scholarly journals Consolidation Inverse Analysis Considering Spatial Variability and Non-Linearity of Soil Parameters

2002 ◽  
Vol 42 (3) ◽  
pp. 45-61 ◽  
Author(s):  
Shin-ichi Nishimura ◽  
Kiyoshi Shimada ◽  
Hiroaki Fujii
Keyword(s):  
Spatial Variability ◽  
Inverse Analysis ◽  
Soil Parameters

scholarly journals Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

2017 ◽  
Vol 21 (8) ◽  
pp. 513-518 ◽  
Author(s):  
Alberto C. de C. Bernardi ◽  
Célia R. Grego ◽  
Ricardo G. Andrade ◽  
Ladislau M. Rabello ◽  
Ricardo Y. Inamasu
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Exchange Capacity ◽  
Soil Parameters ◽  
Forage Production ◽  
Soil P ◽  
Livestock System

ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

scholarly journals Identification of soil parameters by inverse analysis

2001 ◽  
Vol 28 (2) ◽  
pp. 129-144 ◽  
Author(s):  
R. Zentar ◽  
P.Y. Hicher ◽  
G. Moulin
Keyword(s):  
Inverse Analysis ◽  
Soil Parameters

Spatial variability of N 2 O emissions and soil parameters of an arable silt loam - a field study

1999 ◽  
Vol 28 (4) ◽  
pp. 403-406 ◽  
Author(s):  
J. Clemens ◽  
M. P. Schillinger ◽  
H. Goldbach ◽  
B. Huwe
Keyword(s):  
Spatial Variability ◽  
Field Study ◽  
Soil Parameters ◽  
Silt Loam

scholarly journals Spatial prediction of soil acidity and nutrients for site-specific soil management in Bedele district, Southwestern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Gedefa Sori ◽  
Birhanu Iticha ◽  
Chalsissa Takele
Keyword(s):  
Spatial Variability ◽  
Soil Ph ◽  
Crop Production ◽  
Soil Acidity ◽  
Agricultural Land ◽  
Spatial Prediction ◽  
Soil Parameters ◽  
Site Specific ◽  
Southwestern Ethiopia ◽  
Strong Acidity

Abstract Background Understanding the spatial variability of soil properties is useful to tailor site-specific agricultural inputs to enhance crop production on a sustainable basis. This study was aimed to assess and map the spatial patterns of soil acidity and nutrients using geostatistical methods and support site-specific lime and fertilizer recommendations in Bedele district, Southwestern Ethiopia. Methods Soil samples were collected from agricultural land at a depth of 20 cm using grid sampling technique. The semivariogram analysis was performed for accurate spatial prediction and the kriging technique was used for interpolation of soil parameters. Results Soil pH varied between 4.5 and 6.8. Soil organic carbon (OC) content ranged from 0.3 to 5.6% and the mean soil OC density was 0.81 kg m−2. Available phosphorus (AvP) ranged from 0.8 to 38.6 mg kg−1 and nearly 80.23% of the soils exhibited very low to low AvP that could be due to fixation by strong acidity. Soils of the study area exhibited very high exchangeable potassium (K), but very low exchangeable calcium (Ca) and magnesium (Mg). The potassium to magnesium ratio (K:Mg) ranged from 0.2:1 to 10.9:1, while the values of calcium to magnesium ratio (Ca:Mg) varied between 0.3 and 3.4. Among the soil parameters, exchangeable Ca (CV = 54%) and K:Mg ratio (CV = 57.62%) were more variable than other soil parameters. Spatial variability was lowest for soil pH (CV = 10%). Conclusions Major portions of the study site were affected by strong acidity (pH ≤ 5.5). Accordingly, about 89% of the soils require lime that varied between 0.09 and 3.6 tons ha−1. In addition to soil acidity, deficiency of available P, Ca, and Mg were the major liming factors affecting crop production in the study area. Digital soil mapping was used to show the spatial variability of soil acidity and nutrients across agricultural land and applied for efficient lime and nutrients advisory works.

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