Journal of Hydrogeology & Hydrologic EngineeringISSN: 2325-9647

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Research Article, J Hydrogeol Hydrol Eng Vol: 2 Issue: 1

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

Jairo N. Diaz-Ramirez1*, Billy E. Johnson2, William H. McAnally3, James L. Martin4, Vladimir J. Alarcon5 and Rene A. Camacho6
1Director, Mississippi River Research Center, Alcorn State University, 1000 ASU Drive # 209, Alcorn State, MS, USA
2Research Civil Engineer, Engineer Research and Development Center (ERDC), 3909 Halls Ferry Road, Vicksburg, MS, USA
3Reasearch Professor, Department of Civil and Environmental Engineering, Mississippi State University, P.O. Box 9546, Mississippi State, MS, USA
4Professor, Department of Civil and Environmental Engineering, Mississippi State University, P.O. Box 9546, Mississippi State, MS, USA
5Assistant Research Professor, Geosystems Research Institute, Mississippi State University, Box 9627, Mississippi State, MS, USA
6Graduate Research Assistant, Department of Civil and Environmental Engineering, Mississippi State University, USA
Corresponding author : Jairo N. Diaz-Ramirez, Director
Mississippi River Research Center, Alcorn State University, 1000 ASU Drive # 209, Alcorn State, MS, USA
Tel:
(601) 877-3368
E-mail: [email protected]
Received: October 25, 2012 Accepted: March 12, 2013 Published: March 18, 2013
Citation: Diaz-Ramirez JN, Johnson BE, McAnally WH, Martin JL, Alarcon VJ, et al. (2013) Estimation and Propagation of Parameter Uncertainty in Lumped Hydrological Models: A Case Study of HSPF Model Applied to Luxapallila Creek Watershed in Southeast USA. J Hydrogeol Hydrol Eng 2:1. doi:10.4172/2325-9647.1000105

Abstract

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

Explicit quantification of the uncertainty associated to the predictions of a hydrologic model is a necessary activity to objectively evaluate and report the limitations of the model caused by different sources of error. The current state of the practice of hydrologic modeling indicates that parametric uncertainty is considered as one of the most important sources of uncertainty. Some of the most relevant problems remaining in the practice include the identification of the principal parameters affecting model predictions and quantification of parameter ranges. This study evaluated stochastically one of the most popular deterministic watershed water quality models for decision making in USA.

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