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作 者:张杰[1,2] 韩同春[1,2] 豆红强[1,2] 马世国[1,2]
机构地区:[1]浙江大学滨海和城市岩土工程研究中心,浙江杭州310058 [2]浙江大学软弱土与环境土工教育部重点实验室,浙江杭州310058
出 处:《中南大学学报(自然科学版)》2014年第12期4355-4361,共7页Journal of Central South University:Science and Technology
基 金:国家自然科学基金资助项目(51178423)~~
摘 要:Green-Ampt入渗模型是以湿润锋至入渗面间的土体均达到饱和含水率为基础建立的,忽略非饱和区存在的实际情况,造成Green-Ampt模型计算结果不准确。针对黄土入渗水分剖面变化特征,建立入渗分层假设,基于达西定律和雨水入渗质量守恒方程,推求入渗深度和时间的关系,并将其引入边坡安全系数分析。研究结果表明:湿润锋深度和时间的关系中,分层假设模型更贴近实测值,总体吻合性较高。分层假设模型的累积入渗量比实测值略偏大,而Green-Ampt模型的累积入渗量与分层假设值随湿润锋深度增加变大。同时,边坡安全系数中,以Green-Ampt模型计算的边坡安全系数过于保守,分层假设模型比Green-Ampt模型的边坡入渗深度和失稳时间有明显延缓。正确分析土体内部入渗情况,将有助于准确预报边坡滑坡失稳,从而减小不必要的边坡加固,造成经济浪费。Green-Ampt infiltration model was set up based on from wetting front to the infiltration surface soil reach saturation moisture content, regardless of the unsaturated zone existing at actual situation, which caused Green-Ampt model calculation results inaccurately. Aiming at the characteristics of moisture profile changes under loess infiltration, infiltration layer hypothesis was establishd, and then the relationship between infiltration depth and time through solving Darcy's law and rainfall infiltration mass conservation equation was ascertained, and the relationship was introduced into slope safety factor analysis. The result shows that stratified hypothesis model is closer to the measured value and higher total anastomotic between the infiltration depth and time relationship. Cumulative infiltration quantity of stratified hypothesis model is slightly higher than the measured value, and cumulative infiltration quantity is bigger as the wetting front depth increases between Green-Ampt model and stratified hypothesis' s. At the same time, the calculation of slope safety factor of the Green-Ampt model is too conservative, and the slope infiltration depth and instability time of stratified hypothesis model delay obviously in the Green-Ampt model. The correct analysis of the internal soil infiltration will help us to accurately forecast the landslide slope instability, so as to reduce unnecessary slope reinforcement to cause economic waste.
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