Profile distribution of soil–water content and its temporal stability along a 1340-m long transect on the Loess Plateau, China
Introduction
Soil–water content (SWC) is broadly acknowledged as an important control of many geomorphic and hydrological processes (Penna et al., 2013). It is also the principal limiting factor for vegetational restoration (Hu et al., 2009) and agricultural production (Tallon and Si, 2004) in semi-arid and arid regions. SWC can regulate the subsurface flow and migration of pollutants and chemicals to environmentally sensitive areas (Biswas and Si, 2011a). Less is known about deep layers than about surface SWC due to the difficulty of acquiring data. The relationships of SWC at different depths are also unclear. Obtaining information on soil–water dynamics at various depths is thus necessary.
SWC is variable in both space and time across different scales (Manfreda and Rodriguez-Iturbe, 2006, Famiglietti et al., 2008). The characteristics of the spatial variability of SWC have been widely studied in various ecosystems and at various scales (Wang et al., 2013). Despite the variability of SWC, repeated surveys can often identify certain sites, which are relatively stable over time and can be served as representative locations for an area of interest. The concept of temporal stability of spatial patterns of SWC was first introduced by Vachaud et al. (1985), who defined it as “the time-invariant association between spatial location and classical statistical parameters of a given soil property”. The temporal stability of SWC has been investigated for different soil depths (Zhang and Shao, 2013, Heathman et al., 2009), land uses (Hu et al., 2010a, Williams et al., 2009, Lin, 2006), scales (Martínez-Fernández and Ceballos, 2003, Jia and Shao, 2013, Hu et al., 2010b, Gao et al., 2011), regions (Biswas and Si, 2011b, Jia et al., 2013a, Zhang and Shao, 2013), measurement periods (Guber et al., 2008, de Rosnay et al., 2009, Zhao et al., 2010, Biswas and Si, 2011b, Liu and Shao, 2014), and measuring instruments (Jacobs et al., 2004, Gao and Shao, 2012b, Wang et al., 2013, Penna et al., 2013). The characteristics of the temporal stability of SWC vary with depth, but little is known about the precise changes of SWC and its temporal stability in soil profiles due to coarse division of previous soil profiling. Furthermore, the findings of some studies conflict. For example, Gao and Shao (2012a) reported that the temporal stability of soil–water storage increased with depths at 0–1, 1–2, and 2–3 m. In contrast, Hu et al. (2009) observed that the temporal stability of SWC was greater at 0.2 m than at 0.4, 0.6, and 0.8 m. Differences in depth of sampling may thus have an impact on the determination of temporal stability and may lead to conflicting information. Precise changes of SWC and its temporal stability may be observed by carefully sectioning the soil profile. In the present study, soil profiles were sampled at 20-cm intervals for capturing the characteristics of temporal stability.
Some studies have proposed that mean SWC can be estimated directly by identifying representative locations based on certain principles (Hu et al., 2010a, Gao and Shao, 2012a, Jia et al., 2013a), which may not always apply. As a consequence, many studies have investigated alternative approaches by attempting to find representative locations using other properties that can affect SWC, but the identification of representative locations remains inconsistent. For example, da Silva et al. (2001) observed that organic-carbon and clay contents could serve as better explanatory variables than topographic variables. In contrast, Gómez-Plaza et al. (2000) found that vegetation and topography rather than soil properties were more likely to be the primary factors affecting the temporal stability of SWC. Jacobs et al. (2004) concluded that sampling locations with intermediate to moderately high clay contents tended to generate the most temporal stability, and Mohanty and Skaggs (2001) reported that sandy loam had better temporal stability than silty loam. Liu and Shao (2014) found that many of the most temporally stable locations were near the centres of the plots established on a hillslope, and Tallon and Si (2004) observed that temporally stable locations had weak relationships with topographic properties. Grayson and Western (1998) thus proposed an indirect method by introducing a constant offset. This method has been used in other studies (Gao et al., 2011, Wang et al., 2013), but the accuracy of prediction of both the direct and indirect methods along soil profiles is unknown and requires evaluation.
The temporal stability of SWC relies on many factors such as soil properties, vegetation, and topography (Vachaud et al., 1985, Hu et al., 2010b, Zhao et al., 2010, Jia et al., 2013a, Jia and Shao, 2013). Temporal stability is also associated with the status of the SWC (Martínez-Fernández and Ceballos, 2003, Gao and Shao, 2012a, Jia et al., 2013b). Considerable debate, however, remains about the effect of SWC status on temporal stability. Martínez-Fernández and Ceballos (2003) found that the temporal stability of SWC was more pronounced under dry than under wet conditions. In contrast, Gómez-Plaza et al. (2000) observed that SWC was less stable during dry periods than during humid periods when the vegetation consumed more water. Gao et al. (2011) indicated that SWC was not very temporally stable during the transition period from dry to wet. Furthermore, little attention has been focused on the changes at locations representing different soil-moisture conditions along soil profiles. The ability of single locations to represent several soil depths with different moisture status is unknown. Confirmation of the dependence of the characteristics of temporal stability on soil-moisture conditions is thus necessary.
We analysed the characteristics of SWC and its temporal stability at 15 depths along a transect on the Loess Plateau, China, to: (1) assess the depth persistence of spatial patterns of SWC within the soil profiles, (2) describe the precise changes of temporal stability of SWC along the profiles, (3) evaluate both the direct and indirect methods for estimating mean SWC at different depths, and (4) investigate the relationships between temporal stability and sampling location under different soil-moisture conditions.
Section snippets
Study area and experimental design
The experiment was conducted in the Liudaogou catchment (110°21′–110°23′E and 38°46′–38°51′N) of Shenmu County in Shaanxi Province, China (Fig. 1). The study area is in a transitional belt with severe soil and wind erosion. The Liudaogou catchment has an area of 6.89 km2 and is characterised by deep gullies and undulating loessial slopes. The elevation ranges from 1056 to 1130 m a.s.l. The area has a semi-arid continental climate with a mean annual temperature of 8.4 °C and a mean annual
Temporal-spatial dynamics of SWC within the soil profile
The temporal evolution of spatial mean SWC for six selected soil depths is presented in Fig. 2. The spatial mean SWCs over time were 8.7, 15.4, 14.0, 13.6, 14.1, and 14.7% at depths of 10, 60, 120, 180, 240, and 300 cm, respectively. Spatial mean SWC was significantly lower (P < 0.05) at 10 cm and was significantly higher (P < 0.05) at 60 cm than at the other depths (Table 1). Spatial mean SWC did not differ significantly (P < 0.05) among the 120, 180, 240, and 300 cm depths. Gao and Shao (2012a),
Conclusions
This study analysed the changing characteristics of SWC and its temporal stability in soil profile. Based on the SWC datasets of 135 locations on 18 observing dates, the following conclusions can be summarized:
The SDT and CVT of SWC decreased with soil depth. The SDS of SWC decreased with depth, but the CVS first decreased and then increased below 60 cm. Significant depth persistence of the spatial pattern of SWC was observed among the various depths, and the persistence decreased with
Acknowledgement
This study was financially supported by the National Natural Science Foundation of China (Nos. 51179180 and 41390463).
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2022, CatenaCitation Excerpt :In NG, the proportional contributions of soil water in each soil layer were approximative. In the Loess Plateau, soil water was the crucial water source for vegetation growth (Hu et al.,2009; Li et al., 2016), originally derived from precipitation. The rainfall regimes have direct impact on soil water and isotopic values (Dai et al., 2015; Sun et al., 2019).