Runoff Reconstructions and Future Projections Indicate Highly Variable Water Supply From Pacific Rim Water Towers

Abstract Anthropogenic climate change affects regional hydrological cycles and poses significant challenges to the sustainable supply of freshwater. The Central China water tower (CCWT) is the key source region feeding the Yangtze and Yellow Rivers, and its runoff is indispensable for the surrounding mega‐city clusters. Here we present a reconstruction of CCWT runoff depth (RD) back to 1595 CE, based on a new dendrochronological network including 100 tree‐ring sampling sites and an ensemble averaging approach that combines multiple regression models. Comparison of this reconstruction with similar records from six water tower regions along the Pacific Rim (Mongolian Plateau, Tibetan Plateau TP, Great Dividing Range, Southern and Northern Rocky Mountains, Andes Mountains) revealed that the CCWT provide the most stable water supply, while the TP to be most susceptible to extreme runoff events. Twenty‐first century projections indicate generally increasing runoff across most Pacific Rim water towers, whereas the Northern Rocky Mountains are projected to decline substantially. We attribute the differences in runoff variability and projected trends across Pacific Rim water towers to their distinct geographies and synoptic climatic conditions. The long‐term runoff reconstructions and projected changes highlighted in this study provide insights for adaptive management strategies in China and all other regions relying on supply from mountain water towers.

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Publication Details

Journal
AGU Advances
Published
2026-01-03
DOI
https://doi.org/10.1029/2025av002053
Citations
1
Primary Topic
Tree-ring climate responses
Type
article
Field-Weighted Citation Impact
40.64

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article

Runoff Reconstructions and Future Projections Indicate Highly Variable Water Supply From Pacific Rim Water Towers

H. Wang, Junqiang Niu, F. Chen, Jan Esper et al.
1 citations
AGU Advances
Tree-ring climate responses
40.64
article

Runoff Reconstructions and Future Projections Indicate Highly Variable Water Supply From Pacific Rim Water Towers

H. Wang, Junqiang Niu, F. Chen, Jan Esper, Martín A. Hadad, Edurne Martínez del Castillo, Tiyuan Hou, Weipeng Yue, Frederick Reinig, Shijie Wang, Mao Hu, Heli Zhang, Yang Xu, Max C. A. Torbenson, Fidel A. Roig, Xiaoen Zhao, Youping Chen, Álvaro González‐Reyes, Honghua Cao
article en
1 citations

Abstract

Abstract Anthropogenic climate change affects regional hydrological cycles and poses significant challenges to the sustainable supply of freshwater. The Central China water tower (CCWT) is the key source region feeding the Yangtze and Yellow Rivers, and its runoff is indispensable for the surrounding mega‐city clusters. Here we present a reconstruction of CCWT runoff depth (RD) back to 1595 CE, based on a new dendrochronological network including 100 tree‐ring sampling sites and an ensemble averaging approach that combines multiple regression models. Comparison of this reconstruction with similar records from six water tower regions along the Pacific Rim (Mongolian Plateau, Tibetan Plateau TP, Great Dividing Range, Southern and Northern Rocky Mountains, Andes Mountains) revealed that the CCWT provide the most stable water supply, while the TP to be most susceptible to extreme runoff events. Twenty‐first century projections indicate generally increasing runoff across most Pacific Rim water towers, whereas the Northern Rocky Mountains are projected to decline substantially. We attribute the differences in runoff variability and projected trends across Pacific Rim water towers to their distinct geographies and synoptic climatic conditions. The long‐term runoff reconstructions and projected changes highlighted in this study provide insights for adaptive management strategies in China and all other regions relying on supply from mountain water towers.

AGU AdvancesVol. 7(1)
China Meteorological Administration (CN), Austral University of Chile (CL), Yunnan University (CN), Johannes Gutenberg University Mainz (DE), National University of San Juan (AR), Czech Academy of Sciences, Global Change Research Institute (CZ)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Tree-ring climate responses
40.64
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