General and Spatial Variability of Solonetzic Soils in North Central Alberta

Carter, M. R.; Pearen, J. R.

doi:10.4141/cjss85-016

Cited by 13 publications

(6 citation statements)

References 15 publications

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“…Only the participating sites were able to support brush vegetation. Ultimately, the fact that Solonetzic soils are often found in association with Chernozemic soils over small spatial scales (Miller & Brierley, ; Pennock et al, ) results in a particularly heterogeneous landscape (Carter & Pearen, ; Pennock et al, ; Sandoval & Reichman, ). For instance, Carter and Pearen () found that some physical properties of Solonetzic soils, such as the thickness of the A horizon, exhibit little spatial dependence at distances greater than 5 m. Similarly, Sandoval and Reichman () report that infiltration rates into Solonetzic soils are also highly variable within short distances.…”

Section: Discussionmentioning

confidence: 99%

“…Ultimately, the fact that Solonetzic soils are often found in association with Chernozemic soils over small spatial scales (Miller & Brierley, 2011;Pennock et al, 1999) results in a particularly heterogeneous landscape (Carter & Pearen, 1985;Pennock et al, 1999;Sandoval & Reichman, 1971). For instance, Carter and Pearen (1985) found that some physical properties of Solonetzic soils, such as the thickness of the A horizon, exhibit little spatial dependence at Figure 10. Relationship between spatial variability and mean water content for the different depths and profile average fitted with a quadratic function to illustrate the trend.…”

Section: Soil Propertiesmentioning

confidence: 99%

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How Spatial Patterns of Soil Moisture Dynamics Can Explain Field‐Scale Soil Moisture Variability: Observations From a Sodic Landscape

Peterson

Helgason

Ireson

2019

Water Resources Research

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Root‐zone soil moisture (0–110 cm) was monitored at 21 sites within a cold‐region semiarid prairie grazing pasture over multiple growing seasons. There were large differences in the moisture dynamics for different sites, which was related to local‐scale impacts of sodium‐induced clay dispersion. Sites with high exchangeable sodium percentages, indicative of sodic soils, were characterized by small changes in soil moisture storage. The sites with the largest soil moisture changes had negligible exchangeable sodium percentage. We used this difference to divide the area into sites that participate in the field‐scale water balance and those that do not. As a result of this heterogeneity, a unique soil moisture variability‐mean relationship was observed; the spatial variability of root‐zone soil moisture was lowest during intermediate wetness conditions and highest for wet and dry conditions. Furthermore, the shape of the variability‐mean relationship depended on the depth over which soil moisture was integrated. The persistent differences in soil moisture dynamics were also responsible for the presence of two distinct spatial patterns of root‐zone soil moisture, representing early and late growing season (i.e., wet and dry conditions). The participating versus nonparticipating framework may be applicable broadly to sodic soils and to other soil types and has practical implications for parameterizing the water balance in hydrological models and for designing representative soil moisture monitoring networks in such environments.

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Section: Discussionmentioning

confidence: 99%

Section: Soil Propertiesmentioning

confidence: 99%

How Spatial Patterns of Soil Moisture Dynamics Can Explain Field‐Scale Soil Moisture Variability: Observations From a Sodic Landscape

Peterson

Helgason

Ireson

2019

Water Resources Research

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“…), several areas in Central Canada (Buckland et al . ; Carter & Pearen ), the Songnen Plains in Northeastern China (Shvartsev & Wang ; Yang & Li ; Luo et al . ), and Southern Sudan (De Vivo et al ., ) (Figure a, Numbers 1 to 9).…”

Section: Global Distributionmentioning

confidence: 99%

“…The percentages of alkaline soils (pH ≥ 9 in the top meter) across 11 ranges of climatic water balance (PPT:PET at 0·2 steps) are shown for hyperplains (slope ≤ 0·05% and area ≥ 2,000 km 2 ) and for all other topographic situations. [Colour figure can be viewed at wileyonlinelibrary.com] Caspian basin (Khitrov 2005), eastern Hungary (Molnár & Borhidi 2003;Tóth & Rajkai 1994), the Pampas and Chaco in Central Argentina and western Paraguay (Cisneros et al 1999;Lavado & Alconada 1994;Miretzky et al 2000), the Brazilian Pantanal (Furquim et al 2010), the driest section of the Venezuelan Llanos (Guerrero-Alves et al 2004), several areas in Central Canada (Buckland et al 2002;Carter & Pearen 1985), the Songnen Plains in Northeastern China (Shvartsev & Wang 2006;Yang & Li 2003;Luo et al 2011), andSouthern Sudan (De Vivo et al, 1981) (Figure 3a, Numbers 1 to 9). In Southern Africa, the closed-basins of the Etosha (Namibia) and Okavango (Botswana) hyperplains host very alkaline soils and salt deposits (Buch & Rose 1996;McCarthy 2006) (Figure 3a, Numbers 10 and 11).…”

Section: Global Distributionmentioning

confidence: 99%

On the Fundamental Causes of High Environmental Alkalinity (pH ≥ 9): An Assessment of Its Drivers and Global Distribution

et al. 2017

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Very alkaline environments exceeding calcite buffering are globally rare but conspicuous in many sedimentary plains of the World. While the deleterious effects of high alkalinity on soils are well understood, less agreement exists on its causes. We revise these causes to understand these exceptional environments and explain the pervasiveness of calcite buffering elsewhere. We argue that the injection of respired CO2 into stagnant hydrological systems subject to evaporative discharge is the key context for high alkalinization. The evolution of evaporites in nature reaches highly alkaline stages only when excess of (bi)carbonate with respect to divalent cations occurs. In most dry landscapes, evaporating groundwater solutions lose this condition as respired inorganic carbon (recharge zone supply) equilibrates with divalent cations from rocks (whole hydro‐trajectory supply). Groundwater in stagnant landscapes avoids this limitation owing to short/shallow trajectories sustaining (bi)carbonate excess until evaporative discharge zones are reached. Flat sedimentary landscapes that are (i) wet enough to develop stagnation and have shallow water tables but (ii) sufficiently dry to expose them to evaporative concentration should host very alkaline soils. This is confirmed with >9,000 soil profiles from the global WISE database, which shows that profiles with pH ≥ 9 in the top meter are 2·7% globally but 18% in areas with low slope (<0·05%, 25‐km radius, SRTM digital elevation model (SRTM DEM)) and semiarid–subhumid climate (annual precipitation to potential evapotranspiration ratio = 0·2–1, CRU database). Understanding how climate and vegetation change as well as irrigation practices influence hydrological stagnation and evaporative concentration may provide the key to manage very alkaline environments. Copyright © 2017 John Wiley & Sons, Ltd.

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“…The standard deviation and, hence, the coefficient of variation does not incorporate spatial and/or temporal information and therefore doesn't provide a representation of the nature of the spatial and/or temporal behaviour of a given soil property. It is considered as an indicator of global variability as opposed to local variability (Carter & Pearen, 1985), the latter is identified using correlogram, covariance function, or variogram which will be presented later in this chapter (sections 3.3 to 3.6).…”

Section: Coefficient Of Variationmentioning

confidence: 99%