A dataset of soil water measurements at multiple scales and depths on China's Loess Plateau

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 scarce on the Loess Plateau of China (LPC), the world’s largest and thickest loess deposit. To address this gap, the Loess-Obs network was established on the LPC in 2004 to measure deep SWC at five nested scales. Spatial extent and record length trade off against each other: the longest records come from the smallest areas, with 124 campaigns at four plots under distinct land uses (2004–2019) and 112 campaigns on hillslope HB (270 m, 2004–2016). The wider components cover shorter periods: 23 campaigns on hillslope HA (300 m, 2008–2011), 18 along a 1.34 km local-landscape transect (2012–2013), 18 along an 860 km plateau-wide transect (2013–2016) and one survey of 243 points across the plateau in 2015. The measurements are periodic rather than continuous, at intervals that were not fixed and mainly in the growing season. Volumetric SWC was measured with calibrated neutron probes over profiles of 3.0 m on the hillslopes and the local-landscape transect, 4.0 m at the plots and 5.0 m at the two widest scales, read in 16–25 layers. The scheme also changed over time: the number of layers read on hillslope HB was reduced in March 2013. The three calibration curves give R2 of 0.90–0.93 and root mean square residuals of 1.8–2.4 % by volume, and each curve predicts the access tubes withheld from its fit with little further loss of accuracy. The standard uncertainty of a published value is 0.7 % by volume for a plot mean, which averages eleven access tubes, and 1.8–2.8 % for the single-tube values of the other scales. Screening against the measured saturated water content flagged one value and removed none. Land use, soil properties, topography and meteorological records accompany the SWC data. The dataset supports the validation of SWC products, the development of upscaling methods, and the analysis of deep soil hydrological responses to land use and climate change.