Geotechnical and Geological Engineering

, Volume 36, Issue 4, pp 2481–2494 | Cite as

Utilisation of GIS Concepts for Foundation Design on Problematic Eastern Saudi Arabian Sabkha Soil

  • Hamzah M. Beakawi Al-HashemiEmail author
  • Baqer M. Al-Ramadan
  • Naser Al-Shayea
Original paper


The design of foundations on a problematic soil is considered one of the most challenging issues for the geotechnical engineers. Sabkha, or salt flat, is considered as a problematic soil that exists in coastal areas. Ar-Rayyas sabkha is covering a wide area of the Eastern Province of the Kingdom of Saudi Arabia. King Fahd Suburb in the city of Dammam, Saudi Arabia, having been identified with an extensive presence of Ar-Rayyas sabkha, is considered for this study. Many structural failures of the residential buildings in the suburb were reported. The presence of sabkha is predominating the reasons of these failures. 59 investigatory boreholes were performed at the suburb and standard penetration N-values, have been obtained for the boreholes. A regression analysis was carried out, and a prediction model of the N-values using the coordinates and the depth intervals of the boreholes as regressors was provided. Due to the low accuracy of the model, an artificial neural network model was proposed to enhance the accuracy of the prediction; however, a further enhancement was required. Using GIS concepts, the suburb was mapped, and the borehole locations were projected with their attributes on the map. Different interpolation methods were utilised to predict and interpolate the N-values between the boreholes. The inverse distance weighting method yielded the most accurate model and therefore was selected to produce the final layouts for each depth interval. Finally, a framework for the design of foundations with the aid of GIS techniques was developed.


Regression AI ANN GIS Interpolation Foundations SPT Sabkha Ar-Rayyas KF Suburb 





Artificial intelligence


Artificial neural network


Analysis of variances




Completely randomised design


Depth intervals (m)


Degree of freedom


Diffusion kernel


Empirical Bayesian kriging






Geotechnical database


Geotechnical investigation


Geographical information systems


Global polynomial interpolation


Global positioning system


Generalised regression neural network


Groundwater table


Inverse distance weighting

KF Suburb

King Fahd Suburb


Kernel interpolation with barriers


Keyhole markup language


Local polynomial interpolation


Multi-layer feed-forward neural network


Mean of squares


Number of SPT blows

P value

Probability value


Radial basis function


Correlation coefficient


Standard error of estimate




Standard penetration test


Sum of squares




Universal Transverse Mercator


World geodetic system


Eastern coordinates (UTM)


Northern coordinates (UTM)



The authors gratefully acknowledge King Fahd University of Petroleum & Minerals (KFUPM) for supporting this study. Thanks are also extended to Dammam Municipality for providing the raw data.

Supplementary material

10706_2018_477_MOESM1_ESM.pdf (19.4 mb)
Supplementary material 1 (PDF 19854 kb)
10706_2018_477_MOESM2_ESM.pdf (1.4 mb)
Supplementary material 2 (PDF 1480 kb)
10706_2018_477_MOESM3_ESM.docx (15 kb)
Supplementary material 3 (DOCX 14 kb)


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringKing Fahd University of Petroleum and MineralsDhahranSaudi Arabia
  2. 2.Department of City and Regional PlanningKing Fahd University of Petroleum and MineralsDhahranSaudi Arabia

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