Cancer and Alluvial Soil

1883 ◽  
Vol 15 (373supp) ◽  
pp. 5954-5954
Keyword(s):  
Alluvial Soil

Regeneration dynamics in an alluvial dense ash (Fraxinus excelsior L.) stand

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Tabari ◽  
N. Lust ◽  
L. Nachtergale
Keyword(s):  
Alluvial Soil ◽  
Single Species ◽  
Fraxinus Excelsior ◽  
Growth Stages ◽  
Acer Pseudoplatanus ◽  
Development Stages ◽  
Regeneration Dynamics ◽  
Broadleaved Tree Species ◽  
Succession Process ◽  
Broadleaved Tree

Broadleaves  regeneration dynamics and the succession mechanism were studied within  a    transect of 14 m x 56 m in a dense 80-year-old ash stand situated on an  alluvial soil. For this    purpose, abundance and height of all naturally regenerated species at  different development    stages were analyzed and their distribution over the juvenile and older  growth stages    determined.    The study reveals that from the main broadleaved tree species, Quercus robur and Fagus    sylvatica regeneration scarcely occur at any  growth stages. No Fraxinus excelsior regeneration,    except 1 unit, taller than sapling (1.5-4 m) can be found on this soil  type. On the contrary, Acer    pseudoplatanus represents different development  stages (seedling, sapling, thicket, small pole    and large pole) and in stand patches where an understorey is practically  lacking, its    regeneration is well developed. Results generally show that at the juvenile  and older growth    stages Acer proceeds Fraxinus and regeneration is largely  dominated by the invasive Acer. It is    expected that this succession process will continue and that Acer will overcome in the    overstorey and even gradually form an almost single-species dominating  stage. Direct    interventions are unavoidable in order to regulate the primary mixture  patterns.

scholarly journals Comparison of the Concentration of Risk Elements in Alluvial Soils Determined by pXRF In Situ, in the Laboratory, and by ICP-OES

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 938
Author(s):  
Ladislav Menšík ◽  
Lukáš Hlisnikovský ◽  
Pavel Nerušil ◽  
Eva Kunzová
Keyword(s):  
Precision Agriculture ◽  
Alluvial Soil ◽  
Coefficient Of Determination ◽  
Fast Method ◽  
Agricultural Practice ◽  
Regression Equations ◽  
Icp Oes ◽  
Risk Elements ◽  
The Relationship

The aim of the study was to compare the concentrations of risk elements (As, Cu, Mn, Ni, Pb, Zn) in alluvial soil, which were measured by a portable X-ray fluorescence analyser (pXRF) in situ (FIELD) and in the laboratory (LABORATORY). Subsequently, regression equations were developed for individual elements through the method of construction of the regression model, which compare the results of pXRF with classical laboratory analysis (ICP-OES). The accuracy of the measurement, expressed by the coefficient of determination (R2), was as follows in the case of FIELD–ICP-OES: Pb (0.96), Zn (0.92), As (0.72), Mn (0.63), Cu (0.31) and Ni (0.01). In the case of LABORATORY–ICP-OES, the coefficients had values: Pb (0.99), Zn (0.98), Cu and Mn (0.89), As (0.88), Ni (0.81). A higher dependence of the relationship was recorded between LABORATORY–ICP-OES than between FIELD–ICP-OES. An excellent relationship was recorded for the elements Pb and Zn, both for FIELD and LABORATORY (R2 higher than 0.90). The elements Cu, Mn and As have a worse tightness in the relationship; however, the results of the model have shown its applicability for common use, e.g., in agricultural practice or in monitoring the quality of the environment. Based on our results, we can say that pXRF instruments can provide highly accurate results for the concentration of risk elements in the soil in real time for some elements and meet the principle of precision agriculture: an efficient, accurate and fast method of analysis.

Simple approach to obtain ground amplification motion of surface soil deposits with a radical change of depth

2005 ◽  
Vol 42 (2) ◽  
pp. 491-498
Author(s):  
Dae-Sang Kim ◽  
Kazuo Konagai
Keyword(s):  
Seismic Design ◽  
Surface Soil ◽  
Underground Structure ◽  
Free Field ◽  
Alluvial Soil ◽  
Radical Change ◽  
Simple Approach ◽  
Clear Understanding ◽  
Underground Structures ◽  
Soil Deposits

Earthquake observations at different sites within alluvial soil deposits have demonstrated that the motion of buried underground structures closely follows that of the surrounding soil. Therefore, it is usual in a seismic design process to apply free-field ground displacements through Winkler-type soil springs to an underground structure to evaluate stress patterns induced within its structural members. Using a simplified approach, this paper provides a clear understanding of resonant horizontal ground displacement of and strain in a surface soil deposit with a radical change of depth and of where they occur.Key words: simple approach, seismic design, earthquake, resonance, underground structures.

Nitrous Oxide Flux from Soybeans Grown on Mississippi Alluvial Soil

2004 ◽  
Vol 35 (1-2) ◽  
pp. 1-8 ◽  
Author(s):  
E. V. A. Marinho ◽  
R. D. DeLaune ◽  
C. W. Lindau
Keyword(s):  
Nitrous Oxide ◽  
Alluvial Soil ◽  
Nitrous Oxide Flux ◽  
Oxide Flux

scholarly journals The response of groundwater to multiple concerning drivers and its future: a study on Birbhum District, West Bengal, India

2021 ◽  
Vol 11 (4) ◽  
Author(s):  
Niladri Das ◽  
Subhasish Sutradhar ◽  
Ranajit Ghosh ◽  
Prolay Mondal ◽  
Sadikul Islam
Keyword(s):  
Groundwater Level ◽  
Alluvial Soil ◽  
Drilling Process ◽  
Ann Model ◽  
Groundwater Levels ◽  
Agricultural Intensity ◽  
Stage Of Development ◽  
Agricultural Yield ◽  
Artificial Neural Network Ann ◽  
Geological Facies

AbstractGroundwater and its upcoming crisis are the present-day concern of the scientist. This research mainly focuses on responses of groundwater dynamicity to some important drivers, viz. agricultural yield, groundwater irrigated area, groundwater draft, landuse/landcover, and stage of development. The result of this study has been done under three sections. In the first section, the spatiality of groundwater has been discussed where it has been noticed that the western side of the district groundwater level is near the surface due to low drafting and low agricultural yield. Moreover, hard rock geology in the western part disappoints the drilling process. On the eastern part, rich alluvial soil influences high agricultural yield hence groundwater level lowering down rapidly. In the second section, the nature of groundwater levels has been analyzed through the boxplot, and cluster diagram, where boxplots have been drawn over different geological facies, which depicts groundwater is highly fluctuating in hard clay geology. For example, high agricultural intensity and high groundwater draft is the characteristic feature of hard clay geology. The dendrogram in cluster analysis represents a homogeneous groundwater level fluctuating station in three different time series. Last section deals with the future of groundwater level where an artificial neural network (ANN) model has been applied to extract the predicted groundwater level for 2030. This type of environmental analysis, such as groundwater fluctuations in relation to different sensitive parameters and the use of a machine learning model, would aid potential researchers and communities in making wise groundwater use decisions.

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