A Multilayer Soil Moisture Dataset Based on the Gravimetric Method in China and Its Characteristics

Abstract

Based on the gravimetric-technique-measured soil relative wetness and the observed soil characteristic parameters from 1992 to 2013 in China, this study derives a user-convenient monthly volumetric soil moisture (SM) dataset from 732 stations for five soil layers (10, 20, 50, 70, and 100 cm). The temporal–spatial variations in SM and its relationship with precipitation (Pr) in different subregions are then explored. The magnitude of SM is relatively large in south China and is low in northwest China, and it generally increases with soil depth in each region. The maximum SM appears in spring and/or autumn and the minimum in summer, and the SM seasonality does not vary as distinctly as that of Pr. For the top three soil layers (10-, 20-, and 50-cm levels), the linear trend analysis indicates an overall increasing SM tendency, and the mean trends (averaged across stations with trends passing a 95% significance level test) are 9.35 × 10−7, 7.37 × 10−3, and 2.45 × 10−3 cm3 cm−3 yr−1, respectively. SM memory depends on the soil depth and regions, and it has longer retention time in the deeper layers. Furthermore, the correlation between SM and antecedent Pr varies with soil depth and lag time. The antecedent Pr anomaly (1 or 2 months in advance) can be used to some extent as a surrogate SM anomaly in most regions except for in arid regions. This result is further demonstrated by the relationships between the SM anomaly and the standardized precipitation index. The current SM dataset can be used in various applications, such as validating satellite-retrieved products and model outputs.

Regional climate model simulation of soil moisture and its application in drought reconstruction across China from 1911 to 2010

“…Furthermore, as noted in the introduction section, various drought indices have been constructed to emphasize different types of drought and do not necessarily show the same properties for the same regions. A SM drought event might not be consistent with a precipitation‐based meteorological drought event occurring in arid regions in China (Wang and Shi, 2019). The mainland China covers different climate zones and its climate presents distinctly regional characteristics.…”

“…Wang and Shi (2019) (hereafter referred as to WS2019) processed and analysed in situ measured SM dataset which was derived from the gravimetric method in China for the period of 1992–2013. This dataset includes the volumetric SM records for up to 732 stations in five soil layers (Figure 1b).…”

“…Due to highly spatial heterogeneity and point‐versus‐grid cell mismatching, the comparison of point SM measurements and modelled grid box averages is always challenging. To partly avoid this problem, two approaches are adopted: (a) we use the average from observations at all stations in China (rather than focusing on an individual station) to compare the mean modelled values at all corresponding station locations (e.g., Wang and Zeng, 2011); and (b) we use the average from stations over six subregions (Wang and Shi, 2019) to compare the regional mean of model simulations (e.g., Xia et al ., 2014). For method 1, three modelled SM products (WRF‐ERA20C, WRF‐20CR, and WRF‐ENS) from the original grid points are firstly interpolated to the station locations (Figure 1b) using the inverse distance weighted algorithm.…”

“…This is mainly attributable to an absence of reliable long‐term SM datasets. SM is usually obtained directly through in situ measurement, satellite observations, and/or numerical model simulations (Wang and Zeng, 2011; Yang, 2013; Wang and Shi, 2019). In the past 40 years, remotely‐sensed SM datasets have been widely used in drought investigations due to their extensive spatial coverage and continuous temporal extent (e.g., Rhee et al ., 2010; Liu et al ., 2019), but they only represent moisture conditions within the upper 2–5 cm soil layers and are only reliable for bare and sparsely vegetated regions (Liu et al ., 2011).…”

“…Since the soil water holding capacity and soil texture differ from region to region (e.g., Shangguan et al ., 2013), the magnitudes of SM (in volumetric form) is heterogeneous across space (Wang and Shi, 2019). Wang et al .…”