RESUMO
Riverbank instability in the seasonally frozen zone is primarily caused by freeze-thaw erosion. Using the triaxial freeze-thaw test on the bank of Shisifenzi Bend in the Yellow River section of Inner Mongolia, we investigated the changes in the mechanical properties of the soil at different freezing temperatures and freeze-thaw times, and analyzed the bank's stability before and after freezing based on the finite element strength reduction method. The results showed that the elastic modulus, cohesion, internal friction angle and shear strength of the soil tended to decrease with the increase in the number of freeze-thaw cycles and the decrease in freezing temperature. After 10 freezing cycles at - 5 â, - 10 â, - 15 â and - 20 â, the modulus of elasticity of soil decreased by 40.84 ~ 68.70%, the cohesion decreased by 41.96 ~ 56.66%, the shear strength decreased by 41.92 ~ 57.32%, respectively. Moreover, the stability safety coefficient of bank slope decreased by 18.58% after freeze-thaw, indicating that the freeze-thaw effect will significantly reduce the stability of bank slope, and the bank slope is more likely to be destabilized and damaged after freeze-thaw.
RESUMO
The compressibility of bank soils is a critical consideration in t riverbank protection project, construction. In the Inner Mongolia section of the Yellow River, a seasonal frozen soil region, the impact of F-T cycles on soil compressibility cannot be overlooked. This study, based on F-T cycle tests, conducted orthogonal consolidation tests on embankment sandy silt from the Inner Mongolia section of the Yellow River, considering varying initial w and ρd. It investigated the effects of different initial w, ρd, and F-T cycles on soil compressibility, ranked and assessed the significance of influencing factors, and established a predictive model for the compressibility of Inner Mongolia section Yellow River embankment sandy silt. The results show that: the embankment sandy silt is medium-high compression soil, with a between 0.1 and 0.74 MPa-1, Es between 2.65 and 18.47 MPa, and Cc between 0.04 and 0.24 MPa. The greater the ρd of soil, the smaller the initial w, the smaller the a and Cc, and the greater the Es of soil. The F-T effect affects soil compressibility, and soil a, Es and Cc are linearly related to the number of F-T cycles. The ranking of factors influencing soil compressibility is ρd > w > F-T cycles. The initial ρd and w are decisive factors affecting soil compressibility, while the impact of F-T cycles is relatively minor. Additionally, a regression predictive model based on the initial ρd and w of the soil demonstrates good performance in predicting soil compression indices. This model can be utilized for predicting the compressibility indices of embankment soil in the Inner Mongolia section of the Yellow River.
RESUMO
The accurate simulation of stomatal conductance is crucial for not only revealing the carbon and water cycle processes of an ecosystem, but also to improve the accuracy of simulations of evapotranspiration (ET). This study coupled three stomatal conductance models, i.e. the Stannard (ST), Jarvis-Stewart (JS), and Ball-Berry (BB) models, with the Shuttleworth-Wallace (SW) model to estimate ET for a mobile dune ecosystem in the Horqin Sandy Land, North China. These models were calibrated and validated using eddy covariance (EC) measurements taken during the growing season between 2013 and 2018. The results indicated that the SW-BB model showed better performance in comparison to the SW-JS and SW-ST models at half-hourly and daily timescales. The stomatal conductance models incorporating soil moisture (SM) content generally showed better performance during the extreme drought period, with the rank of the three models according to performance being: SW-BB > SW-JS > SW-ST. The models showed the highest sensitivity to SM when incorporating the effect of SM on stomatal conductance, indicating that SM has an important effect on stomatal conductance and ET. The results of this study indicate that of the models assessed, the Ball-Berry stomatal conductance model coupled with the SW model is optimal for estimating ET in dune ecosystems with sparse vegetation.