INVESTIGATING THE LINK BETWEEN HYDRAULIC CONDUCTIVITY AND SOIL CHARACTERISTICS OF PERMAFROST CORES FOR THE NEXT GENERATION ECOSYSTEM EXPERIMENT (NGEE)-ARCTIC

2016 ◽  
Author(s):  
Robin D. López ◽  
◽  
Yuxin Wu ◽  
Craig Ulrich ◽  
Chunwei Nick Chou ◽  
...  
Author(s):  
Jan Sevink ◽  
Sander Koopman

Abstract The area ‘Het Gooi’ in the Netherlands is part of a Pleistocene ice-pushed ridge system that partially drowned during the Holocene upon sea level and associated groundwater rise. As a result, the ridge system was gradually encroached by peat. From the late Middle Ages onward, man reclaimed the peatlands surrounding Het Gooi, heavily reducing their extension and lowering the regional groundwater level by increasingly intensive drainage. Based on historical and archaeological arguments, several authors assume that the Holocene peat cover in the border zones of ‘Het Gooi’ formed the extension of large raised peat bogs that formed further to the west and east, respectively. They presume that in the late Middle Ages these extensions reached ‘upslope’ to a maximum altitude of 3 m + NAP (Dutch Ordnance Datum – approximating mean sea level). However, the original extension is difficult to reconstruct, as this peat has disappeared as a result of its exploitation and oxidation, if having been present at all. In this study, the maximum extension of the Holocene peat cover on the ice-pushed ridge system was reconstructed based on soil characteristics. Used soil characteristics concerned the presence of iron coatings around sand grains and the upper boundary of gleyic features, because these are indicators for the mean highest groundwater level (MHG). For peat to form, this MHG needs to be at or just above the ground surface for most of the year. Based on study of a number of soil transects, we reconstructed to what maximum altitude peat encroachment may have occurred. This ‘maximum extension’ can alternatively be described as the maximum altitude of the bottom of the peat onlapping the ridge system. In the western border zone, this peat cover was found to have reached to c. NAP or just above, near Hilversum. No indications were found for the occurrence of raised bogs. We conclude that the phreatic groundwater level in this zone was controlled by the sea level and associated lake levels (Naardermeer and Horstermeer), a dominant role being played by the shallow presence of Pleistocene formations with a high hydraulic conductivity. In the eastern border zone, altitudes were more variable and in places reached 2 m + NAP. Peat at this higher elevation probably formed under the influence of a higher phreatic groundwater level, induced by the presence of a clayey Eemian fill with low hydraulic conductivity in the adjacent glacial basin (the Eem valley). This study demonstrates the value of detailed soil transect studies for palaeogeographical reconstructions of the former Holocene peat cover in Pleistocene landscapes of NW Europe. It also provides independent data for validation of geohydrological models for such landscapes.


2015 ◽  
Vol 725-726 ◽  
pp. 355-360 ◽  
Author(s):  
Vitaly Terleev ◽  
Vladimir Badenko ◽  
Inna Guseva ◽  
Wilfried Mirschel

New theoretical justification for the function of soil differential moisture capacity (dependence of the relative water volume content on the capillary pressure) and its antiderivative is presented. New method is based on the concept of capillarity and the lognormal distribution of the effective radii of pores. Relative hydraulic conductivity of soil is calculated with usage of these functions and Mualem's approach. Hydrophysical parameters have been interpreted and evaluated on the base of some physical and statistical soil characteristics. Also the approximation for functions of water-retention capacity and relative hydraulic conductivity of soil has been proposed.


Soil Research ◽  
1992 ◽  
Vol 30 (5) ◽  
pp. 751 ◽  
Author(s):  
AR Astaraei ◽  
RPS Chauhan

A laboratory study on loamy soil (19.6% clay) with different quality waters varying in Ca : Mg ratio (1 : 1, 1 : 2, 1 : 4, 1 : 6, 1 : 8) at two levels each of salinity (6 and 12 dSm-1) and SAR (10 and 50) was carried out. Exchangeable sodium (ES), exchangeable sodium percentage (ESP), Na: (Ca+Mg) ratio and degree of dispersed clay in soil increased with increasing Mg concentration at both the levels of EC(iw) and SAR(iw). The percentage of dispersed clay was more with increasing Mg concentration at higher SAR(iw) with a lower level of EC(iw), while the reverse trend was observed with hydraulic conductivity of soil. The Ca : Mg ratio in the exchange complex decreased with increasing Mg concentration, EC(iw) and SAR(iw). Further Mg concentration in the exchange complex increased with Mg in water and EC(iw) and decreased with the rise in SAR(iw). The multiple correlations between different water parameters and soil characteristics, namely ESP, degree of dispersion and hydraulic conductivity, were calculated and regression equations were developed. The relative contributions of water parameters to ESP, degree of dispersion and hydraulic conductivity of soil were in the order SAR(iw) > EC(iw) > Ca : Mg; EC(iw) > Ca : Mg > SAR(iw), EC(iw) > SAR(iw) > Ca : Mg, respectively.


2020 ◽  
Author(s):  
Alejandro Cueva ◽  
Daniel R. Hirmas ◽  
Attila Nemes ◽  
Pamela L. Sullivan

<p>Pedotransfer functions (PTFs) are widely used tools to predict soil properties across different spatial scales and are commonly built using regression-based techniques (e.g., multiple linear regression or regression trees) and, more recently, machine learning methods (e.g., artificial neural networks). In these techniques<em>,</em> soil material arising from different soil horizons are treated as independent samples despite the depth dependency that exists for horizons within individual pedons. Here we propose a new approach to build PTFs that takes into account the depth dependency of saturated hydraulic conductivity (<em>K<sub>sat</sub></em>) and refer to this type of depth-dependent PTFs as a “pedontranfer” function (PnTF). Slope (<em>β<sub>1</sub></em>) and intercept (<em>β<sub>0</sub></em>) parameters describing the relationship of log-scale <em>K<sub>sat</sub></em> with soil horizon depth were fit to pedons selected from the Pedogenic and Environmental DataSet (PEDS). The intercept parameter can be interpreted as the <em>K<sub>sa</sub><sub>t</sub></em> at a 0 cm depth (i.e., <em>K<sub>sa</sub><sub>t</sub></em> at the soil surface) and <em>β<sub>1</sub></em> as the rate of change of <em>K<sub>sa</sub><sub>t</sub></em> with respect to depth. In order to build the PnTF, we used field-based pedon information from PEDS, encompassing approximately 2,000 pedons and >13,000 soil horizons across the United States and estimated <em>K<sub>sat</sub></em> using a generalized Kozeny-Carman equation. Our results show a strong negative linear relationship between <em>β<sub>1</sub></em> and <em>β<sub>0</sub></em> (<em>r<sup>2</sup></em> = 0.80; <em>P</em> < 0.01). When we predicted the fitted line of the linear relationship between <em>β<sub>1</sub></em> and <em>β<sub>0</sub></em> using a multiple linear regression with different soil and climatological variables we found a significant (<em>P</em> < 0.01) and direct relationship, with relatively good agreement (<em>R<sup>2</sup></em> = 0.38). Our results suggest that the PnTF approach represents a step forward in the development of the next generation of PTFs, although further research is needed to improve its precision and accuracy. We believe that PnTFs, in principle, have significant advantages over PTFs that should be of interest to the community of developers and users of Earth system and community land models. For example, soil <em>K<sub>sa</sub></em><sub>t</sub> at depth may be predicted from knowledge only of the surface <em>K<sub>sa</sub><sub>t</sub></em> since <em>β<sub>1</sub></em> can be predicted from <em>β<sub>0</sub></em>. Future work should incorporate other soil databases in order to account for systematic biases of the different methods to measure or estimate <em>K<sub>sa</sub><sub>t</sub></em>.</p>


2004 ◽  
Vol 171 (4S) ◽  
pp. 389-389
Author(s):  
Manoj Monga ◽  
Ramakrishna Venkatesh ◽  
Sara Best ◽  
Caroline D. Ames ◽  
Courtney Lee ◽  
...  

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