Snow-Dependence Modulates Warming-Induced Seasonal Extremization in Mountain Watersheds

Mountain watersheds are experiencing divergent hydrological responses to warming, yet the mechanisms controlling this divergence remain unclear. We introduce the Seasonal Extremization Index (SEI), the ratio of dry-season mean flow to annual median flow, to quantify changes in seasonal flow structure. Across 78 watersheds in the western United States, spring warming drives SEI decline (r = -0.277, p = 0.043), but this effect is strongly modulated by snow reliance (SRF). In snow-influenced watersheds (n = 54), the interaction between SRF and spring warming explains 18.0% additional variance in SEI trends (p < 0.001; stratified bootstrap 95% CI [-0.721, -0.092]). We validated the predictive power of this relationship using a temporal split: early-period SRF (1990-2005) significantly predicts late-period SEI decline (2006-2020) across 36 watersheds (r = -0.405, p = 0.014). High-SRF watersheds show significant SEI decline (r = -0.492, p = 0.009), while low-SRF watersheds show no significant response (r = +0.091, p = 0.652). We identify four anchor types with distinct response pathways. A cross-region application to 14,406 grid points in Chinese mountains reveals a latitudinal gradient: snow anchor failure in the north (>40°N) and monsoon-driven anchor strengthening in the south (<35°N). These results suggest that mountain hydrological futures are determined not by warming alone, but by the strength of snow reliance, which acts as an amplifier of warming effects.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-13
DOI
https://doi.org/10.5281/zenodo.22736287
Primary Topic
Hydrology and Watershed Management Studies
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
preprint

Snow-Dependence Modulates Warming-Induced Seasonal Extremization in Mountain Watersheds

Qiao Ou
Zenodo (CERN European Organization for Nuclear Research)
Hydrology and Watershed Management Studies
preprint

Snow-Dependence Modulates Warming-Induced Seasonal Extremization in Mountain Watersheds

Qiao Ou
preprint en

Abstract

Mountain watersheds are experiencing divergent hydrological responses to warming, yet the mechanisms controlling this divergence remain unclear. We introduce the Seasonal Extremization Index (SEI), the ratio of dry-season mean flow to annual median flow, to quantify changes in seasonal flow structure. Across 78 watersheds in the western United States, spring warming drives SEI decline (r = -0.277, p = 0.043), but this effect is strongly modulated by snow reliance (SRF). In snow-influenced watersheds (n = 54), the interaction between SRF and spring warming explains 18.0% additional variance in SEI trends (p < 0.001; stratified bootstrap 95% CI [-0.721, -0.092]). We validated the predictive power of this relationship using a temporal split: early-period SRF (1990-2005) significantly predicts late-period SEI decline (2006-2020) across 36 watersheds (r = -0.405, p = 0.014). High-SRF watersheds show significant SEI decline (r = -0.492, p = 0.009), while low-SRF watersheds show no significant response (r = +0.091, p = 0.652). We identify four anchor types with distinct response pathways. A cross-region application to 14,406 grid points in Chinese mountains reveals a latitudinal gradient: snow anchor failure in the north (>40°N) and monsoon-driven anchor strengthening in the south (<35°N). These results suggest that mountain hydrological futures are determined not by warming alone, but by the strength of snow reliance, which acts as an amplifier of warming effects.

Zenodo (CERN European Organization for Nuclear Research)
Life in Land
Hydrology and Watershed Management Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.