Bayesian Framework for Detecting Changes in Downstream Flow-Duration Curves Induced by Reservoir Operation Method

초록

The construction of a dam significantly alters downstream flow characteristics, often analyzed through changes in flow-duration curves before and after construction. Typically, post-dam flow-duration curves exhibit increased probabilities in low-flow zones and decreased probabilities in high-flow zones, primarily influenced by reservoir operation methods (ROMs). This study introduces a Bayesian framework to replace ROM simulations for predicting downstream flow-duration curve changes after dam construction, mainly during the flood season. Within this framework, inflow data are treated as random variables, and the ROM is analogized to a likelihood function in Bayesian analysis. The key challenge lies in deriving a likelihood function that mimics the given ROM. The Rigid ROM, a hybrid of constant rate and constant magnitude ROMs commonly used in the Republic of Korea, is targeted in this study. Using hourly inflow data from the Republic of Korea's Andong Dam (2010-2019), the proposed Bayesian method produces flow-duration curves closely matching simulation-based results, validating its accuracy. Furthermore, the method's ability to seamlessly handle multi-dam systems in a series highlights its practical advantage, attributed to the iterative nature of Bayesian updates. This study underscores the Bayesian approach's potential for efficient and robust flow-duration curve modeling in complex hydrological systems.

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