TY - JOUR
T1 - Systematic and scientometric analyses of predictors for modelling water pipes deterioration
AU - Shaban, Ibrahim Abdelfadeel
AU - Eltoukhy, Abdelrahman E.E.
AU - Zayed, Tarek
N1 - Funding Information:
The authors gratefully acknowledge the support of the Innovation and Technology Fund (Innovation and Technology Support Programme (ITSP)) under grant number ITS/033/20FP and the support of the Water Supplies Department of Hong Kong .
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023/5
Y1 - 2023/5
N2 - The deterioration of water pipes causes significant socio-economic and environmental burdens. Many predictors/factors are used to mitigate such problems by modelling the water pipe deterioration. However, these predictors have not been thoroughly investigated in the literature. This study adopts mixed systematic and scientometric analyses to review the predictors used in modelling water pipe deterioration. Within the study context, the predictors are categorised into pipe-related, soil and corrosion-induced, operational, and environmental. The results reveal that the pipe-related predictors have received the most attention in the reviewed studies, whereas further investigations are required to study long-term changes in the environmental-induced predictors. Accordingly, future research directions are recommended to fill these gaps (e.g., considering sustainability issues, and deploying real-time monitoring, and IoT facilities to enhance data availability. These directions greatly benefit practitioners and researchers from multidisciplinary backgrounds in research directions related to water pipes.
AB - The deterioration of water pipes causes significant socio-economic and environmental burdens. Many predictors/factors are used to mitigate such problems by modelling the water pipe deterioration. However, these predictors have not been thoroughly investigated in the literature. This study adopts mixed systematic and scientometric analyses to review the predictors used in modelling water pipe deterioration. Within the study context, the predictors are categorised into pipe-related, soil and corrosion-induced, operational, and environmental. The results reveal that the pipe-related predictors have received the most attention in the reviewed studies, whereas further investigations are required to study long-term changes in the environmental-induced predictors. Accordingly, future research directions are recommended to fill these gaps (e.g., considering sustainability issues, and deploying real-time monitoring, and IoT facilities to enhance data availability. These directions greatly benefit practitioners and researchers from multidisciplinary backgrounds in research directions related to water pipes.
KW - Deterioration modelling
KW - Performance measurement
KW - Water mains
KW - Water pipes
UR - http://www.scopus.com/inward/record.url?scp=85149177955&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2022.104710
DO - 10.1016/j.autcon.2022.104710
M3 - Review article
AN - SCOPUS:85149177955
SN - 0926-5805
VL - 149
JO - Automation in Construction
JF - Automation in Construction
M1 - 104710
ER -