Frequent road collapses caused by water leakages from pipelines pose a severe threat to urban safety and the wellbeing of city residents. Limited research has been conducted on the relationship between pipeline leakage and soil settlement, thus resulting in a lack of mathematical models that accurately describe the soil settlement process resulting from water erosion. In this study, we developed an equation for pipeline leakage, conducted physical model experiments on road collapses induced by drainage pipeline leakage, investigated the functional relationship between drainage pipeline leakage and soil settlement, and validated this relationship through physical experiments with pipelines of various sizes. The results indicated that drainage pipeline leakage triggered internal erosion and damaged the soil layers in four stages: soil particle detachment, seepage channel formation, void development, and road collapse. When the pipeline size was increased by a factor of 1.14, the total duration of road collapse induced by pipeline leakage increased by 20.78%, and the total leakage water volume increased by 33.5%. The Pearson correlation coefficient between the theoretical and actual settlement exceeded 0.9, thus demonstrating the reasonableness and effectiveness of the proposed settlement calculation method. The findings of this study serve as a basis for monitoring soil settlement and issuing early road collapse warnings.

The leakage of drainage pipes is the primary cause of underground cavity formation, and the cavity diameter-to-depth ratio significantly affects the overall stability of roads. However, studies on the quantitative calculation for road comprehensive bearing capacity considering the cavity diameter-to-depth ratio have not been extensively explored. This study employed physical model tests to examine the influence of the cavity diameter-to-depth ratio on road collapse and soil erosion characteristics. Based on limit analysis theorems, a mechanical model between the road comprehensive bearing capacity and the cavity diameter-to-depth ratio (FB-L model) was established, and damage parameters of the pavement and soil layers were introduced to modify the FB-L model. The effectiveness of the FB-L model was validated by the data derived from eight physical model tests, with an average deviation of 14.0%. The results indicate a nonlinear increase in both the maximum diameter and fracture thickness of the collapse pit as the cavity diameter-to-depth ratio increased. The pavement and soil layers adjusted the diameter and fracture thickness of the collapse pit to maintain their load-bearing capacity when the cavity diameter-to-depth ratio changed. The fluid erosion range increased continuously with increasing depth of buried soil and was influenced predominantly by gravity and seepage duration. Conversely, the cavity diameter decreased as the buried depth increased, which is associated with the rheological repose angle of the soil. Furthermore, the damage parameters of the pavement and soil layers decrease as the distance from the collapse pit diminishes, with the pavement exhibiting more severe damage than the soil layer. This study provides a theoretical basis for preventing road collapses.

Recent accidents in water supply networks have the negative impact on the state of the historical and architectural heritage of the Kyiv-Pechersk Lavra, which has been formed over many centuries and is a UNESCO World Heritage Site. We have analysed the water supply system emergency situation on the territory of the Metropolitan Garden that occurred in October 2022 during the Russian military aggression. It caused surface sinkholes, increased groundwater levels, and significant destruction of a historical underground - the Metropolitan Cellar. The study was carried out using numerical analysis implemented in Plaxis 2D. To resolve the uncertainties of the accident, several options for developing the emergency situation were considered, taking into account the number of probable pipe leakages, their size, etc. Accident parameterization was performed with a leakage volume of 1600.0 m3/day, considering damage to the water supply network in two locations. The volume of the watered soil mass was 7.0-8.5 thousand m3. We evaluated the state of destruction of the southern and southeastern branches of the Metropolitan Cellar. Engineering measures for strengthening the of the Monastery walls with buttress elements, increasing the width of the foundations by means of additional concrete and piling are studied. The numerical calculations were verified using the results of geophysical surveys. Comparison of analytical calculations, geophysical surveys and field surveys showed that parts of the underground structure were completely destroyed. Their restoration is possible only by modern methods through reconstruction, that will lead to a loss of authenticity, which is unacceptable for historical structures. To take preventive actions for the protection of monuments, it is necessary to conduct continuous monitoring.

Leakages from damaged or deteriorated buried pipes in urban water distribution networks may cause significant socio-economic and environmental impacts, such as depletion of water resources and sinkhole events. Sinkholes are often caused by internal erosion and fluidization of the soil surrounding leaking pipes, with the formation of soil cavities that may eventually collapse. This in turn causes road disruption and building foundation damage, with possible victims. While the loss of precious water resources is a well-known problem, less attention has been paid to anthropogenic sinkhole events generated by leakages in water distribution systems. With a view to improving urban smart resilience and sustainability of urban areas, this study introduces an innovative framework to localize leakages based on a Machine learning model (for the training and evaluation of candidate sets of pressure sensors) and a Genetic algorithm (for the optimal sensor set positioning) with the goal of detecting and mitigating potential hydrogeological urban disruption due to water leakage in the most sensitive/critical locations. The application of the methodology on a synthetic case study from literature and a real-world case scenario shows that the methodology also contributes to reducing the depletion of water resources.