Articles | Volume 26, issue 7
https://doi.org/10.5194/hess-26-1845-2022
https://doi.org/10.5194/hess-26-1845-2022
Research article
 | 
12 Apr 2022
Research article |  | 12 Apr 2022

Critical transitions in the hydrological system: early-warning signals and network analysis

Xueli Yang, Zhi-Hua Wang, and Chenghao Wang

Data sets

CRU TS4.03: Climatic Research Unit (CRU) Time-Series (TS) version 4.03 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901-Dec. 2018) Centre for Environmental Data Analysis https://data.ceda.ac.uk/badc/cru/data/cru_ts/cru_ts_4.03/data

Climate at a Glance: City Time Series NOAA - National Oceanic and Atmospheric Administration National, Centers for Environmental Information https://www.ncdc.noaa.gov/cag/city/time-series

TIGER/Line Geodatabases US Census Bureau https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-geodatabase-file.html

Daymet: Monthly Climate Summaries on a 1-km Grid for North America, Version 3 M. M. Thornton, P. E. Thornton, Y. Wei, B. W. Mayer, R. B. Cook, and R. S. Vose https://doi.org/10.3334/ORNLDAAC/1345

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Short summary
In this study, we investigated potentially catastrophic transitions in hydrological processes by identifying the early-warning signals which manifest as a critical slowing down in complex dynamic systems. We then analyzed the precipitation network of cities in the contiguous United States and found that key network parameters, such as the nodal density and the clustering coefficient, exhibit similar dynamic behaviour, which can serve as novel early-warning signals for the hydrological system.