Assessment of Temporally Conditioned Runoff Fractions in Unregulated Rivers
Publication: Journal of Hydrologic Engineering
Volume 23, Issue 5
Abstract
Increasing nonstationarity increases the uncertainty of hydrological processes. Consequently, intrinsic randomness increases in magnitude and occurrence. In order to generate a reliable and robust predictive model, time series need to be better understood. This study addresses this challenge through the internal causality of annual runoff series. According to new methodological tendencies for hydrological research, complex temporal dependences within time series have been adequately captured through causal reasoning implemented by Bayes’ theorem. Those dependences permit quantifying the relative percentage of annual runoff change attributable to causality. This was later useful for calculating the temporally conditioned/nonconditioned runoff (TCR/TNCR) fractions. Results satisfactorily show the high and low temporally conditioned behavior of Porma-Esla and Adaja subbasin runoff, respectively. This study also provides a new stochastic approach for the return period (RP) assessment. Using TCR and TNCR fractions, the RP for each fraction was calculated and called the temporally conditioned RP (TCRP) and temporally nonconditioned RP (TNCRP), respectively. Results show coherent behavior, and, consequently, the highest RP corresponds to the largest runoff and vice versa.
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Acknowledgments
The authors especially appreciate the contribution in the phase of algebraic development of this research of Professor Dr. Marta Molina (Granada University, Spain).
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Journal of Hydrologic Engineering
Volume 23 • Issue 5 • May 2018
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©2018 American Society of Civil Engineers.
History
Received: Jul 13, 2017
Accepted: Oct 26, 2017
Published online: Mar 14, 2018
Published in print: May 1, 2018
Discussion open until: Aug 14, 2018
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