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.     

Effect of freeze–thaw cycles on strength and ductility and microstructure of cement-treated silt with polypropylene fiber

Acta Geotechnica - In this paper, the strength, ductility and microstructure behavior of cement-treated silt with polypropylene fiber was studied by a host of experimental studies. The influence of...     

Sensitivity assessment of strontium isotope as indicator of polluted groundwater for hydraulic fracturing flowback fluids produced in the Dameigou Shale of Qaidam Basin

Hydrogeochemical processes that would occur in polluted groundwater and aquifer system, may reduce the sensitivity of Sr isotope being the indicator of hydraulic fracturing flowback fluids(HFFF) in groundwater. In this paper, the Dameigou shale gas field in the northern Qaidam Basin was taken as the study area, where the hydrogeochemical processes affecting Sr isotope was analysed. Then, the model for Sr isotope in HFFF-polluted groundwater was constructed to assess the sensitivity of Sr isotope as HFFF indicator. The results show that the dissolution can release little Sr to polluted groundwater and cannot affect the εSr(the deviation of the 87 Sr/86 Sr ratio) of polluted groundwater. In the meantime, cation exchange can considerably affect Sr composition in the polluted groundwater. The Sr with low εSr is constantly released to groundwater from the solid phase of aquifer media by cation exchange with pollution of Quaternary groundwater by the HFFF and it accounts for 4.6% and 11.0% of Sr in polluted groundwater when the HFFF flux reaches 10% and 30% of the polluted groundwater, respectively. However, the Sr from cation exchange has limited impact on Sr isotope in polluted groundwater. Addition of Sr from cation exchange would only cause a 0.2% and 1.2% decrease in εSr of the polluted groundwater when the HFFF flux reaches 10% and 30% of the polluted groundwater, respectively. These results demonstrate that hydrogeochemical processes have little effect on the sensitivity of Sr isotope being the HFFF indicator in groundwater of the study area. For the scenario of groundwater pollution by HFFF, when the HFFF accounts for 5%(in volume percentage) of the polluted groundwater, the HFFF can result in detectable shifts of εSr(ΔεSr=0.86) in natural groundwater. Therefore, after consideration of hydrogeochemical processes occurred in aquifer with input of the HFFF, Sr isotope is still a sensitive indicator of the Quaternary groundwater pollution by the HFFF produced in the Dameigou shale of Qaidam Basin.     

我国大风机理研究和预报技术进展

大风作为常见且影响严重的天气现象,可在各类天气系统和地形综合影响下产生。全面认识其机理和预报方法,对风灾防御和风能利用都有很大帮助。本文梳理了我国气象观测和业务预报关于大风定义、大风分布特征以及雷暴、台风等主要灾害性系统大风分布情况。之后简述雷暴、台风、冷空气等系统产生大风的机理,以及复杂地形下垫面的热力和动力作用对局地大风的影响,概括了不同系统大风预报技术的研究进展。最后总结大风研究现状和不足。     

百色气候变化特征及城市适应策略建议

利用气候观测数据分析表明,近60a来,百色出现了与全球气候变化背景一致的增暖变化,主要变化特征有:气温明显升高,年降水日数减少,冬季降水量增多,年日照时数减少;高温和干旱频率高,20世纪90年代以来暴雨日数偏多。与广西平均气候变化状况相比,百色的气候变化程度风险低于广西平均水平。预估到本世纪中期,百色气温仍将缓慢升高,干旱和强降水的强度可能加剧。建议科学规划,统筹协调,科学评估城市气候承载力,开展城市适应气候变化风险管理,提升生态气候环境监测及自然灾害预警应急能力,建设生态气候宜居城市。     

An Assessment of ENSO Stability in CAMS Climate System Model Simulations

We present an overview of the El Ni?o–Southern Oscillation(ENSO) stability simulation using the Chinese Academy of Meteorological Sciences climate system model(CAMS-CSM). The ENSO stability was quantified based on the Bjerknes(BJ) stability index. Generally speaking, CAMS-CSM has the capacity of reasonably representing the BJ index and ENSO-related air–sea feedback processes. The major simulation biases exist in the underestimated thermodynamic damping and thermocline feedbacks. Further diagnostic analysis reveals that the underestimated thermodynamic feedback is due to the underestimation of the shortwave radiation feedback, which arises from the cold bias in mean sea surface temperature(SST) over central–eastern equatorial Pacific(CEEP). The underestimated thermocline feedback is attributed to the weakened mean upwelling and weakened wind–SST feedback(μ_a) in the model simulation compared to observation. We found that the weakened μ_a is also due to the cold mean SST over the CEEP.The study highlights the essential role of reasonably representing the climatological mean state in ENSO simulations.     

近56a洛阳地区雾和霾气候特征及其气象要素分析

利用1961—2016年洛阳9个县(市)地面气象观测站的雾、霾日数及相关气象要素资料,采用统计学方法分析了洛阳地区雾和霾日数的时空分布特征及影响其产生的气象要素特征。结果表明:近56a来洛阳市平均年雾日数在20世纪80和90年代较多,21世纪初开始逐渐减少,但在2015—2016年明显增加;平均年霾日数以2013—2016年最多;雾和霾日数在冬季最多,夏季最少。2000—2016年洛阳市雾日数自北向南逐渐减少,霾日数则在西部多、东部少,全区霾日数较1981—2010年明显增加。对雾、霾日气象要素的分析表明,相对湿度越大雾出现的频率越高、能见度越低,浓雾发生时相对湿度一般都在90%以上;中度和重度霾发生时相对湿度主要集中在50%~79%。雾发生时气温主要在-4.0~4.0℃之间,中度和重度霾发生时,气温分别集中在0~15.0℃和0~8.0℃,轻微和轻度霾发生时气温分布范围较大,以0~10.0℃较为集中。雾和霾出现时风速大部分在3.0m·s^-1及以下,并且主要是来自东北、东东北风向区域。     

GRAPES区域集合预报两种侧边界扰动方法对比试验

中国气象局数值预报中心自2014年建立了区域集合预报业务系统,其使用的侧边界扰动由全球集合预报系统动力降尺度得到。为深入了解侧边界扰动对区域集合预报的影响,基于15 km水平分辨率的区域集合预报模式,使用动力降尺度方法和尺度化滞后平均法(scaled lagged average forecasting,SLAF)设计构造了两种侧边界扰动方案,并开展了2015年7月共6天的集合预报试验,利用集合均方根误差、集合离散度、连续分级概率评分、离群值、Brier Score及相对作用特征曲线面积等概率预报检验方法进行了多方面检验,分析了两种侧边界扰动方案对区域集合预报质量的影响。结果表明:动力降尺度侧边界扰动方案(DOWN)的扰动总能量在各垂直层次均大于SLAF方案,使得边界上前者的离散度大于后者,集合扰动增长更为合理;对于等压面要素和地面要素,DOWN方案的离散度、Outlier、CRPS等评分优于SLAF方案,反映了DOWN方案构造的侧边界扰动更加合理;在降水概率预报技巧方面,SLAF方案在评分上具有一定优势,但评分的提高没有通过显著性水平检验,因此认为两种方案对降水预报的改进基本相当。     

"九五"数字化地震前兆台站整体接入因特网的研究

介绍了如何将"九五"数字化前兆台站设备整体接人因特网,提供了一种非常简便、实用的整体接人方案.台站原来的构成模式没有改变,台网中心和台站熟悉的原工作方式得到了保留,实现了台站网络化的目标,使现有台网在因特网环境下能够正常运行.它能够与"十五"新建的前兆台网进行集成,便于整个台网的统一管理.     

鄂西-渝东地区热史恢复及烃源岩成烃史

根据鄂西—渝东地区镜质体反射率数据进行的热史恢复结果表明:该区在晚二叠世初期达到最高古热流(可达68~78mW/m²,地表热流),从晚二叠世初到现今古热流持续降低,在侏罗纪末期古热流平均为~54mW/m²(地表热流);鄂西—渝东地区中生界与新生界之间不整合面的剥蚀量可达1700~4000m。成烃史研究表明:鄂西—渝东地区志留系烃源岩在晚志留世—早二叠世进入生油高峰,在早-中三叠世进入生气期,中侏罗世晚期进入过成熟干气阶段,快速生烃时期是在晚志留世、二叠纪—中三叠世及早-中侏罗世;而二叠系烃源岩在早三叠世进入生油门限,于中-晚三叠世达到生油高峰,在中-晚侏罗世进入生气期,晚侏罗世晚期进入过成熟,快速生烃时期是在早-中三叠世及侏罗纪。