Modelling of Field Capacity from Basic Soil Properties on a Typical Alfisol
The understanding of soil water retention characteristics, including field capacity, plays a pivotal role in various agricultural studies and practices. This knowledge informs the development of irrigation and drainage schedules, assessments of soil water storage capacity (commonly referred to as pl...
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| Published in: | Bulgarian Journal of Soil Science Vol. 9; no. 1; pp. 113 - 128 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Bulgarian Soil Science Society
01-06-2024
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | The understanding of soil water retention characteristics, including field capacity, plays a pivotal role in various agricultural studies and practices. This knowledge informs the development of irrigation and drainage schedules, assessments of soil water storage capacity (commonly referred to as plant available water), analyses of solute movement, evaluations of plant growth, and assessments of water stress levels. This study the aim of creating a regression model or equation to predict field capacity of soils in a typical Alfisol, which originated from parent material of basement complex, at the University of Ilorin Teaching and Research Farm. A total of forty-five (45) disturbed and forty-five (45) undisturbed soils samples were collected along a toposequence (upper, middle and bottom slope) at depths: 0 – 30 cm, 30 – 60 cm and 60 – 90 cm. Soil properties of the disturbed and undisturbed samples were ascertained through standard laboratory techniques and/or calculated utilizing established protocols. The measured soil properties include sand, silt, clay, bulk density, total porosity, field capacity and organic matter. A significant negative relationship between field capacity and bulk density (r = -0.582, P≤0.05) was found and a significant positive relationship between field capacity and total porosity (r = 0.581, P≤0.05) was found. A total of four different models were developed for predicting field capacity of the soil. Model four of field capacity was identified as the best model with the highest R2 adjusted value of 0.4494. The model explains 45% of variance in the mean square errors of field capacity with sand, bulk density, silt and organic matter contributing statistically to the model. |
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| ISSN: | 2534-8787 2367-9212 |
| DOI: | 10.5281/zenodo.11409795 |