ArticlePloS one2018
Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 84 citations in OpenAlex.
- Spatial variability of soil physicochemical properties in soybean wheat belts in Vertisols of central India.Scientific reports · 2025Article
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- A Global Database of Soil Plant Available Phosphorus.Scientific data · 2023Article
- Influence of land use types on the distribution of selected soil properties in tropical soils of the Coastal Savanna zone.Heliyon · 2023Article
- Assessing spatial variability of selected soil properties in Upper Kabete Campus coffee farm, University of Nairobi, Kenya.Heliyon · 2022Article
- Application of a semivariogram based on a deep neural network to Ordinary Kriging interpolation of elevation data.PloS one · 2022Article
- Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China.PloS one · 2021Article
- Evaluation of spatial spreading of phyto-available sulphur and micronutrients in cultivated coastal soils.PloS one · 2021Article
- Spatial variability of soil chemical properties under different land-uses in Northwest Ethiopia.PloS one · 2021Article
- Potassium nutrient response in the rice-wheat cropping system in different agro-ecozones of Nepal.PloS one · 2021Article
- Article
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands of the Bara district in Nepal. The study was carried out in 23 Village Development Committees with 12,516 ha total area, in the southern part of the Bara district. A total of 109 surface soil samples (0 to 15 cm depth) were collected and analyzed for pH, organic matter (OM), nitrogen (N), phosphorus (P, expressed as P2O5), potassium (K, expressed as K2O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P2O5) were skewed and non-normally distributed and logarithmic transformation was then applied. A geostatistical tool, kriging, was used in ArcGIS to interpolate measured values for those variables and several digital map layers were developed based on each soil chemical property. Geostatistical interpolation identified a moderate spatial variability for pH, OM, N, P2O5, and a weak spatial variability for K2O, Zn, and B, depending upon the use of amendments, fertilizing methods, and tillage, along with the inherent characteristics of each variable. Exponential (pH, OM, N, and Zn), Spherical (K2O and B), and Gaussian (P2O5) models were fitted to the semivariograms of the soil variables. These maps allow farmers to assess existing farm soils, thus allowing them to make easier and more efficient management decisions and maintain the sustainability of productivity.
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