Hydraulic Conductivity and Diffusivity: Laboratory Methods

Klute, A.; Dirksen, C.

doi:10.2136/sssabookser5.1.2ed.c28

Cited by 900 publications

(352 citation statements)

References 38 publications

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“…Th e sample type was: (i) disturbed soil sample for chemical analyses prepared by a standard process to air-dried and sieved soil sample of fi ne particles (< 2 mm) (ISO 11464). SOC (soil organic carbon) was determined as C ox (total oxidized carbon in ISO/FDIS 14235), SOM (soil organic matter) was expressed by 1.724 C ox (assumption that SOM contains 58% of organically bound carbon in Nelson, Sommers 1982), fractionation of humic substances (HS) as a ratio of HA:FA (according to the method described in Richter, Hlušek 1999), pH KCl by potentiometry (according to ISO 10390), cation exchange capacity (CEC) and exchangeable cations measured by AAS-Varian240 (according to ISO 13536); (ii) undisturbed soil samples (Kopecký cylinders -volume 100 cm 3 , according to ISO 11508) for determination of physical characteristics of soil: total porosity was expressed from the values of reduced bulk density (Blake, Hartge 1986) and particle density (Danielson, Sutherland 1986), porosity system was defi ned as a sum of capillary (CP), semi-capillary (SP) and gravitational (GP) pores and calculated by the value of suction capacity (Qs) according to the standard ČSN 13040; (iii) Kopecký rings for saturated hydraulic conductivity (K sat ) described by Klute and Dirksen (1986) and determined according to the standard ČSN 721020; (iv) samples for determination of aggregate stability (weight of sample -3 kg) were airdried and sifted through nested sieves (Retch -ISO 3310-1) to particles of 1-2 mm (WSA) and 3-5 mm in size (MWD), WSA method was described by Kemper and Rosenau (1986), MWD method was described by Le Bissonais (1996).…”

Section: Methodsmentioning

confidence: 99%

Effects of afforestation on soil structure formation in two climatic regions of the Czech Republic

Podrázský¹,

Holubík²,

Vopravil³

et al. 2015

J. For. Sci.

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ABSTRACT:The aim of this study was to determine the effect of agricultural land afforestation on soil characteristics. Two sites in two regions of the Czech Republic were evaluated, at lower as well as higher submountain elevations: in the regions of the Orlické hory Mts. and Kostelec nad Černými lesy, afforested, arable and pasture lands were compared for basic chemical and physical characteristics. It was determined: pH, CEC, exchangeable nutrients, SOC, bulk density, volume density, porosity (differentiated by pore size), water conductivity and soil aggregate stability. This study demonstrated the important influence of previous land use upon soil characteristics. The characteristics of the arable horizon can persist for many years; in forests, the mineral horizons (15-30 cm) can persist within 15-30 years after afforestation. Afforestation, which caused an increase in soil porosity by decreasing reduced bulk density and increasing capillary and gravitational pores (increasing the water-holding capacity and soil air capacity), is important for maintaining the soil stability. The positive effect on infiltration and retention capacity resulted not only from the presence of a forest overstorey, but also from the presence of permanent grass cover of pasture land.

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Section: Methodsmentioning

confidence: 99%

Effects of afforestation on soil structure formation in two climatic regions of the Czech Republic

Podrázský¹,

Holubík²,

Vopravil³

et al. 2015

J. For. Sci.

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“…Transects were set in the north and east axis at 1, 5, 15, 30 m from 10 randomly chosen nodes of the grid. Soil texture was determined using the hydrometer method (Klute and Dirkens, 1986), soil bulk density was measured with the core method (Grossman and Reinsch, 2002) and soil pH and electric conductivity were measured with a pH/EC tester on a soil water extract. Organic carbon was measured using the Walkley-Black method (Walkley and Black, 1934) and the results converted to organic matter by multiplying the carbon percentage by 1.72.…”

Section: Soil Samplingmentioning

confidence: 99%

Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone

Basso

Dumont

Cammarano

et al. 2016

Science of The Total Environment

143

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Agronomic input and management practices have traditionally been applied uniformly on agricultural fields despite the presence of spatial variability of soil properties and landscape position. When spatial variability is ignored, uniform agronomic management can be both economically and environmentally inefficient. The objectives of this study were to: i) identify optimal N fertilizer rates using an integrated spatio-temporal analysis of yield and site-specific N rate response; ii) test the sensitivity of site specific N management to nitrate leaching in response to different N rates; and iii) demonstrate the environmental benefits of variable rate N fertilizer in a Nitrate Vulnerable Zone. This study was carried out on a 13.6 ha field near the Venice Lagoon, northeast Italy over four years (2005–2008). We utilized a validated crop simulation model to evaluate crop response to different N rates at specific zones in the field based on localized soil and landscape properties under rainfed conditions. The simulated rates were: 50 kg N ha− 1 applied at sowing for the entire study area and increasing fractions, ranging from 150 to 350 kg N ha− 1 applied at V6 stage. Based on the analysis of yield maps from previous harvests and soil electrical resistivity data, three management zones were defined. Two N rates were applied in each of these zones, one suggested by our simulation analysis and the other with uniform N fertilization as normally applied by the producer. N leaching was lower and net revenue was higher in the zones where variable rates of N were applied when compared to uniform N fertilization. This demonstrates the efficacy of using crop models to determine variable rates of N fertilization within a field and the application of variable rate N fertilizer to achieve higher profit and reduce nitrate leaching

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“…Schematic Position of the sampling points was presented in the studied region (Figure 2). Physical and chemical properties measurements Percent of sand, silt and clay particles was calculated with hydrometric method (Bouyoucos, 1962), bulk density of soil was calculated with sampling cylinder (Klute and Dirksen, 1986), and total porosity of soil samples was calculated with apparent and real specific mass of soil as a follow (Eq. 1):…”

Section: Study Area and Experimental Designmentioning

confidence: 99%

Evaluating inverse distance weighting and kriging methods in estimation of some physical and chemical properties of soil in Qazvin Plain

Mousavi¹,

Sarmadian²,

Dehghani³

et al. 2017

Eurasian Journal of Soil Science (Ejss)

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Article Info Received : 30.12.2016 Accepted : 03.05.2017 Today, the presence of accurate information about variability of soil properties been considered more than ever to apply this information in economic modeling, environmental predictions, accurate farming and natural resources management. The present research was conducted in some lands of Qazvin plain to study variability of some chemical and physical properties of soil by sampling 62 observational points in depth of 20 cm above soil surface. Initial statistical study of data indicated that the studied properties follow normal distribution in the region. Spatial variations of the studied properties showed that spherical model was the best fitted model to semivariogramin other properties than silt percent and bulk densityand total porosity. The highest radius for the studied properties was 21100 m related to bulk density, total porosity and electric conductivity and pH. Spatial dependence class was observed medium to strong in all physcial and chemcial properties. To validate intrapolation methods, three indices of evaluation, R 2 , MBE, MAE which indicate accuracy of each of the intrapolation methods were used and results showed that the studied properties had spatial structure, their impact range had good variability and kriging estimator better can show variability of the studied properties in the region in comparison to IDW method. At the end, considering the best interpolation method, spatial variability map of each of the properties was prepared in ArcGIS software.

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Hydraulic Conductivity and Diffusivity: Laboratory Methods

Cited by 900 publications

References 38 publications

Effects of afforestation on soil structure formation in two climatic regions of the Czech Republic

Effects of afforestation on soil structure formation in two climatic regions of the Czech Republic

Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone

Evaluating inverse distance weighting and kriging methods in estimation of some physical and chemical properties of soil in Qazvin Plain

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