English
Język Polski
Risk assessment for underground utility damage due to spatial data quality
DOI:
https://doi.org/10.24425/ace.2024.151884Abstract
Spatial data are used in a variety of projects. Their quality directly contributes to the project’s success. One of the risk sources for underground utility damage in construction works is the quality of spatial data. The article presents the results of research on a method for estimating underground utility damage risk. It consists in calculating the risk (both qualitative and quantitative risk) from specific risk factors and impact weights. The primary risk factors are incomplete spatial datasets and horizontal and vertical position accuracy of objects in the database. The calculated risk value is within 7.0 to 34.2 points. This means that the minimum risk of damage to underground utilities during construction works is 7.0 points and the maximum risk of 34.2 points is nearly five times higher. We also developed a risk map of underground utility damage. It is a thematic map with qualitative project risk. The proposed map is a 2D and 3D cartographic document that represents the actual risk of damage to underground utilities due to spatial data quality.References
[1] I.N. Gleim, CIA Review – Part I: The Internal Audit Activity’s Role in Governance, Risk and Control. Gainesville FL: Gleim Publications Inc., 2004.
[2] S. Kaplan and B.J. Garrick, “On the quantitative definition of risk”, Risk Analysis, vol. 1, no. 1, pp. 11-27, 1981.
[3] Y.Y. Haimes, Risk Modeling, Assessment, and Management. London: Wiley, 2015.
[4] M. Zhao and X. Liu, “Regional risk assessment for urban major hazards based on GIS geoprocessing to improve public safety”, Safety Science, vol. 87, pp. 18-24, 2016, doi:10.1016/j.ssci.2016.03.016.
[5] Q. Tan, M. Bai, P. Zhou, J. Hu, and X. Qin, “Geological hazard risk assessment of line landslide based on remotely sensed data and GIS”, Measurement, vol. 169, 2021, doi:10.1016/j.measurement.2020.108370.
[6] A. Malinowska, X. Cui, E.F. Salmi, and R. Hejmanowski, “A novel fuzzy approach to gas pipeline risk assessment under influence of ground movement”, International Journal of Coal Science & Technology, vol. 9, art. no. 47, 2022, doi:10.1007/s40789-022-00511-2.
[7] A. Malinowska, A. Guzy, R. Hejmanowski, and P. Ulmaniec, “Hybrid-approach for sinkhole occurrence risk mitigation in urban areas”, IOP Conf. Series: Earth and Environmental Science, vol. 291, 2019, doi:10.1088/1755-1315/291/1/012022.
[8] F.H. Bouzahar, L. Ouerdachi, M. Keblouti, and A. Seddiki, “The contribution of remote sensing in hydraulics and hydrology, analysis and evaluation of digital terrain model for flood risk mapping”, Journal Of Water And Land Development, no. 39, pp. 17-26, 2018, doi:10.2478/jwld-2018-0055.
[9] S. Cai, J. Fan, and W. Yang, “Flooding Risk Assessment and Analysis Based on GIS and the TFN-AHP Method, A Case Study of Chongqing, China”, Atmosphere, vol. 12, no. 5, pp. 623, 2021, doi:10.3390/atmos12050623.
[10] D. Zhang, X. Shi, H. Xu, Q. Jing, X. Pan, T. Liu, H. Wang, and H. Hou, “A GIS-based spatial multi-index model for flood risk assessment in the Yangtze River Basin, China”, Environmental Impact Assessment Review, vol. 83, art. no. 106397, 2020, doi:10.1016/j.eiar.2020.106397.
[11] V. Hadipour, F. Vafaie, and K. Deilami, “Coastal Flooding Risk Assessment Using a GIS-Based Spatial Multi-Criteria Decision Analysis Approach”, Water, vol. 12, no. 9, art. no. 2379, 2020, doi:10.3390/w12092379.
[12] P. Tomar, S.K. Singh, S. Kanga, G. Meraj, N. Kranjcic, B. Durin, and A. Pattanaik, “GIS-Based Urban Flood Risk Assessment and Management – A Case Study of Delhi National Capital Territory (NCT), India”, Sustainability, vol. 13, no. 22, art. no. 12850, 2021, doi:10.3390/su132212850.
[13] A.A. Belal, H.R. El-Ramady, S. Elsayed, and A.M. Saleh, “Drought risk assessment using remote sensing and GIS techniques”, Arabian Journal of Geosciences, vol. 7, pp. 35-53, 2014, doi:10.1007/s12517-012-0707-2.
[14] S. Wijitkosum and T. Sriburi, “Fuzzy AHP Integrated with GIS Analyses for DroughtRisk Assessment: A Case Study from Upper Phetchaburi River Basin, Thailand”, Water, vol. 11, no. 5, art. no. 939, 2019, doi:10.3390/w11050939.
[15] R. Jena, B. Pradhan, G. Beydoun, A. Al-Amri, and H. Sofyan, “Seismic hazard and risk assessment: a review of state-of-the-art traditional and GIS models”, Arabian Journal of Geosciences, vol. 13, art. no. 50, 2020, doi:10.1007/s12517-019-5012-x.
[16] P. Yariyan, H. Zabihi, I. D. Wolf, M. Karami, and S. Amiriyan, “Earthquake risk assessment using anintegrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran”, International Journal of Disaster Risk Reduction, vol. 50, art. no. 101705, 2020, doi:10.1016/j.ijdrr.2020.101705.
[17] E. Psomiadis, N. Charizopoulos, N. Efthimiou, K.X. Soulis, and I. Charalampopoulos, “Earth Observation and GIS-Based Analysis for Landslide Susceptibility and Risk Assessment”, ISPRS International Journal of Geo-Information, vol. 9, no. 9, art. no. 552, 2020, doi:10.3390/ijgi9090552.
[18] A. Roccati, G. Paliaga, F. Luino, F. Faccini, and L. Turconi, “GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment”, Land, vol. 10, no. 2, art. no. 162, 2021, doi:10.3390/land10020162.
[19] Q. Zhenga, H. M. Lyua, A. Zhoub, and S.L. Shen, “Risk assessment of geohazards along Cheng-Kun railway using fuzzy AHP incorporated into GIS”, Geomatics, Natural Hazards And Risk, vol. 12, no. 1, pp. 1508-1531, 2021, doi:10.1080/19475705.2021.1933614.
[20] X. Yang, X. Jin, and Y. Zhou, “Wildfire Risk Assessment and Zoning by Integrating Maxent and GIS in Hunan Province, China”, Forests, vol. 12, no. 10, art. no. 1299, 2021, doi:10.3390/f12101299.
[21] Y. A. Hermawan, L. Warlina, and M. Mohd, “GIS-based urban village regional fire riskassessment and mapping”, International Journal of Informatics, Information System and Computer Engineering, vol. 2, no. 2, pp. 143-155, 2021, doi:10.34010/injiiscom.v2i2.6041.
[22] P. Oort, Spatial data quality: from description to application. Publications on Geodesy, no. 60. Delft, 2005.
[23] A. Przewięźlikowska, “Right-of-way for Transmission Facilities as Regulation of Legal Relationships Regarding Real Estate between the Real Estate Owner and the Transmission Entity”, in 10th International Conference: Environmental Engineering, 2017, pp. 1-8, doi:10.3846/enviro.2017.233.
[24] A. Przewięźlikowska and R. Krzyżek, “Inwentaryzacja powykonawcza budynków w kontekście zgodności usytuowania z projektem zagospodarowania terenu – As-built survey of buildings in the context of compliance of the location of the building with the site development plan for the plot”, Przegląd Geodezyjny, no. 8, pp. 11-15, 2016.
[25] B. Tchórzewska-Cieślak, “Characterization of risk function in the analysis and assessment of water supply systems safety”, Technical Transactions, vol. 3, pp. 187-196, 2018.
[26] Y. Kleiner, B.B. Rajani, and R. Sadiq, “Failure risk management of buried infrastructure using fuzzy-based techniques”, Journal of Water Supply Research and Technology – Aqua, vol. 55, no. 2, pp. 81-94, 2006.
[27] B. Tchórzewska-Cieślak, “Rozmyty model ryzyka awarii sieci wodociągowej”, Ochrona Środowiska, vol. 33, no. 1, pp. 35-40, 2012.
[28] P. Kostrzewa-Demczuk and M. Rogalska, “Planning of construction projects taking into account the design risk”, Archives of Civil Engineering, vol. 69, no. 1, pp. 613-626, 2023, doi:10.24425/ace.2023.144191.
[29] T. Godlewski, E. Koda, M. Mitew-Czajewska, S. Łukasik, and S. Rabarijoely, “Essential georisk factors in the assessment of the influence of underground structures on neighboring facilities”, Archives of Civil Engineering, vol. 69, no. 3, pp. 113-128, 2023, doi:10.24425/ace.2023.146070.
Downloads
Published
How to Cite
Issue
Section
