Geospatial Approach to Soil Fertility Mapping in Dailekh District, Nepal: A GIS Perspective
Spatial mapping of the soil gives the distribution patterns of the nutrients, which is crucial for integrated nutrient management, site-specific crop selection, water resource management, and adaptation to climate change for optimizing productivity. This research aims to identify the spatial variab...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Society for AgroEnvironmental Sustainability
2025-03-01
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| Series: | AgroEnvironmental Sustainability |
| Subjects: | |
| Online Access: | https://www.sagens.org/journal/agens/article/view/130 |
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| Summary: | Spatial mapping of the soil gives the distribution patterns of the nutrients, which is crucial for integrated nutrient management, site-specific crop selection, water resource management, and adaptation to climate change for optimizing productivity. This research aims to identify the spatial variability of soil chemical properties in the Dailekh district of Karnali Province, Nepal, by preparing a map in a raster setting. A total of 204 samples were collected using stratified random sampling techniques using Google Earth Pro and were analyzed using IBM SPSS 27.0 and Arc Map 10.2 software. The classical statistical method was used for the descriptive analysis of sampled data. The Quantile Quantile (QQ) plot was made to visualize the distribution pattern, and non-normal data were log-transformed to match the straight line. Before making a map, sampled datasets were examined using the trend analysis feature of Arc Map using second-order polynomials in 3D scattered plots. The widely used interpolation technique, Ordinary kriging of two Exponential and Circular models, was applied to data and cross-validated with minimum estimated errors. Fertility mapping of parameters results in more than 81%, 56 %, and 57% of the areas covered by nitrogen, phosphorus, and potassium, with medium in status. Similarly, organic matter has low content shades in 65% of areas and moderately acidic pH in 49% of areas. This research supports decision-making for nutrient distribution across agricultural fields and sustainable land management for precision farming.
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| ISSN: | 2583-942X |