Time‐varying operation policies with GRU‐based parameterization for adaptive multi‐objective reservoir operation under climate change

Wei, Yiming, Wang, Renchao, Zhuo, Lu and Dong, Zengchuan 2026. Time‐varying operation policies with GRU‐based parameterization for adaptive multi‐objective reservoir operation under climate change. Water Resources Research 62 (10) , e2025WR043033. 10.1029/2025wr043033

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Abstract

Designing reservoir operation policies that can adapt to non-stationary hydroclimatic conditions is a major challenge for water resources management under climate change. This study develops an adaptive dynamic operation policy (ADOP), in which Gaussian radial basis functions (RBFs) are coupled with a gated recurrent unit (GRU)-based parameterization module that maps meteorological information to time-varying RBF weights. Using the reservoir system in the Qingjiang River Basin, China, as a case study, ADOP is optimized using an expanded historical hydroclimatic ensemble within an evolutionary multi-objective direct policy search (EMODPS) framework and is evaluated under both an independent historical test period and 12 GCM-based climate scenarios. A static operation policy (SOP) and a scenario-specific re-optimized ideal operation policy (IOP) are used as benchmarks. Results show that ADOP outperforms SOP under both historical training and test conditions. Under future scenarios, ADOP achieves higher hypervolume than SOP in 10 of 12 scenarios, indicating the advantage of the time-varying parameterization in out-of-sample conditions. Although both historically trained policies retain a performance gap relative to the re-optimized IOP, ADOP partially mitigates this gap. The water-level and release trajectories for representative years further demonstrate that the advantage of ADOP is associated with improved storage–release coordination. Moreover, a diagnostic comparison supports the value of the GRU-based module, as adding meteorological inputs to a static RBF policy does not reproduce ADOP's gains. The proposed time-varying policy provides a practical pathway for improving the adaptability of historically trained reservoir operation policies under uncertain future hydroclimatic conditions.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Earth and Environmental Sciences Schools > Physical, Chemical & Environmental Sciences
Publisher:	American Geophysical Union (AGU)
ISSN:	0043-1397
Date of First Compliant Deposit:	26 October 2026
Date of Acceptance:	29 September 2026
Last Modified:	26 Oct 2026 13:15
URI:	https://orca.cardiff.ac.uk/id/eprint/190434

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