EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS

Joel Godwin; Ishaya Marafa

doi:10.47137/uujes.1753856

EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS

Abstract

Tropical residual soils, widely found in developing regions, exhibit diverse engineering behaviors due to variations in mineralogy, particle size distribution, and degree of weathering. This study investigates the empirical correlation between California Bearing Ratio (CBR) and index properties—specific gravity, grain size distribution, and Atterberg limits—of tropical residual soils in Niger State, Nigeria. A total of 45 disturbed samples were collected from five locations: Gidan Kwano, Lapai Gwari, Brighter, Gidan Waya, and Gidan Mangoro. Laboratory tests were conducted to determine index and compaction properties, followed by CBR tests under unsoaked and soaked conditions. Statistical summaries revealed wide variation in soil behavior, with plasticity index ranging from 4.73% to 23.63% and maximum dry density from 1.94 to 2.25 g/cm³. The CBR values also varied significantly, with Brighter recording the highest unsoaked CBR of 109.84% and Gidan Kwano the lowest at 15.76%. Using multilinear regression analysis, strong correlations were established between CBR and selected index and properties, with R² values exceeding 0.90 in most cases. These findings affirm the feasibility of using index properties for rapid prediction of CBR, providing a cost-effective tool for pavement subgrade evaluation, especially in resource-constrained settings.

Keywords

References

Oyelami CA, Van Rooy JL. Mineralogical characterisation of tropical residual soils from south-western Nigeria and its impact on earth building bricks. Environ Earth Sci. 2018;77(5):178.
Huat BB, Toll DG, Prasad A. Handbook of tropical residual soils engineering. Boca Raton: CRC Press; 2012.
de Carvalho JC, de Rezende LR, Cardoso FBDF, de Lucena LCF, Guimarães RC, Valencia YG. Tropical soils for highway construction: peculiarities and considerations. Transp Geotech. 2015;5:3–19.
Kassa S, Tamirat H, Quezon E. Empirical correlation of Hossaena Town soil index properties with California bearing ratio (CBR) values. Put i Saobraćaj. 2024. doi:10.31075/pis.70.03.01.
Kassa S, Wubineh B. Use of machine learning to predict California bearing ratio of soils. Adv Civ Eng. 2023. doi:10.1155/2023/8198648.
Koirala D, Awasthi K, Bohara N. Association between CBR and soil index properties: empirical analysis from Chitwan and Makwanpur District soil samples. J UTEC Eng Manag. 2023;1(1). doi:10.36344/utecem.2023.v01i01.002.
Khasawneh M, Mewada H, Nayeemuddin M, Rababah S, Khasawneh A. Integrating soil index parameters and machine learning for reliable California bearing ratio estimation using a GA-ELM model. Int J Pavement Res Technol. 2024. doi:10.1007/s42947-024-00489-x.
Bakri M, Aldhari I, Alfawzan M. Prediction of California bearing ratio of granular soil by multivariate regression and gene expression programming. Adv Civ Eng. 2022. doi:10.1155/2022/7426962.

Ho L, Tran V. Machine learning approach for predicting and evaluating California bearing ratio of stabilized soil containing industrial waste. J Clean Prod. 2022. doi:10.1016/j.jclepro.2022.133587.
Alam S, Mondal A, Shiuly A. Prediction of CBR value of fine-grained soils of Bengal Basin by genetic expression programming, artificial neural network and kriging method. J Geol Soc India. 2020;95:190–196. doi:10.1007/s12594-020-1409-0.
Akinwamide OG. Development of mathematical models to predict the CBR of soaked lateritic soil from five local government areas in Ekiti State, Nigeria [master’s thesis]. Nigeria: Kwara State University; 2022.
Hassan J, Alshameri B, Iqbal F. Prediction of California bearing ratio (CBR) using index soil properties and compaction parameters of low plastic fine-grained soil. Transp Infrastruct Geotech. 2022;9(6):764–776. doi:10.1007/s40515-021-00197-0.
Pule BB, Yendaw JA. The effect of geotechnical soil properties on CBR value. AI Civ Eng. 2024;3(1):19.
Irokwe J, Nwaogazie I, Sule S. Development of empirical models for the estimation of CBR value of soil from their index properties: a case study of the Ogbia–Nembe Road in Niger Delta Region of Nigeria. Open J Civ Eng. 2022. doi:10.4236/ojce.2022.124036.
Katte V, Mfoyet S, Manefouet B, Wouatong A, Bezeng L. Correlation of California bearing ratio (CBR) value with soil properties of road subgrade soil. Geotech Geol Eng. 2018;37:217–234. doi:10.1007/s10706-018-0604-x.
Gowda S, Kunjar V, Gupta A, Kavitha G, Shukla B, Sihag P. Prediction of the subgrade soil California bearing ratio using machine learning and neuro-fuzzy inference system techniques. Urban Sci. 2024. doi:10.3390/urbansci8010004.
Koech B, Osano S, Nyete A. Application of machine learning in estimating California bearing ratio from soil index properties in Kenya. East Afr J Eng. 2025;8(1). doi:10.37284/eaje.8.1.2651.
Khasawneh M, Al-Akhrass H, Rabab’ah S, Al-Sugaier A. Prediction of California bearing ratio using soil index properties by regression and machine-learning techniques. Int J Pavement Res Technol. 2022;17:306–324. doi:10.1007/s42947-022-00237-z.
British Standards Institution. BS 1377: Methods of tests for soils for civil engineering purposes. London: BSI; 1990.
American Association of State Highway and Transportation Officials. AASHTO guide for design of pavement structures. Texas: AASHTO; 1993.
Unified Soil Classification System. Appendix B: Characteristics of soil groups pertaining to roads and airfields. California; 1953.

Details

Primary Language

English

Subjects

Civil Geotechnical Engineering, Transportation Engineering

Journal Section

Research Article

Authors

Joel Godwin ^*
0009-0004-9589-8753
Nigeria

Ishaya Marafa This is me
Nigeria

Publication Date

June 30, 2026

Submission Date

July 30, 2025

Acceptance Date

February 26, 2026

Published in Issue

Year 2026 Volume: 9 Number: 1

DOI

https://doi.org/10.47137/uujes.1753856

IZ

https://izlik.org/JA24XY87CG

Cite

RIS / Bibtex

APA

Godwin, J., & Marafa, I. (2026). EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS. Usak University Journal of Engineering Sciences, 9(1), 1-14. https://doi.org/10.47137/uujes.1753856

AMA

1.Godwin J, Marafa I. EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS. UUJES. 2026;9(1):1-14. doi:10.47137/uujes.1753856

Chicago

Godwin, Joel, and Ishaya Marafa. 2026. “EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS”. Usak University Journal of Engineering Sciences 9 (1): 1-14. https://doi.org/10.47137/uujes.1753856.

EndNote

Godwin J, Marafa I (June 1, 2026) EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS. Usak University Journal of Engineering Sciences 9 1 1–14.

IEEE

[1]J. Godwin and I. Marafa, “EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS”, UUJES, vol. 9, no. 1, pp. 1–14, June 2026, doi: 10.47137/uujes.1753856.

ISNAD

Godwin, Joel - Marafa, Ishaya. “EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS”. Usak University Journal of Engineering Sciences 9/1 (June 1, 2026): 1-14. https://doi.org/10.47137/uujes.1753856.

JAMA

1.Godwin J, Marafa I. EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS. UUJES. 2026;9:1–14.

MLA

Godwin, Joel, and Ishaya Marafa. “EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS”. Usak University Journal of Engineering Sciences, vol. 9, no. 1, June 2026, pp. 1-14, doi:10.47137/uujes.1753856.

Vancouver

1.Joel Godwin, Ishaya Marafa. EMPIRICAL CORRELATION BETWEEN CBR AND INDEX PROPERTIES OF TROPICAL RESIDUAL SOILS. UUJES. 2026 Jun. 1;9(1):1-14. doi:10.47137/uujes.1753856