Results of the Study of Zircon (SIMS) from Granitoids of the Konstantinovskii Stock (Area of the Sukhoi Log Gold Deposit): Age,Sources, and Geological Consequences

Doklady Earth Sciences - The results of U–Pb geochronological (SIMS) study of zircons from granitoids of the Konstantinovskii Stock located 6 km from the Sukhoi Log gold deposit are reported....     

The Strong Earthquake in Sakhalin Island in September 13, 2020

Doklady Earth Sciences - The seismotectonic position of the strong earthquake that occurred in the southern part of Sakhalin Island on September 13, 2020, is considered. The maximum shaking...     

Field study on the behavior of pre-bored grouted planted pile with enlarged grout base

This paper presents the results of field tests performed to investigate the compressive bearing capacity of pre-bored grouted planted (PGP) pile with enlarged grout base focusing on its base bearing capacity. The bi-directional O-cell load test was conducted to evaluate the behavior of full scale PGP piles. The test results show that the pile head displacements needed to fully mobilize the shaft resistance were 5.9% and 6.4% D (D is pile diameter), respectively, of two test piles, owing to the large elastic shortening of pile shaft. Furthermore, the results demonstrated that the PHC nodular pile base and grout body at the enlarged base could act as a unit in the loading process, and the enlarged grout base could effectively promote the base bearing capacity of PGP pile through increasing the base area. The normalized base resistances (unit base resistance/average cone base resistance) of two test piles were 0.17 and 0.19, respectively, when the base displacement reached 5% D_b (D_b is pile base diameter). The permeation of grout into the silty sand layer under pile base increased the elastic modulus of silty sand, which could help to decrease pile head displacement under working load.

     

Basal stability analysis of braced excavations in anisotropic and non-homogeneous undrained clay using streamline velocity fields

Acta Geotechnica - A basal heave stability analysis in anisotropic and non-homogeneous undrained clay by using the kinematic approach of limit analysis is presented. The proposed failure mechanism...     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

Liquid bridge contribution to shear behavior of unsaturated soil: modeling and application to a micromechanics model

Acta Geotechnica - Liquid bridges in unsaturated soils attach to grain contacts and contribute to strengthening microscopic bonding forces, which leads to macroscopic high strength and stiffness...     

淮河流域(河南段)连续性暴雨天气分型及环流背景

利用19812016年68月河南省淮河流域64个国家自动观测站逐日2020时日降水量资料、常规高空探测和地面观测资料等对淮河流域连续性暴雨时间分布特征、影响系统等进行分析和天气分型,结果表明:1)36年淮河流域共发生45次连续性暴雨,2000年的最多,19982008年是高发期,近10年较少,年出现次数无明显减少趋势,存在2~4年和4~6年两个周期;7月连续性暴雨次数最多,6月的最少,旬分布呈正态分布;最长连续时间5天,连续2天的最多。2)影响系统主要有切变线和高低空急流,高空急流在方向转换的过程中,降水有24h左右的减弱期,低空急流有明显的日变化特征,夜间加强,白天减弱。3)连续性暴雨按照500hPa影响系统,分为低槽型、副高边缘型、西北低涡型三类。4)以不同类型的3次典型连续性暴雨为例,从大尺度环流背景、高度距平场、水汽输送、高低空急流等方面探讨了连续性暴雨的维持成因,3次连续性暴雨的发生与异常的500hPa大气环流、高低空急流、切变线和持续偏强的水汽输送等有关。     

1960—2017年沈阳地区春播期降水变化特征

基于1960—2017年沈阳市5个气象观测站4—5月降水量资料,采用线性趋势法和累积距平分析了沈阳市春播期(4—5月)降水量演变特征,并分析首场透雨及最大连续无有效降水日数演变特征及对春播期降水量影响,对春播期降水量资源变化特征进行相关分析。结果表明:近58a沈阳春播期降水量整体呈现弱的增加趋势,平均每10a增加3.1mm,2004年开始降水量迅速增加,且波动性较大,降水量异常偏多或偏少年份较多,易诱发春旱春涝事件。春播期首场透雨出现日期平均每10a偏晚0.051d,首场透雨日期偏晚,将导致春播期前期雨水条件不足,引起土壤干旱,不利于春播开展。最大连续无有效降水日数呈波动性增加趋势,平均每10a增加0.56d,对4月降水量影响较大,虽然春播期降水资源总量增加,但存在降水资源时间分配不均的问题,且长时间无有效降水事件频发,将导致春播期干旱灾害事件发生风险加大,导致适播期延后。     

浙江省涂膜柑橘贮藏期烂果风险区划及历史变化特征

为了了解浙江省涂膜柑橘贮藏期烂果风险的时空分布规律及其近60年的变化特征,利用1961—2016年常规站日气象观测资料,以涂膜柑橘贮藏腐烂阈值及各时段发生的频率为区划指标,采用距离权重反比法(IDW,Inverse Distance Weighted),开展了柑橘贮藏期烂果时间阈值风险区划,并分析了它的年代际变化。结果表明:2006年以后,浙江涂膜柑橘贮藏期烂果出现的时间越来越早,且从西南地区到东北地区柑橘贮藏期烂果出现时间逐渐推迟。最晚时间西南部地区在3月上旬,中西部地区和沿海南部地区在3月中旬,其他地区在3月下旬。21世纪10年代前6年与20世纪60年代相比较,丽水涂膜柑橘贮藏最早烂果时间从3月第1候提前到2月第4候,而最晚时间从4月第4候提前到第1候。区划结果将为橘农合理安排柑橘贮存、及时进行贩销提供参考和科学依据,从而减少对柑橘贮藏品质的影响。     

中国地区集合预报产品自适应递减平均偏差订正法的改进研究

基于中国地区T213集合预报产品2 m温度预报数据,采用卡尔曼滤波类型的自适应递减平均法进行偏差订正处理,原方案在剧烈降温天气订正效果表现不理想。通过对递减平均参数w的重新构建得到改进的订正方案w(i,p)(i为站点信息,p为天气过程信息),在此基础上进一步优化对历史信息的有效提取,得到改进的方案w(i,p)相似法和w(i,p)统计法,并进行效果检验。结果表明:改进为包含空间和天气过程信息的函数w(i,p)后方案的订正效果得到不同程度的提高,其中24 h剧烈降温预报各成员预报均方根误差平均减小了0. 15℃;而进一步改进的w(i,p)统计法在当前几种剧烈降温预报中订正效果最优,其集合平均偏差与w(i,p)方案相比减小2. 54℃。