Reference Maps for Cohesion of Karbala Soil using GIS

IJEP 43(14): 1338-1343 : Vol. 43 Issue. 14 (Conference 2023)

Haneen M. Ali1, Raghad Adel1, Jawad K.Thajeel1 and Ahmed Raad Al-Adhadh2*

1. University of Thi-Qar, Department of Civil, College of Engineering, Thi-Qar, Iraq
2. Al-Muthanna University, Department of Civil, College of Engineering, Samawah, Iraq

Abstract

The preliminary design of any building should include soil feature maps as a data resource. Soil cohesion is important in the theories and calculations for designing shallow and deep foundations. However, mapping soil qualities is expensive and time-consuming, especially in areas with complex topographic circumstances. This study used the ArcGIS 10.7.2 programme and the inverse distance weighting (IDW) method to develop coherence maps for soils at a depth of 20 m in Karbala. Then, the contour maps were created to give a general overview of the soil cohesion property, which is one of the crucial characteristics considered while designing the foundations’ bearing capacity. A database was created that can be updated whenever new data is available to store the location of borehole data in addition to other services provided by the GIS database. The results of the digital maps show that the sandy, silty soil layers are dominant and the cohesion value ranges from 8-14 kpa. From a statistical standpoint, the results show acceptable and positive soil cohesiveness mean error values (-0.219, -0.225, -0.258, 0.266, 0.255, 0.263) and root mean squared error values (1.707, 1.943, 1.978, 1.077, 1.977, 5.364) for the six layers.

Keywords

Cohesion, Mapping, Geographic information systems, Inverse distance weighting

References

  1. Brown, C., et al. 2012. Review: Cohesion, coherence, cooperation: European spatial planning coming of age? A dictionary of transport analysis, spatial decision support systems, geographic information science and public participation, making maps: A visual guide to map design for GIS, planning Asian cities: Risks and resilience. Env. Planning B Planning Design. 39(2): 406–412.
  2. Alexander, E. R. 2002. The public interest in planning: From legitimation to substantive plan. Planning Theory. 1(3): 226-249.
  3. Parry, R. B. and C.R. Perkins. 1986. World mapping today. Butterworth, London.
  4. Parry, R. B. and C.R. Perkins. 2000. World mapping today (2nd edn). Bowker Saur, London.
  5. Rashed, K.A. and A.A. Hussein. 2020. GIS as a tool for expansive soil detection at Sulaymaniyah city. J. Eng., 26(6): 152–171.
  6. Khatri, S. and S. Suman. 2019. Mapping of soil geotechnical properties using GIS. Indian Conference on Geotechnical and geo-environmental engineering (ICGGE-2019), Prayagraj, India.
  7. Al-Ani, H., et al. 2013. Categorising geotechnical properties of surfers paradise soil using geographic information system (GIS). Int. J. Geomate. 5(2): 690–695.
  8. Arshid, M. U. and M. A. Kamal. 2020. Regional geotechnical mapping employing kriging on electronic geodatabase. Appl. Sci. (Switzerland). 10 (21): 1–15.
  9. Al-Maliki, L.A.J., et al. 2018. Bearing capacity map for An-Najaf and Kufa cities using GIS. Eng., 10(5): 262–269.
  10. Santos, J.V., S. Thiesen and R.A.R. Higashi. 2018. Geological-geotechnical database from standard penetration test investigations using geographic information systems. In Management of information systems. Ed Maria Pomffyova. IntechOpen.
  11. Mandhour, E.A. 2020. Prediction of compression index of the soil of Al-Nasiriya city using simple linear regression model. Geotech. Geol. Eng., 38 (5): 4969–4980.
  12. Aldefae, A.H., J. Mohammed and H.D. Saleem. 2020. Digital maps of mechanical geotechnical parameters using GIS. Cogent Eng., 7(1).
  13. Ali, H.M., J.K. Thajeel and A.R. Al-Adhadh. 2023. Produce reference maps of internal friction angle for soil using GIS. Int. J. Technical Physical Problems Eng., 15(1): 204–211.
  14. Ali, H.M. and R.R. Shakir. 2021. Geotechnical map of Thi-Qar Governorate using geographical information systems (GIS). Mater. Today Proceedings. 60(3): 1286-1296.
  15. Din, M., et al. 2019. Geotechnical characteristics of subsoil for different sectors of Islamabad. NUST J. Eng. Sci., 11(1): 33–40.
  16. Ziboon, A.R., I. Imzahim and A.G. Khalaf. 2013. Utilization of remote sensing data and GIS applications for determination of the land cover change in Karbala Governorate. 31(15): 2773–2787.
  17. Kadhim, A. 2021. Implementing e-government in Karbala city correlated with the application of GIS. 10(1): 61-75.
  18. Litvak, M. 1990. Continuity and change in the Ulama population of Najaf and Karbala, 1791-1904: A socio-demographic study. Iranian Studies. 23(1–4): 31–60.
  19. Parkes, A. 2021. The ashura assemblage: Kar-bala’s religious urban fabric and reproduction of collective Shi’i identity. Religions. 12(10).
  20. Al-Yasery, H., R.R.A. Almuhanna and Z. Al-Jawa-hery. 2018. Metro stations site selection in Karbala city using GIS. IOP Conference Series Mater. Sci. Eng., 433(1) :012036.
  21. Kadhim, M.M., N.K.S. Al-Saoudi and A.R.T. Ziboon. 2013. Digital geotechnical maps of Basrah city using geographical information systems technique. Eng. Tech. J., 31(4): 599–617.
  22. Delmonaco, G., et al. 2003. Large scale debris-flow hazard assessment: A geotechnical approach and GIS modelling. Natural Hazards Earth System Sci., 3(5): 443–455.
  23. Valverde-Palacios, I., et al. Geotechnical map of Holocene alluvial soil deposits in the metropolitan area of Granada (Spain): A GIS approach. Bulletin Eng. Geol. Env., 73.1: 177-192.
  24. Chen, F.W. and C.W. Liu. 2012. Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy Water Env., 10(3): 209–222.
  25. Tomczak, M. 1998. Spatial interpolation and its uncertainty using automated anisotropic inverse distance weighting (IDW)- Cross-validation/jackknife approach. J. Geographic Information Decision. 2(2): 18–30.