ArticleScientific data2026
MACH: A Multi-Attribute Catchment Hydrometeorological dataset.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- MACH: A Multi-Attribute Catchment Hydrometeorological dataset.Scientific data · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MACH is a comprehensive hydrometeorological dataset spanning 1,014 watersheds across the United States. It unifies, extends, and enhances existing large-sample hydrology resources by integrating daily meteorological forcings and streamflow observations at the basin scale over a 44-year period (1980-2023). For 395 catchments, MACH also includes records dating back to 1948, extending the hydrologic analyses period to 75-years. MACH provides a rich set of watershed attributes, encompassing topography, soils, geology, land cover, anthropogenic influences, and a wide range of hydroclimatic indices. This comprehensive structure supports investigations of climate-runoff interactions, hydrologic sensitivity, model calibration, and long-term watershed change across diverse spatial and temporal gradients. MACH serves as a flexible, high-resolution dataset for advancing large-sample hydrology, hydroclimatic assessment, and data-driven water science.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.