Response Surface Modelling of The Physicochemical Properties and Hydraulic Conductivity Prediction Using Selected Properties of Soil in Abia State, Nigeria
Fuente:
Zenodo
Guardado en:
| Autores principales: | , , , , , |
|---|---|
| Formato: | Recurso digital |
| Lenguaje: | inglés |
| Publicado: |
Zenodo
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866902222904754176 |
|---|---|
| author | Edet, J. A. Tom, C. N. Ahaneku, I. E. Etoamaihe, U. J. Orji, C. U Gam, Eunice N. |
| author_facet | Edet, J. A. Tom, C. N. Ahaneku, I. E. Etoamaihe, U. J. Orji, C. U Gam, Eunice N. |
| contents | <p>Understanding the dynamic interplay between soil physicochemical properties and water transmission behavior is crucial in enhancing agricultural productivity, resource efficiency, and environmental sustainability. In line with this, the present research focuses on the response surface modeling (RSM) of the physicochemical properties and hydraulic conductivity (K) of soils in Abia State, Nigeria, spanning the three senatorial districts: Abia North, Abia Central, and Abia South. The study is situated within the broader framework of Agricultural Bioresources Engineering, a field concerned with optimizing natural resources for sustainable agriculture using engineering principles. The research aims to evaluate how soil texture, physical structure, and chemical composition interact across various soil types—Ferralitic, Hydromorphic, and Alluvial—and how these interactions influence hydraulic conductivity at different depths (1–15 cm, 16–25 cm, and 26–35 cm). These properties are critical for irrigation planning, fertilizer scheduling, erosion control, and the design of soil-water conservation structures. Field sampling was carried out systematically across selected agricultural zones in Abia State. A total of 27 composite soil samples were collected and analyzed for both physical properties—sand, silt, clay, bulk density, porosity, particle density, and hydraulic conductivity—and chemical properties—nitrogen (N₂), organic carbon (OC), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), and phosphorus (P). Laboratory analysis followed standardized protocols, and data were subjected to statistical modeling, using Response Surface Methodology (RSM) to investigate multi-variable interactions and predictive capabilities. The results revealed significant spatial and vertical variability in all soil parameters. Texture analysis showed that sand dominates the topsoil (average 61.24%), while clay increases with depth, particularly in Ferralitic soils of Abia South, where values exceed 38%. Silt content remained relatively consistent but played a secondary role in determining hydraulic behavior. Bulk density ranged from 1.12 to 1.82 g/cm³, increasing with depth, while porosity showed a converse trend, reflecting classical compaction profiles. Particle density was stable (~2.34 g/cm³), suggesting mineral-dominant soils with moderate organic input. The models demonstrated strong predictive power (R² > 0.85), confirming that soil texture and structure parameters, along with organic matter and base saturation, are primary drivers of hydraulic conductivity. The interaction terms in the models provided insight into synergistic and antagonistic effects—for example, high organic carbon improved K in sandy soils but had limited effect in clay-dominated layers unless supported by high calcium or porosity.</p> <p> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15393892 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Response Surface Modelling of The Physicochemical Properties and Hydraulic Conductivity Prediction Using Selected Properties of Soil in Abia State, Nigeria Edet, J. A. Tom, C. N. Ahaneku, I. E. Etoamaihe, U. J. Orji, C. U Gam, Eunice N. Response Surface, Modeling, Physicochemical, Properties, Hydraulic, Conductivity <p>Understanding the dynamic interplay between soil physicochemical properties and water transmission behavior is crucial in enhancing agricultural productivity, resource efficiency, and environmental sustainability. In line with this, the present research focuses on the response surface modeling (RSM) of the physicochemical properties and hydraulic conductivity (K) of soils in Abia State, Nigeria, spanning the three senatorial districts: Abia North, Abia Central, and Abia South. The study is situated within the broader framework of Agricultural Bioresources Engineering, a field concerned with optimizing natural resources for sustainable agriculture using engineering principles. The research aims to evaluate how soil texture, physical structure, and chemical composition interact across various soil types—Ferralitic, Hydromorphic, and Alluvial—and how these interactions influence hydraulic conductivity at different depths (1–15 cm, 16–25 cm, and 26–35 cm). These properties are critical for irrigation planning, fertilizer scheduling, erosion control, and the design of soil-water conservation structures. Field sampling was carried out systematically across selected agricultural zones in Abia State. A total of 27 composite soil samples were collected and analyzed for both physical properties—sand, silt, clay, bulk density, porosity, particle density, and hydraulic conductivity—and chemical properties—nitrogen (N₂), organic carbon (OC), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), and phosphorus (P). Laboratory analysis followed standardized protocols, and data were subjected to statistical modeling, using Response Surface Methodology (RSM) to investigate multi-variable interactions and predictive capabilities. The results revealed significant spatial and vertical variability in all soil parameters. Texture analysis showed that sand dominates the topsoil (average 61.24%), while clay increases with depth, particularly in Ferralitic soils of Abia South, where values exceed 38%. Silt content remained relatively consistent but played a secondary role in determining hydraulic behavior. Bulk density ranged from 1.12 to 1.82 g/cm³, increasing with depth, while porosity showed a converse trend, reflecting classical compaction profiles. Particle density was stable (~2.34 g/cm³), suggesting mineral-dominant soils with moderate organic input. The models demonstrated strong predictive power (R² > 0.85), confirming that soil texture and structure parameters, along with organic matter and base saturation, are primary drivers of hydraulic conductivity. The interaction terms in the models provided insight into synergistic and antagonistic effects—for example, high organic carbon improved K in sandy soils but had limited effect in clay-dominated layers unless supported by high calcium or porosity.</p> <p> </p> |
| title | Response Surface Modelling of The Physicochemical Properties and Hydraulic Conductivity Prediction Using Selected Properties of Soil in Abia State, Nigeria |
| topic | Response Surface, Modeling, Physicochemical, Properties, Hydraulic, Conductivity |
| url | https://doi.org/10.5281/zenodo.15393892 |