Change-point detection and trend magnitude estimation in long-term streamflow records of a transboundary river basin under climate change

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Global climate change is reshaping basin hydrology by altering precipitation timing, evaporative demand, runoff generation, and groundwater recharge, which makes long-term streamflow trend detection essential for sustainable water resources management and climate adaptation. In this study, monthly, seasonal, and annual streamflow trends from three gauging stations in the upper Euphrates basin (D21A001, E21A019, and E21A051) were evaluated using an integrated non-parametric framework that combines Mann–Kendall (MK), Spearman’s rank correlation (SRC), Sequential Mann–Kendall (SMK), innovative trend analysis (ITA), and ITA slope (ITAS). This multi-method design allowed consistent identification of trend direction, magnitude, and temporal transition behavior, while also improving interpretive robustness across stations with different streamflow characteristics. The results show a clear common signal: streamflow weakening is most pronounced in the spring to early summer period, although the strength and timing vary by station. E21A019 shows a relatively coherent declining trend across methods, particularly during April–June and at seasonal and annual scales, indicating a stronger tendency toward streamflow reduction compared to the other stations. E21A051 shows a seasonally contrasting regime, with increasing tendencies in winter and late summer/early autumn (notably January–February and August–September), but decreasing trends during spring and early summer, implying intra-annual redistribution rather than uniform change. D21A001 presents weaker trend magnitudes overall, yet decreasing tendencies are still evident in late spring, early summer, and autumn. Across methods, MK and SRC consistently support the trend directions, while ITA/ITAS better highlight magnitude and seasonal contrast. Overall, the findings provide robust evidence of long-term streamflow change and hydrological pressure in the upper Euphrates basin. They can support adaptive and transboundary water management planning, while attribution to specific climatic or anthropogenic drivers requires direct analysis of the relevant forcing variables. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2026.

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https://doi.org/10.1007/s11600-026-02023-yYayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorTanas Savaş, Gülçin
dc.contributor.authorErtugay, Neşe
dc.contributor.authorKatipoğlu, Okan Mert
dc.date.accessioned2026-10-18T20:25:33.974656861Z
dc.date.available2026-10-18T20:25:33.974656861Z
dc.date.issued2026
dc.description.abstractGlobal climate change is reshaping basin hydrology by altering precipitation timing, evaporative demand, runoff generation, and groundwater recharge, which makes long-term streamflow trend detection essential for sustainable water resources management and climate adaptation. In this study, monthly, seasonal, and annual streamflow trends from three gauging stations in the upper Euphrates basin (D21A001, E21A019, and E21A051) were evaluated using an integrated non-parametric framework that combines Mann–Kendall (MK), Spearman’s rank correlation (SRC), Sequential Mann–Kendall (SMK), innovative trend analysis (ITA), and ITA slope (ITAS). This multi-method design allowed consistent identification of trend direction, magnitude, and temporal transition behavior, while also improving interpretive robustness across stations with different streamflow characteristics. The results show a clear common signal: streamflow weakening is most pronounced in the spring to early summer period, although the strength and timing vary by station. E21A019 shows a relatively coherent declining trend across methods, particularly during April–June and at seasonal and annual scales, indicating a stronger tendency toward streamflow reduction compared to the other stations. E21A051 shows a seasonally contrasting regime, with increasing tendencies in winter and late summer/early autumn (notably January–February and August–September), but decreasing trends during spring and early summer, implying intra-annual redistribution rather than uniform change. D21A001 presents weaker trend magnitudes overall, yet decreasing tendencies are still evident in late spring, early summer, and autumn. Across methods, MK and SRC consistently support the trend directions, while ITA/ITAS better highlight magnitude and seasonal contrast. Overall, the findings provide robust evidence of long-term streamflow change and hydrological pressure in the upper Euphrates basin. They can support adaptive and transboundary water management planning, while attribution to specific climatic or anthropogenic drivers requires direct analysis of the relevant forcing variables. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2026.
dc.identifier.doi10.1007/s11600-026-02023-y
dc.identifier.eissn1895-7455
dc.identifier.issn1895-6572
dc.identifier.issue5
dc.identifier.scopus2-s2.0-105050387405
dc.identifier.startpage288
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/10332
dc.identifier.volume74
dc.identifier.wosWOS:001873710300001
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofActa Geophysica
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEuphrates basin
dc.subjectHydrological variability
dc.subjectNon-parametric trend methods
dc.subjectStreamflow data
dc.subjectTrend analysis
dc.subjectGroundwater resources
dc.subjectStream flow
dc.subjectWater conservation
dc.subjectWater management
dc.subjectEuphrate basin
dc.subjectEuphrates
dc.subjectInnovative trends
dc.subjectMann-Kendall
dc.subjectNon-parametric trend method
dc.subjectNon-parametric trends
dc.subjectUpper euphrates basins
dc.subjectclimate change
dc.subjectdetection method
dc.subjecthydrological change
dc.subjectmagnitude
dc.subjectstreamflow
dc.titleChange-point detection and trend magnitude estimation in long-term streamflow records of a transboundary river basin under climate change
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus0
rdl.citation.wos0
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)