Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-903-2025
https://doi.org/10.5194/hess-29-903-2025
Research article
 | 
21 Feb 2025
Research article |  | 21 Feb 2025

Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments

Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu

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Cited articles

Ammann, L., Fenicia, F., and Reichert, P.: A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation, Hydrol. Earth Syst. Sci., 23, 2147–2172, https://doi.org/10.5194/hess-23-2147-2019, 2019. 
Armstrong, R. A.: Should Pearson's correlation coefficient be avoided?, Ophthal. Physl. Opt., 39, 316–327, https://doi.org/10.1111/opo.12636, 2019. 
Bales, R. C., Goulden, M. L., Hunsaker, C. T., Conklin, M. H., Hartsough, P. C., O'Geen, A. T., Hopmans, J. W., and Safeeq, M.: Mechanisms controlling the impact of multi-year drought on mountain hydrology, Sci. Rep., 8, 690, https://doi.org/10.1038/s41598-017-19007-0, 2018. 
Berghuijs, W. R., Larsen, J. R., van Emmerik, T. H. M., and Woods, R. A.: A global assessment of runoff sensitivity to changes in precipitation, potential evaporation, and other factors, Water Resour. Res., 53, 8475–8486, https://doi.org/10.1002/2017WR021593, 2017. 
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Short summary
This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
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