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.

A change in soil temperature (ST) is a significant indicator of climate change, so understanding the variations in ST is required for studying the changes of the Qinghai-Tibet Plateau (QTP) permafrost. We investigated the performance of three reanalysis ST products at three soil depths (0-10 cm, 10-40 cm, and 40-100 cm) on the permafrost regions of the QTP: the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the second version of the National Centers for Environmental Prediction Climate Forecast System (CFSv2), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results indicate that all three reanalysis ST products underestimate observations with negative mean bias error values at all three soil layers. The MERRA-2 product performed best in the first and second soil layers, and the ERA-Interim product performed best in the third soil layer. The spatiotemporal changes of annual and seasonal STs on the QTP from 1980 to 2017 were investigated using Sen's slope estimator and the Mann-Kendall test. There was an increasing trend of ST in the deeper soil layer, which was less than that of the shallow soil layers in the spring and summer as well as annually. In contrast, the first-layer ST warming rate was significantly lower than that of the deeper soil layers in the autumn and winter. The significantly (P < 0.01) increasing trend of the annual ST indicates that the QTP has experienced climate warming during the past 38 years, which is one of the factors promoting permafrost degradation of the QTP.