-N), nitrate-nitrogen (NO3-N), dissolved oxygen (DO), and biochemical oxygen demand (BOD) at six evaluation points within the watershed. Results indicate fairly good agreement between gauge- and SPP-simulated Q for TMPA and CMORPH, however, PERSIANN-simulated Q is lowest among SPPs, due to its inability to accurately measure stratiform precipitation between intense periods of precipitation during an extreme event. Correlations of water quality indicators vary considerably, however, TW has the strongest positive linear relationship compared to other indicators evaluated in this study. SPP-simulated TSS, a flow-dependent variable, has the weakest relationship to gauge-simulated TSS among all water quality indicators, with CMORPH performing slightly better than TMPA and PERSIANN. This study demonstrated that the spatiotemporal variability of SPPs, along with their algorithms to estimate precipitation, have an influence on water quality simulations during extreme hydrometeorological events.

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“…Nevertheless, the accuracy of HSPF-modeled sediment transport predictions was shown to be (i) limited by the inability of ground-based meteorological stations to adequately cover the spatial extents and density necessary to represent watershed precipitation [65]; (ii) influenced by storm magnitude and frequency [65]; and (iii) seasonally dependent [42]. A few studies [66][67][68] evaluated the propagation of errors in an HSPF model from input to output. Diaz-Ramirez et al [66] suggested that streamflow uncertainty is significantly impacted by precipitation patterns and magnitude, but may also be impacted by several other parameters and variables (e.g., land use classification, slope, infiltration capacity, soil moisture, groundwater recharge, and interflow recession).…”

Section: Hydrologic Modelmentioning

confidence: 99%

“…A few studies [66][67][68] evaluated the propagation of errors in an HSPF model from input to output. Diaz-Ramirez et al [66] suggested that streamflow uncertainty is significantly impacted by precipitation patterns and magnitude, but may also be impacted by several other parameters and variables (e.g., land use classification, slope, infiltration capacity, soil moisture, groundwater recharge, and interflow recession). Young et al [68] determined that the quality of precipitation input data has a significant impact on the uncertainty associated not only with HSPF-simulated streamflow, but also with sediment transport loads and water quality constituents.…”

Section: Hydrologic Modelmentioning

confidence: 99%

Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model

2020

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This study investigated the propagation of errors in input satellite-based precipitation products (SPPs) on streamflow and water quality indicators simulated by a hydrological model in the Occoquan Watershed, located in the suburban Washington, D.C. area. A dense rain gauge network was used as reference to evaluate three SPPs which are based on different retrieval algorithms. A Hydrologic Simulation Program-FORTRAN (HSPF) hydrology and water quality model was forced with the three SPPs to simulate output of streamflow (Q), total suspended solids (TSS), stream temperature (TW), and dissolved oxygen (DO). Results indicate that the HSPF model may have a dampening effect on the precipitation-to-streamflow error. The bias error propagation of all three SPPs showed a positive dependency on basin scale for streamflow and TSS, but not for TW and DO. On a seasonal basis, bias error propagation varied by product, with larger values generally found in fall and winter. This study demonstrated that the spatiotemporal variability of SPPs, along with their algorithms to estimate precipitation, have an influence on water quality simulations in a hydrologic model.

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Estimation and Propagation of Parameter Uncertainty in Lumped Hydrological Models: A Case Study of HSPF Model Applied to Luxapallila Creek Watershed in Southeast USA

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Cited by 6 publications

References 33 publications

Characteristics of Water Budget Components in Paddy Rice Field under the Asian Monsoon Climate: Application of HSPF-Paddy Model

Characteristics of Water Budget Components in Paddy Rice Field under the Asian Monsoon Climate: Application of HSPF-Paddy Model

On the Performance of Satellite-Based Precipitation Products in Simulating Streamflow and Water Quality During Hydrometeorological Extremes

Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model

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