Increasingly frequent extreme rainfall as a result of climate change is strongly damaging the global soil and water environment. However, few studies have focused on daily extreme sediment events (DESE) in heterogeneous karst watersheds based on long-term in -situ observations. This study quantitatively assessed the time effect of DESE on rainfall response, decoupled the impact of environmental factors on DESE by using structural equation modelling, and finally explored the modelling scheme of DESE based on the hybrid model. The results showed that DESE had the highest frequency of occurrence in May -July, with dispersed distribution in the value domain. Rainfall with a time lag of 1 day and a time accumulation of 2 or 3 days was an important contribution to DESE ( P < 0.01, R = 0.47 -0.68). Combined effects of environmental factors explained 53.6 % -64.1 % of the variation in DESE. Runoff and vegetation exerted the strongest direct and indirect effects on DESE, respectively (8 = 0.66/ -0.727). Vegetation was the dominant driver of DESE in Dabanghe and Yejihe (8 = -0.725/-0.758), while the dominant driver in Tongzhihe was climate (8 = 0.743). In the future, the risk of extreme sediments should be prevented and resolved through the comprehensive regulation of multiple paths, such as runoff and vegetation. Hybrid models significantly improved the modelling performance of machine learning models. Generalized additive model -Extreme gradient boost had the best performance, while Partial least squares regression -Extreme gradient boost was the most valuable when considering performance and input data cost. Two methods can be used as recommended solutions for DESE modelling. This study provides new and in-depth insights into DESE in

In this study, in situ observations were conducted for six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O-3) at 23 sites in western China for 1 year. Subsequently, the detailed Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) results for the pollutants were determined. The WRF-Chem model provided a clear perspective on the spatiotemporal distribution of air pollutants. High pollutant concentrations were mainly observed over highly populated mega-city regions, such as Sichuan and Guanzhong basins, whereas low concentration levels were observed over the Tibetan Plateau (TP). The TP also showed an increased concentration of O-3. Seasonally, all six pollutants except O-3 exhibited high concentration values during winter and low values during summer. O-3 concentrations exhibited an opposite seasonal variation in low-altitude regions. Unlike other pollutants that exhibited gradually decreasing concentrations with an increase in altitude, O-3 concentrations revealed an increasing trend. Furthermore, NO2 concentrations gradually increased in the upper atmosphere possibly due to lighting and stratospheric transmission. Atmospheric pollution is closely related to emissions and meteorological variations in western China. Meteorological conditions in the summer are conducive to pollutant dispersion and wet scavenging; however, unfavourable weather conditions (high pressure as well as a low planetary boundary layer height and precipitation level) in the winter can further worsen air pollution. Atmospheric pollutants from various emission sectors generally exhibited varying monthly profiles. In six typical cities, pollutants were positively correlated with multiple emission sources except for industrial emissions. Further sensitivity simulations indicated that eliminating residential emissions resulted in the largest decrease (up to 70%) in PM2.5 and PM10 concentrations. The most significant reductions in the concentrations of SO2 and NO2 were achieved by eliminating industrial and transportation emissions, respectively. The outcomes of this study could be helpful for future studies on pollution formation mechanisms as well as environmental and health risk assessments in western China. (C) 2019 Elsevier Ltd. All rights reserved.

The calculation of the settlement after the soft foundation treatment is directly related to the unloading time of the soft foundation treatment. In order to study the post-construction settlement characteristics of soft foundation treatment under secondary consolidation, the numerical models of soft foundation without consideration of secondary consolidation and under secondary consolidation were established by MC (Mohr-Coulomb) constitutive and SSC(soft soil creep) constitutive construction, respectively, and the influencing factors of secondary consolidation were proposed. and the existing settlement calculation formula was modified, and the results showed that: (1) The secondary consolidation has a significant effect on the sedimentation rate, and the sub-consolidation is only about 0.5 times of the non-secondary consolidation sedimentation rate, and it is recommended that the sub-consolidation impact factor should be 0.5-0.8. (2) The sedimentation rate calculated by the method proposed in this paper is similar to the measured data and has good applicability.