Committee Chair

Bathi, Jejal Reddy

Committee Member

Wu, Weidong; Ghasemi, Arash; Hossain, A.K.M. Azad

Department

Dept. of Civil and Chemical Engineering

College

College of Engineering and Computer Science

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

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.

Acknowledgments

The author would like to acknowledge the funding support from the Tennessee Higher Education Commission: Center of Excellence in Computational Science and Engineering Grant Competition (CEACSE) at the University of Tennessee at Chattanooga.

Degree

M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.

Date

5-2021

Subject

Computer programs--Validation; Hydraulic models

Keyword

HSPF; Model calibration; Validation; Sensitivity analysis; Uncertainty analysis

Document Type

Masters theses

DCMI Type

Text

Extent

x, 72

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by/4.0/

Date Available

10-31-2022

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