Distinct roles of climate change and variability in driving runoff generation capacity changes across China's large reservoirs.

Authors

Kaiwen Wang, Yu Lu, Xiaomang Liu, Yuqi Li, Xiaohua Yang, Jiamiao Yu, Simon N Gosling

Published in

Science bulletin. Sep 11, 2026. Epub Sep 11, 2026.

Abstract

China has constructed over 900 large reservoirs to impound runoff from upstream drainage areas, supplying freshwater for industrial, agricultural, and domestic uses. Sufficient and stable runoff generation capacities across the drainage areas of these reservoirs are pivotal for securing sustainable water supply, yet they may be compromised under a changing climate. Nonetheless, changes in these capacities and their drivers remain unknown. Here, we integrate observation-based hydroclimatic data with georeferenced drainage boundaries to calculate runoff coefficients for 913 large reservoirs across China, thereby approximating the interannual magnitude and variability of runoff generation capacities. Nearly 40% of reservoirs exhibit decreasing and stabilizing runoff generation capacities from 1961 to 2018, mainly concentrated along a northeast-southwest stretch, whereas 60% show increasing and fluctuating trends on either side of this stretch. Attribution using an ensemble of Global Hydrological Models (GHMs) reveals distinct roles of anthropogenic climate change (ACC) and natural climate variability (NCV) in driving the magnitude and variability of runoff coefficients. Specifically, ACC and NCV jointly determine interannual magnitude changes, with ACC dominating 48% of reservoirs and NCV dominating 52%. NCV governs interannual variability changes, with median contribution rates ranging from 68% to 97% across different water resource regions. Given that ACC and NCV respectively drive directional and periodic changes, ACC-dominated reservoirs require targeted management-safeguarding supply where magnitude declines and expanding storage where it increases-whereas NCV-dominated reservoirs require improved early warning systems, enhanced short-term forecasting, and disaster response plans to reduce the adverse impacts of alternating drought and flood episodes.

PMID:
42816265
Bibliographic data and abstract were imported from PubMed on 01 Oct 2026.

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