Stationarity assumptions in streamflow sensitivity to precipitation may bias future projections

Anderson, Bailey J. ORCID: https://orcid.org/0000-0002-5936-3346; Slater, Louise J. ORCID: https://orcid.org/0000-0001-9416-488X; Rapson, Jessica; Brunner, Manuela I. ORCID: https://orcid.org/0000-0001-8824-877X; Dadson, Simon J. ORCID: https://orcid.org/0000-0002-6144-4639; Yin, Jiabo; Buechel, Marcus. 2025 Stationarity assumptions in streamflow sensitivity to precipitation may bias future projections. Earth's Future, 13 (7), e2025EF006188. 17, pp. 10.1029/2025EF006188

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Official URL: https://doi.org/10.1029/2025EF006188

Abstract/Summary

Streamflow elasticity to precipitation is a metric which is used to estimate how responsive rivers are to changes in precipitation. It is commonly used to anticipate future impacts of climate change on streamflow and is assumed to be constant in time, despite evidence that this relationship varies with climatological and landscape changes. To assess the need for a more flexible definition, we present a large-sample non-stationary regional regression approach to estimate long-term trends and variability in interannual streamflow elasticity to precipitation in the USA. We find that elasticity is highly variable in water-limited catchments year-to-year, indicating high sensitivity to climate variability in arid regions. Statistically significant long-term trends in elasticity exist in some regions, but trend magnitude is generally small. We demonstrate that a single average estimate of elasticity may be a poor indicator of streamflow sensitivity to climate change. Consideration of the variability of response is essential for elasticity to be a useful hydrologic signature.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1029/2025EF006188
UKCEH and CEH Sections/Science Areas:	Directors, SCs
ISSN:	2328-4277
Additional Information:	Open Access paper - full text available via Official URL link.
Additional Keywords:	sensitivity, elasticity, hydrology, non-stationarity
NORA Subject Terms:	Earth Sciences Hydrology Data and Information
Related URLs:	Dataset Dataset Dataset Dataset Dataset
Date made live:	11 Jul 2025 09:36 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/539849

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1029/2025EF006188

UKCEH and CEH Sections/Science Areas:

Directors, SCs

ISSN:

2328-4277

Additional Information:

Open Access paper - full text available via Official URL link.

Additional Keywords:

sensitivity, elasticity, hydrology, non-stationarity