scholarly journals Spatial Variability and Geostatistical Analysis of Soil Properties in the Diversified Cropping Regions of Bangladesh Using Geographic Information System Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Md. Zulfikar Khan ◽  
Md. Rafikul Islam ◽  
Ahmed Bin Abdus Salam ◽  
Tama Ray
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Nutrient Management ◽  
Sampling Site ◽  
Geostatistical Analysis ◽  
Kriging Interpolation ◽  
Total N ◽  
Study Region ◽  
Site Specific ◽  
Classical Statistics

Mapping of soil properties is an important operation as it plays an important role in the knowledge about soil properties and how it can be used sustainably. The study was carried out in a local government area in Bangladesh in order to map out some soil properties and assess their variability within the area. From the study area, a total of 92 soil samples (0–20 cm) were collected from different cropping patterns at an interval of 2.2 × 2.2 km2 on a regular grid design. A portable global positioning system (GPS) was used to collect coordinates of each sampling site. Then, soil properties, that is, pH, electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (Total N), and soil available nutrients (P, K, and S) were measured in the laboratory. After the normalization of data, classical statistics were used to describe the soil properties, and geostatistical analysis was used to illustrate the spatial variability of the soil properties by using kriging interpolation techniques in a GIS environment. Results show that the spatial distribution and spatial dependency level of soil properties can be different even within the small or large scale. According to cross-validation results, for most soil properties, the kriging interpolation method provided the least interpolation error. The generated maps of soil properties that indicate soil nutrient status over the study region could be helpful for farmers and decision-makers to enhance site-specific nutrient management. Also, these prototype maps would be helpful for future nutrient and fertilizer applications management, including a site-specific condition to not only reduce the cost of input management but also prevent any environmental hazard. It also demonstrates that the effectiveness of geostatistics and GIS techniques provided a powerful tool for this study in terms of regionalized nutrient management.

Mapping of spatial variability in soil properties for site-specific nutrient management of Nagpur Mandarin in Central India

2018 ◽  
Vol 75 (2) ◽  
pp. 209 ◽  
Author(s):  
S.S. Sawant ◽  
M.S.S. Nagaraju ◽  
Rajeev Srivastava ◽  
Jagdish Prasad ◽  
R.A. Nasre ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Nutrient Management ◽  
Central India ◽  
Site Specific

scholarly journals Delineation of Soil Fertility Management Zones for Site-specific Nutrient Management in the Maize Belt Region of Nigeria

2020 ◽  
Vol 12 (21) ◽  
pp. 9010
Author(s):  
Kamaluddin T. Aliyu ◽  
Alpha Y. Kamara ◽  
Jibrin M. Jibrin ◽  
Jeroen E. Huising ◽  
Bello M. Shehu ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Crop Production ◽  
Nutrient Management ◽  
Available P ◽  
Soil Fertility Management ◽  
Extrinsic Factors ◽  
Total N ◽  
Site Specific ◽  
Management Zones

Site-specific nutrient management can reduce soil degradation and crop production risks related to undesirable timing, amount, and type of fertilizer application. This study was conducted to understand the spatial variability of soil properties and delineate spatially homogenous nutrient management zones (MZs) in the maize belt region of Nigeria. Soil samples (n = 3387) were collected across the area using multistage and random sampling techniques, and samples were analyzed for pH, soil organic carbon (SOC), macronutrients (N, P, K, S, Ca and Mg), micronutrients (S, B, Zn, Mn and Fe) content, and effective cation exchange capacity (ECEC). Spatial distribution and variability of these parameters were assessed using geostatistics and ordinary kriging, while principal component analysis (PCA) and multivariate K-means cluster analysis were used to delineate nutrient management zones. Results show that spatial variation of macronutrients (total N, available P, and K) was largely influenced by intrinsic factors, while that of S, Ca, ECEC, and most micronutrients was influenced by both intrinsic and extrinsic factors with moderate to high spatial variability. Four distinct management zones, namely, MZ1, MZ2, MZ3, and MZ4, were identified and delineated in the area. MZ1 and MZ4 have the highest contents of most soil fertility indicators. MZ4 has a higher content of available P, Zn, and pH than MZ1. MZ2 and MZ3, which constitute the larger part of the area, have smaller contents of the soil fertility indicators. The delineated MZs offer a more feasible option for developing and implementing site-specific nutrient management in the maize belt region of Nigeria.

scholarly journals Soil Properties Spatial Variability and Delineation of Site-Specific Management Zones Based on Soil Fertility Using Fuzzy Clustering in a Hilly Field in Jianyang, Sichuan, China

2019 ◽  
Vol 11 (24) ◽  
pp. 7084 ◽  
Author(s):  
Mohamed S. Metwally ◽  
Sameh M. Shaddad ◽  
Manqiang Liu ◽  
Rong-Jiang Yao ◽  
Ahmed I. Abdo ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Degradation ◽  
Crop Production ◽  
Nutrient Management ◽  
Soil Nutrient ◽  
Available Phosphorus ◽  
Site Specific ◽  
Management Zones ◽  
Nutrient Contents

Avoiding soil degradation and improving crop productivity could be achieved by performing sustainable soil nutrient management with an appropriate understanding of soil properties’ spatial variability. The present fertilizer recommendations for the region where the study area is located are typically symmetric for large regions. This leads to the under-application of fertilizers in zones with low nutrient contents and over-application in zones with high nutrient contents. Therefore, this study was conducted to assess soil management zones (MZs) in the study area for effective soil nutrient management and to evaluate soil properties’ spatial variability. A total of 100 geo-referenced soil samples were collected at a depth of 0–20 cm, processed and analyzed for pH, available nitrogen (AN), available phosphorus (AP), available potassium (AK), soil organic carbon (SOC), total nitrogen (TN) and total phosphorous (TP), while C:N, C:P and N:P ratios were calculated. Soil properties’ coefficients of variation (CVs) widely varied from low (1.132%) to moderate (45.748%). Ordinary kriging and semi-variogram analysis showed differed spatial variability patterns for the studied soil properties with spatial dependence ranged from weak to strong. MZs were delineated by performing principal component analysis (PCA) and fuzzy K-means clustering. Four PCs with eigen values more than 1 dominated 84.44% of the total variance, so they were retained for clustering analysis. Three MZs were delineated based on the two criteria modified partition entropy (MPE) and fuzzy performance index (FPI). The studied soil properties differed significantly among MZs. Thus, the methodology used for MZ delineation could be used effectively for soil site-specific nutrient management for avoiding soil degradation concurrently with maximizing crop production in the study area.

scholarly journals Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

2009 ◽  
Vol 33 (4) ◽  
pp. 819-830 ◽  
Author(s):  
José Maria Barbat Parfitt ◽  
Luís Carlos Timm ◽  
Eloy Antonio Pauletto ◽  
Rogério Oliveira de Sousa ◽  
Danilo Dufech Castilhos ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Information Quality ◽  
Biological Properties ◽  
Exchange Capacity ◽  
Soil Water Storage ◽  
Irrigated Rice ◽  
Total N ◽  
Classical Statistics ◽  
Lowland Area

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

Assessment of spatial variability of soil properties using geospatial techniques for farm level nutrient management

2017 ◽  
Vol 169 ◽  
pp. 25-34 ◽  
Author(s):  
Duraisamy Vasu ◽  
S.K. Singh ◽  
Nisha Sahu ◽  
Pramod Tiwary ◽  
P. Chandran ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Nutrient Management ◽  
Geospatial Techniques ◽  
Farm Level

scholarly journals Spatial variability of saturated hydraulic conductivity and its links with other soil properties at the regional scale

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Boguslaw Usowicz ◽  
Jerzy Lipiec
Keyword(s):  
Spatial Distribution ◽  
Hydraulic Conductivity ◽  
Organic Carbon ◽  
Spatial Variability ◽  
Soil Properties ◽  
Regional Scale ◽  
Total Porosity ◽  
The Other ◽  
Study Region ◽  
The Mean

AbstractSaturated hydraulic conductivity (K) is a key property for evaluating soil water movement and quality. Most studies on spatial variability of K have been performed soil at a field or smaller scale. Therefore, the aim of this work was to assess (quantify) the spatial distribution of K at the larger regional scale in south-eastern Poland and its relationship with other soil properties, including intrinsic sand, silt, and clay contents, relatively stable organic carbon, cation exchange capacity (CEC) and temporally variable water content (WC), total porosity (FI), and dry bulk density (BD) in the surface layer (0–20 cm). The spatial relationships were assessed using a semivariogram and a cross-semivariogram. The studied region (140 km2) with predominantly permeable sandy soils with low fertility and productivity is located in the south-eastern part of Poland (Podlasie region). The mean sand and organic carbon contents are 74 and 0.86 and their ranges (in %) are 45–95 and 0.002–3.75, respectively. The number of individual samples varied from 216 to 228 (for K, WC, BD, FI) to 691 for the other soil properties. The best fitting models were adjusted to the empirical semivariogram (exponential) and the cross-semivariogram (exponential, Gaussian, or linear) used to draw maps with kriging. The results showed that, among the soil properties studied, K was most variable (coefficient of variation 77.3%) and significantly (p < 0.05) positively correlated with total porosity (r = 0.300) and negatively correlated with soil bulk density (r = – 0.283). The normal or close to the normal distribution was obtained by natural logarithmic and root square transformations. The mean K was 2.597 m day−1 and ranged from 0.01 up to 11.54 m day−1. The spatial autocorrelation (range) of K in the single (direct) semivariograms was 0.081° (8.1 km), while it favourably increased up to 0.149°–0.81° (14.9–81 km) in the cross-semivariograms using the OC contents, textural fractions, and CEC as auxiliary variables. The generated spatial maps allowed outlining two sub-areas with predominantly high K above 3.0 m day−1 in the northern sandier (sand content > 74%) and less silty (silt content < 22%) part and, with lower K in the southern part of the study region. Generally, the spatial distribution of the K values in the study region depended on the share of individual intrinsic textural fractions. On the other hand, the ranges of the spatial relationship between K and the intrinsic and relatively stable soil properties were much larger (from ~ 15 to 81 km) than between K and the temporally variable soil properties (0.3–0.9 km). This knowledge is supportive for making decisions related to land management aimed at alteration of hydraulic conductivity to improve soil water resources and crop productivity and reduce chemical leaching.

scholarly journals Deciphering Soil Spatial Variability through Geostatistics and Interpolation Techniques

2020 ◽  
Vol 13 (1) ◽  
pp. 194
Author(s):  
Mohamed A. E. AbdelRahman ◽  
Yasser M. Zakarya ◽  
Mohamed M. Metwaly ◽  
Georgios Koubouris
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Nutrient Management ◽  
Prediction Method ◽  
Available Phosphorus ◽  
Detailed Knowledge ◽  
Agricultural Planning ◽  
Management Recommendations ◽  
Soil Spatial Variability

Detailed knowledge of soil properties is fundamentally important for optimizing agriculture practices and management. Meanwhile, the spatial distribution of soil physicochemical properties is considered a fundamental input of any sustainable agricultural planning. In the present study, ordinary kriging, regression kriging and IDW were chosen for deciphering soil spatial variability and mapping soil properties in a reclaimed area of the Behera Governorate of Egypt where soil arose from two different types, one sandstone and the other limestone. Geostatistics were used to show the interrelationships and conditions of soil properties (available phosphorus, potassium and nitrogen, EC, pH, Sp, ESP, CEC, OC, SAR, and CaCO3). The results of mapping spatial soil variability by Geostatistics could be used for precision agriculture applications. Based on the soil test results, nutrient management recommendations should be applied regarding variable rates of fertilizers. The performance of the maps was evaluated using Mean square error (MSE). Inverse distance weight (IDW) showed higher efficiency than Kriging as a prediction method for mapping the studied soil properties in the study area. The results of the present study suggest that the application of the selected fit model worldwide in any relevant study of soil properties of different geological sources is feasible.

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