Abstract
<jats:p>Abstract. Soil water content (SWC) is a key state variable in land-surface hydrological processes and the primary water source for vegetation, particularly in arid and semi-arid regions. However, long-term, multi-scale in situ measurements of deep SWC remain insufficient on the Loess Plateau of China (LPC), the world’s largest and deepest loess deposit area. To address this gap, the Loess-Obs network, a long-term multi-scale SWC observation system, was established on the LPC about 20 years ago, covering five spatial scales including plot, hillslope, local-landscape, plateau-wide transect, and regional-survey scale. Here, we present a long-term SWC profile dataset derived from the Loess-Obs network, including continuous measurements (2004–2019) of four plots with distinct land uses, two hillslope transects of 300 m and 270 m (2004–2016), a 1340 m local-landscape transect spanning multiple hillslopes (2012–2013), an 860 km plateau-wide transect (2013–2016), and a regional survey conducted in 2015. Volumetric SWC in the 0–5 m layer was measured at multiple depths using calibrated neutron probes (sampling frequency: weekly to monthly). We detail the network design, field protocols, experimental setup, sampling strategies, calibration equations, maintenance procedures, and quality control measures, alongside associated environmental datasets (land use, soil properties, topography, meteorology) to support extended applications. Key findings include: (1) exotic shrubs (Caragana korshinskii) and grasses (Medicago sativa) accelerated deep SWC depletion compared to cropland and naturally restored fallow land; (2) temporal variability of SWC decreased, while its spatial variability increased with soil depth; (3) time-stable sampling sites could be effectively used to characterize mean SWC of different soil layers, with accuracy improving with depth; (4) regional soil water storage decreased from southeast to northwest; (5) the discrepancy between SWC products and Loess-Obs observations generally increased with depth, reflecting the scarcity of deep in situ observations in model development. This dataset is valuable for validating SWC products, developing upscaling methods, and understanding deep soil hydrological responses to land use and climate change. It is publicly accessible at https://zenodo.org/records/21859310.</jats:p>