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。     

NUMERICAL PREDICTION OF AN EXTREME RAINSTORM OVER THE PEARL RIVER DELTA REGION ON 7 MAY 2017 BASED ON WRF-ENKF

An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm.     

Interannual and Decadal Changes in Tropospheric Ozone in China and the Associated Chemistry–Climate Interactions: A Review

China has been experiencing widespread air pollution due to rapid industrialization and urbanization in recent decades.The two major concerns of ambient air quality in China are particulate matter(PM) and tropospheric ozone(O_3). With the implementation of air pollution prevention and control actions in the last five years, the PM pollution in China has been substantially reduced. In contrast, under the conditions of the urban air pollution complex, the elevated O_3 levels in city clusters of eastern China, especially in warm seasons, have drawn increasing attention. Emissions of air pollutants and their precursors not only contribute to regional air quality, but also alter climate. Climate change in turn can change chemical processes, long-range transport, and local meteorology that influence air pollution. Compared to PM, less is known about O_3 pollution and its climate effects over China. Here, we present a review of the main findings from the literature over the period 2011–18 with regard to the characteristics of O_3 concentrations in China and the mechanisms that drive its interannual to decadal variations, aiming to identify robust conclusions that may guide decision-making for emissions control and to highlight critical knowledge gaps. We also review regional and global modeling studies that have investigated the impacts of tropospheric O_3 on climate, as well as the projections of future tropospheric O_3 owing to climate and/or emission changes.     

CWRF模式在中国夏季极端降水模拟的误差订正

利用1980—2015年6—8月我国逐日降水观测数据评估CWRF模式（Climate-Weather Research and Forecasting model）多种参数化方案对我国夏季日降水的模拟能力,并考察累积概率变换偏差订正法（CDFt）的订正效果。通过将广义帕累托分布（GPD）引入到偏差订正模型中,提出针对极端降水的累积概率变换偏差订正法（XCDFt）,检验和评估其对极端降水订正的适用性。结果显示:CWRF模式微物理过程选用Morrison-aerosol参数化方案组合对我国降水场的模拟较好,CDFt订正效果良好;XCDFt偏差订正模型能够较好地提取模式建模与验证时期变化信号,订正后相比订正前与观测极端降水的概率分布更为接近;经过XCDFt订正后华南、华中和华北地区20年一遇的极端降水重现水平较模拟值更接近观测值,可为CWRF模式提高极端降水的业务预测水平提供参考。     

应用线性合成概率方法探讨青藏高原北部地区强震趋势

基于周期谱分析基础上的线性合成概率预测方法,对青藏高原北部地区Ms≥7.0、Ms≥6.5强震进行了试验性研究,并利用其结果作为预测依据,对青藏高原北部地区强震趋势做了初步估计.利用该方法,本文还对东昆仑断裂带1900年以来的Ms≥7.0强震进行了研究.     

含部分晶须的钛酸锂的制备及其性能表征

L i4T i5O12是一种循环性能好、有很好的充放电平台、理论比容量较大、不与电解液反应的新型负极材料,研究探索以偏钛酸和碳酸锂为主要原料制备含部分晶须的尖晶石型晶型L i4T i5O12的一种方法。通过此工艺在1 000℃煅烧8 h后在样品中约20%的晶须出现,晶须的直径≤0.5μm,晶须的长度约为7μm。