Temporal Stability of Soil Moisture Spatial Pattern and Subsurface Preferential Flow Pathways in the Shale Hills Catchment

Abstract

Hydropedologic approaches utilize a strategy of ''map first, then design'' and ''direction first, then velocity'' in enhancing the understanding of complex landscape processes. This is illustrated in this study by examples dealing with (i) the mapping of soils and landforms in monitoring and interpreting soil moisture dynamics and (ii) the identification of flow pathways in determining landscape water fluxes.Year-round monitoring at 77 sites in the Shale Hills Catchment in central Pennsylvania revealed a temporal stability of soil moisture spatial pattern as governed by soil types and landforms, and suggested the significance of subsurface preferential flow in rapid channeling of precipitation to stream discharge. The five soil series identified in the catchment had the following decreasing trend of moisture storage within the upper 1.1-m solum: Ernest . Blairton $ Rushtown $ Berks . Weikert. The four landform units showed a decreasing trend of soil moisture storage: Valley . Swale . Hillslope . Hilltop. The 77 monitoring sites exhibited considerable ranking stability throughout the monitoring year at multiple depths, with the subsurface's moisture ranking stability being slightly stronger than that at the surface. A slope-intercept analysis of linear regression further described the four conditions of temporal stability as related to soil moisture and hydrologic dynamics. Because of more extensively distributed deeper soils and hydrologically active swales, plus favorable subsurface lateral flow pathways and slightly higher cumulative rainfall, the south-facing slope in this V-shaped catchment was hydrologically more active than the north-facing slope in terms of draining more water at a faster rate to the stream. Approximately two-thirds of the soil horizons measured in the catchment had lateral saturated hydraulic conductivity (K sat ) values 1.5 to 142.5 higher than vertical values. Because of a moderate slope (up to 25-48%), horizontally dipping shale bedrock (11.5-17.1°), and shallow tree rooting systems (branching laterally), subsurface lateral flow was prominent in this humid forested catchment.

Profile distribution of soil–water content and its temporal stability along a 1340-m long transect on the Loess Plateau, China

“…Below 180 cm, the mean r s gradually increased to 0.979 at 300 cm. The trend of r s along the profile was in disagreement with that of other studies (Cassel et al, 2000;Lin, 2006;Guber et al, 2008;Gao and Shao, 2012a;Penna et al, 2013), where the mean r s increased with depth. The different depths of sampling in these studies may not have been able to detect precise changes in mean r s along the soil profile.…”

“…The mean SDRDs were 16.2, 9.9, 9.1, 8.8, 6.9, and 6.1% and the mean MABEs were 15.0, 8.9, 8.4, 7.9, 6.0, and 5.4% at 10, 60, 120, 180, 240, and 300 cm, respectively (Table 4). Similar results have also been reported for a desert area (Wang et al, 2013), a forest ecosystem (Lin, 2006), and a semi-arid hillslope (Gao and Shao, 2012a, b). SDRD and MABE decreased rapidly between 10 and 40 cm (Fig.…”

“…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, 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.…”

A review of advances in hydropedology for application in South Africa

“…Wilding and Lin (2006) further state that the emphasis of pedology is shifting from classification and inventory to understanding and quantifying spatially and temporal processes upon which the water cycle and ecosystems depend. The quantification of soil hydromorphology and modelling, predictions of soil and hydrologic properties and processes and data-bridging through pedotransfer functions are identified as current knowledge gaps (Lin, 2003;Lin et al, 2006;Wilding & Lin, 2006).…”

Fluctuations in the properties of forest soils in the Central European highlands (Czech Republic)

“…Forest soils develop more or less naturally and can thus form a matrix for estimates of the deviations of succession in other ecosystems (Borůvka et al 2007). Models of forest soils ecology are usually defined using a set of chemical balance equations and applied to catchments (Lin 2006). However, these models can only provide probable soil development predictions provided that there exists a constant system of response to internal or external stimuli (Cosby et al 2001).…”