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Sensitivity and uncertainty analysis in hydrological modeling: a case study of South Chickamauga Creek watershed using BASINS/HSPF

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Title: Sensitivity and uncertainty analysis in hydrological modeling: a case study of South Chickamauga Creek watershed using BASINS/HSPF
Authors: Dey, Preyanka
Source: Masters Theses and Doctoral Dissertations
Publisher Information: UTC Scholar
Publication Year: 2021
Collection: University of Tennessee at Chattanooga: UTC Scholar
Subject Terms: Computer programs--Validation, Hydraulic models
Description: Sensitivity and uncertainty analyses are crucial for the quality control and application of hydrological models in water resources management. While sensitivity analysis identifies major input parameters affecting model response, uncertainty analysis evaluates the uncertainty in model predictions. In this analysis, a Hydrological Simulation Program-Fortran (HSPF) model was developed for simulating surface and sub-surface hydrology, and creek flows in the South Chickamauga Creek Watershed, TN. The HSPF model was calibrated against USGS observed data from January 2013 to December 2017 and was validated for the period January 2018 to October 2019. Parameter Sensitivity analysis using the one-at-a-time (OAT) perturbation method revealed that watershed hydrology was highly sensitive to evapotranspiration and groundwater-related parameters. Uncertainty analysis with Monte Carlo and Latin Hypercube parameter sampling demonstrated the highest uncertainty in extreme flows and least uncertainty in annual runoff predictions. Overall, model output distribution was more uniform and achieved convergence faster with Latin hypercube sampling.
Document Type: text
File Description: application/pdf
Language: English
Relation: https://scholar.utc.edu/theses/712; https://scholar.utc.edu/context/theses/article/1886/viewcontent/ThesisFinal_PD_4.28.21.pdf
Availability: https://scholar.utc.edu/theses/712
https://scholar.utc.edu/context/theses/article/1886/viewcontent/ThesisFinal_PD_4.28.21.pdf
Rights: http://rightsstatements.org/vocab/InC/1.0/
Accession Number: edsbas.463BA4A1
Database: BASE
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  – Url: https://scholar.utc.edu/theses/712#
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Sensitivity and uncertainty analysis in hydrological modeling: a case study of South Chickamauga Creek watershed using BASINS/HSPF
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dey%2C+Preyanka%22">Dey, Preyanka</searchLink>
– Name: TitleSource
  Label: Source
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  Data: Masters Theses and Doctoral Dissertations
– Name: Publisher
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  Data: UTC Scholar
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  Data: 2021
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  Data: University of Tennessee at Chattanooga: UTC Scholar
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  Data: <searchLink fieldCode="DE" term="%22Computer+programs--Validation%22">Computer programs--Validation</searchLink><br /><searchLink fieldCode="DE" term="%22Hydraulic+models%22">Hydraulic models</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Sensitivity and uncertainty analyses are crucial for the quality control and application of hydrological models in water resources management. While sensitivity analysis identifies major input parameters affecting model response, uncertainty analysis evaluates the uncertainty in model predictions. In this analysis, a Hydrological Simulation Program-Fortran (HSPF) model was developed for simulating surface and sub-surface hydrology, and creek flows in the South Chickamauga Creek Watershed, TN. The HSPF model was calibrated against USGS observed data from January 2013 to December 2017 and was validated for the period January 2018 to October 2019. Parameter Sensitivity analysis using the one-at-a-time (OAT) perturbation method revealed that watershed hydrology was highly sensitive to evapotranspiration and groundwater-related parameters. Uncertainty analysis with Monte Carlo and Latin Hypercube parameter sampling demonstrated the highest uncertainty in extreme flows and least uncertainty in annual runoff predictions. Overall, model output distribution was more uniform and achieved convergence faster with Latin hypercube sampling.
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  Data: https://scholar.utc.edu/theses/712; https://scholar.utc.edu/context/theses/article/1886/viewcontent/ThesisFinal_PD_4.28.21.pdf
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  BibEntity:
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: Computer programs--Validation
        Type: general
      – SubjectFull: Hydraulic models
        Type: general
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      – TitleFull: Sensitivity and uncertainty analysis in hydrological modeling: a case study of South Chickamauga Creek watershed using BASINS/HSPF
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              Y: 2021
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