Assessment of Soil Fertility by Spatial Interpolation Model of Salt Affected Soils in Muang Pere Subdistrict, Ban Phai District, Khon Kaen Province
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Abstract
Background and Objectives: The assessment of soil fertility in salt-affected soils on a large spatial scale has been constrained by limitations in time, manpower, and budget for soil analysis. The application of spatial interpolation modeling, coupled with digital mapping, for evaluating soil fertility emerges as a crucial tool for swiftly forecasting and monitoring the spatial soil fertility of salt-affected soils. This information can be utilized as data for the effective management of salt-affected soils. However, there persists a lack of development of a precise and accurate model. This study seeks to investigate spatial interpolation using the Random Forest (RF) model
to predict properties, and distribution, and assess the fertility level of salt-affected soils of Typic Natraqualfs in Muang Pere subdistrict, Ban Phai district, Khon Kaen province.
Methodology: Soil samples were collected from 100 locations with Typic Natraqualfs in Muang Pere subdistrict, Ban Phai district, Khon Kaen province. The samples were taken from a dept of 0–30 cm and analyzed for organic matter content, available phosphorus and potassium, cation exchange capacity, base saturation percentage, and electrical conductivity of a saturated soil extract. These parameters, along with predicted variables obtained from the Digital Elevation Model (DEM) and Landsat 8’s satellite image data, were input into the spatial interpolation model to predict the spatial distribution of soil properties.
Main Results: The RF model accurately predicted the spatial distribution of soil properties with coefficients of determination (R2 = 0.41–0.82). However, notable prediction errors were observed for available phosphorous, available potassium, and electrical conductivity. The model’s assessment of soil fertility at a depth of 0–30 cm revealed that the Typic Natraqualfs subgroup in the studied area exhibited low to moderate fertility levels.
Conclusions: The RF model demonstrates an accuracy level that can be utilized for the preliminary prediction of the spatial distribution of soil properties and effective assessment of soil fertility in salt-affected soils.
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