Reliability of Semiarid Flash Flood Modeling Using Bayesian Framework
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 4
Abstract
A case study examining Bayesian techniques for assessing parameter and predictive uncertainty of semiarid flash flood events is presented here. The focus is on testing a fully distributed rainfall-runoff model (i.e., AFFDEF) linked with Markov chain Monte Carlo (MCMC) samplers to simulate four semiarid flash flood events with varying rainfall durations () and amounts (). MCMC samplers showed consistent behaviors with the a priori assumption and successfully improved performances on complex and multivariate search problems of semiarid flood simulation over the Abol-Abbas watershed, Iran. Analysis suggests that parameters associated with infiltration and interception capacity along with the contributing area threshold for the digital river network were the key model parameters and were more influential on the shape and volume of the flood hydrograph. Model predictive uncertainty was heavily dominated by error and bias in the soil water storage capacity, which reflects inadequate representation of the upper soil zone processes in the AFFDEF distributed model. Overall, the modeling results revealed that a fat-tailed Gaussian distribution using the standard least-squares (SLS) error assumption yielded improved estimates of parameter and predictive uncertainty for the semiarid flood events. This case study emphasizes the importance of proper statistical representation of the residual error distribution as a basis to improve parameter and predictive uncertainty.
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Acknowledgments
The authors appreciate those persons and agencies that assisted in accessing research data. Particular acknowledgment is given to the SCEM-UA, DREAM, and DREAM-ZS developer, Dr. Jasper Vrugt, from the University of California at Irvine, for his advice throughout the study. Special thanks are owed to Dr. Karim Abbaspour at the Swiss Federal Institute of Aquatic Science and Technology (Eawag), for providing an opportunity to visit Eawag for the first author during this research. The authors wish to thank three anonymous reviewers and the associate editor for their constructive criticism and fruitful discussions. This project was funded by Khozestan Water and Power Authority (KWPA) for Shahid Chamran University (Grant No. 038-02-02-89). The modified source code of AFFDEF linked to MCMC samplers can be obtained from the first author upon request.
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Journal of Hydrologic Engineering
Volume 22 • Issue 4 • April 2017
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©2016 American Society of Civil Engineers.
History
Received: Jan 19, 2016
Accepted: Sep 8, 2016
Published online: Nov 16, 2016
Published in print: Apr 1, 2017
Discussion open until: Apr 16, 2017
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