A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024

Abstract. Snowmelt runoff onset timing represents a critical hydrological parameter, particularly in mountainous regions where seasonal snow serves as a natural reservoir for downstream water resources. Despite this importance, high-resolution observations of snowmelt runoff onset across complex terrain are limited, due to challenges from sparse in situ monitoring networks, intermittent optical remote sensing data, and coarse passive microwave remote sensing data. To address this gap, we prepared a global snowmelt runoff onset timing dataset (https://doi.org/10.5281/zenodo.16953614, Gagliano et al., 2026) for the 10-year period spanning 2015–2024, with 80 m spatial resolution and 9.5 d average temporal resolution. We created this dataset by identifying backscatter minima empirically associated with runoff onset in a time series of Sentinel-1 C-band SAR images, with detection constrained by a custom MODIS-derived snow phenology dataset. We evaluated our dataset using in situ snow pillow estimates of runoff onset from 1116 automated weather stations across the Western United States, British Columbia, Norway, and Nepal, finding a median timing difference of −2.0 d and a median absolute deviation of 10.0 d. The local agreement between our runoff onset estimates and snow pillow runoff onset estimates varies with site-specific variables like forest cover fraction, SWE, and dataset temporal resolution. We characterized these dependencies to provide empirically-derived thresholds for quality filtering as well as guidance for interpretation and use of our products. The dataset includes global annual runoff onset products for each water year, annual local temporal resolution products for each water year, and 10-year composites of median runoff onset, median absolute deviation, and local temporal resolution. This unique combination of high spatial resolution, global coverage, and decade-long temporal coverage provides unprecedented detail for the study of snowmelt runoff onset across snow-covered regions. Our snowmelt runoff onset dataset enables an improved understanding of mountain hydrological processes and informs water resource management in snow-dominated watersheds.

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Publication Details

Journal
Earth system science data
Published
2026-08-14
DOI
https://doi.org/10.5194/essd-18-5871-2026
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.00

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article

A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024

Scott Henderson, David Shean, Eric Gagliano
Earth system science data
Cryospheric studies and observations
article

A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024

Scott Henderson, David Shean, Eric Gagliano
article en

Abstract

Abstract. Snowmelt runoff onset timing represents a critical hydrological parameter, particularly in mountainous regions where seasonal snow serves as a natural reservoir for downstream water resources. Despite this importance, high-resolution observations of snowmelt runoff onset across complex terrain are limited, due to challenges from sparse in situ monitoring networks, intermittent optical remote sensing data, and coarse passive microwave remote sensing data. To address this gap, we prepared a global snowmelt runoff onset timing dataset (https://doi.org/10.5281/zenodo.16953614, Gagliano et al., 2026) for the 10-year period spanning 2015–2024, with 80 m spatial resolution and 9.5 d average temporal resolution. We created this dataset by identifying backscatter minima empirically associated with runoff onset in a time series of Sentinel-1 C-band SAR images, with detection constrained by a custom MODIS-derived snow phenology dataset. We evaluated our dataset using in situ snow pillow estimates of runoff onset from 1116 automated weather stations across the Western United States, British Columbia, Norway, and Nepal, finding a median timing difference of −2.0 d and a median absolute deviation of 10.0 d. The local agreement between our runoff onset estimates and snow pillow runoff onset estimates varies with site-specific variables like forest cover fraction, SWE, and dataset temporal resolution. We characterized these dependencies to provide empirically-derived thresholds for quality filtering as well as guidance for interpretation and use of our products. The dataset includes global annual runoff onset products for each water year, annual local temporal resolution products for each water year, and 10-year composites of median runoff onset, median absolute deviation, and local temporal resolution. This unique combination of high spatial resolution, global coverage, and decade-long temporal coverage provides unprecedented detail for the study of snowmelt runoff onset across snow-covered regions. Our snowmelt runoff onset dataset enables an improved understanding of mountain hydrological processes and informs water resource management in snow-dominated watersheds.

Earth system science dataVol. 18(8)
University of Washington (US), Earth and Space Research (US)
Bureau of Reclamation, NASA Headquarters, National Science Foundation Graduate Research Fellowship Program
Clean water and sanitation
Openalex Percentile: Top 13%
Cryospheric studies and observations
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