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Updated: Jun 8, 2026
10:22
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Analysis of uncertainty propagation through model parameters and structure.
Abhijit Patil1, Zhi-Qiang Deng
1Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA. abhijitapatil1@gmail.com
Summary
This study effectively estimates uncertainty in watershed models using Rosenblueth and sensitivity analysis for Hydrologic Simulation Program-FORTRAN (HSPF) models. Results show water temperature significantly impacts dissolved oxygen, crucial for total maximum daily load (TMDL) calculations.
Area of Science:
- Environmental Science
- Hydrology
- Water Quality Modeling
Background:
- Estimating uncertainty propagation in watershed models is critical for accurate Total Maximum Daily Load (TMDL) calculations.
- The Hydrologic Simulation Program-FORTRAN (HSPF) model is widely used for TMDL development, but its uncertainty analysis presents challenges.
Purpose of the Study:
- To present an effective approach for determining uncertainty propagation in the HSPF model's parameters and structure.
- To assess the impact of water temperature on dissolved oxygen (DO) and biochemical oxygen demand (BOD) within the HSPF model.
Main Methods:
- Combined application of the Rosenblueth method and sensitivity analysis to quantify uncertainty.
- Comparison of descriptive statistics for dissolved oxygen data from HSPF simulations and Rosenblueth's method.
- Calculation of error propagation from water temperature to dissolved oxygen, including second-order sensitivity coefficients.
Main Results:
- Water temperature identified as a major forcing function influencing the DO-BOD balance and overall dissolved oxygen concentration.
- Error propagation from water temperature to dissolved oxygen, considering second-order sensitivity, yielded a mean of 0.281 mg/l and a standard deviation of 0.099 mg/l.
- Low error propagation values were attributed to low skewness in dependent and independent variables.
Conclusions:
- The developed approach provides valuable insights into uncertainty propagation within the HSPF model.
- The findings support improved accuracy in TMDL development by quantifying model uncertainties.
- Understanding the influence of water temperature on DO is essential for effective water quality management.
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