Article(id=1307086654649426257, tenantId=1146029695717560320, journalId=1306274195778404443, issueId=1307086317918122434, articleNumber=null, orderNo=null, doi=10.12401/j.nwg.2025093, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734537600000, receivedDateStr=2024-12-19, revisedDate=1748102400000, revisedDateStr=2025-05-25, acceptedDate=1748188800000, acceptedDateStr=2025-05-26, onlineDate=1789563342964, onlineDateStr=2026-09-16, pubDate=1776614400000, pubDateStr=2026-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789563342964, onlineIssueDateStr=2026-09-16, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789563342964, creator=13701087609, updateTime=1789563342964, updator=13701087609, issue=Issue{id=1307086317918122434, tenantId=1146029695717560320, journalId=1306274195778404443, year='2026', volume='59', issue='2', pageStart='1', pageEnd='328', issueExtLink='null', onlineDate='null', pubDate='1776614400000', pubDateStr='2026-04-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789563262680, creator='13701087609', updateTime=1789616239746, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1307308519917638393, tenantId=1146029695717560320, journalId=1306274195778404443, issueId=1307086317918122434, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1307308519917638394, tenantId=1146029695717560320, journalId=1306274195778404443, issueId=1307086317918122434, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=153, endPage=160, ext={EN=ArticleExt(id=1307086656008380754, articleId=1307086654649426257, tenantId=1146029695717560320, journalId=1306274195778404443, language=EN, title=Research on the Geometric Characteristics and Formation Mechanism of Loess Collapse Based on UAV Aerial Survey and Numerical Simulation, columnId=null, journalTitle=Northwestern Geology, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In response to the complex formation mechanism of loess landslide disasters and the insufficient accuracy of traditional investigation methods, this study proposes a "space ground number" collaborative analysis method. The typical loess landslide body that occurred in Yangjiagou Town Industrial Park, Mizhi County on September 14, 2023, is taken as the research object. Three dimensional terrain data with centimeter level resolution is obtained through unmanned aerial vehicle aerial survey technology to reconstruct the geometric shape characteristics of the landslide body; Reveal the characteristics of controlling structural planes and stratigraphic combinations through on-site geological surveys. Based on the mixed finite element discrete element numerical simulation (Y-Mat), a dual scale model considering the real geometric shape and structural plane distribution is constructed. Through simulation, it is revealed that due to the influence of terrain and crack water conduction, the slope foot softens when encountering water, the strength decreases, and the upper loess body is pulled to deform. When the deformation accumulates to a certain extent, it collapses downwards along the original through water conduction cracks. During the falling process, some loess disintegrates and accumulates within a certain range of the slope foot, forming loess blocks and loose soil of different sizes, which impact the buildings at the slope foot and cause them to collapse. The research results can provide multi-source data fusion analysis methods and technical support for the study of the evolution mechanism of landslide geological hazards in the Loess Plateau.

, authors=Bo GAO, Gang LIU*, authorsList=Bo GAO, Gang LIU, authorCompany=null, correspAuthors=Gang LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2026 Northwestern Geology. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1307086660429177195, articleId=1307086654649426257, tenantId=1146029695717560320, journalId=1306274195778404443, language=CN, title=基于无人机航测与数值模拟的黄土崩塌几何特征及形成机制研究, columnId=1307086318673097157, journalTitle=西北地质, columnName=西北地区环境岩土工程问题研究, runingTitle=null, highlight=null, articleAbstract=

针对黄土崩塌灾害形成机制复杂、传统调查手段精度不足的问题,本研究提出"空–地–数"协同分析方法,以2023年9月14日米脂县杨家沟镇产业园区发生的典型黄土崩塌体为研究对象,通过无人机航测技术获取厘米级分辨率的三维地形数据,重构崩塌体几何形态特征;结合现场地质调查揭示控制性结构面与地层组合特征。基于混合有限元–离散元数值模拟(Y-Mat)构建考虑真实几何形态与结构面分布的双尺度模型,通过模拟揭示:受地形与裂隙导水影响,坡脚遇水发生软化,强度降低,牵引上部黄土体产生形变,形变累计至一定程度,沿原有贯通性导水裂隙向下崩落,下落过程中部分黄土发生解体,堆积于坡脚一定范围内,形成大小不同的黄土块体和散土,对坡脚房屋产生冲击,造成房屋倒塌。研究成果可为黄土高原崩塌地质灾害演化机制研究提供多源数据融合分析方法与技术支撑。

, authors=高波, 刘港*, authorsList=高波, 刘港, authorCompany=null, correspAuthors=刘港, authorNote=

高波(1981−),男,正高级工程师,从事地质灾害监测预警与风险评价研究工作。E−mail:

, correspAuthorsNote=
刘港(1990−),副研究员,博士,主要从事地质灾害调查与研究工作。E−mail:。
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高波(1981−),男,正高级工程师,从事地质灾害监测预警与风险评价研究工作。E−mail:

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高波(1981−),男,正高级工程师,从事地质灾害监测预警与风险评价研究工作。E−mail:

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Mechanical parameters of loess

, figureFileSmall=null, figureFileBig=null, tableContent=
单元类别物理力学参数黄土软化黄土裂隙
网格
单元
弹性模量(MPa)8.82.5—
泊松比(−)0.420.43—
密度(kg/m3)1.691.88—
内聚力(kPa)125—
内摩擦角(°)2518—
抗拉强度(kPa)136—
节理
单元
粘聚力(kPa)1255
最大静摩擦角(°)282121
滑动摩擦角(°)251818
残余摩擦角(°)151010
抗拉强度(kPa)1366
I型断裂能释放率(N/m)1002020
II型断裂能释放率(N/m)800160160
裂隙罚函数(Pa)2.6×1071.2×1071.2×107
法向接触罚函数(Pa)2.6×1071.2×1071.2×107
), ArticleFig(id=1307086666766770586, tenantId=1146029695717560320, journalId=1306274195778404443, articleId=1307086654649426257, language=CN, label=表1, caption=

数值模拟计算参数

, figureFileSmall=null, figureFileBig=null, tableContent=
单元类别物理力学参数黄土软化黄土裂隙
网格
单元
弹性模量(MPa)8.82.5—
泊松比(−)0.420.43—
密度(kg/m3)1.691.88—
内聚力(kPa)125—
内摩擦角(°)2518—
抗拉强度(kPa)136—
节理
单元
粘聚力(kPa)1255
最大静摩擦角(°)282121
滑动摩擦角(°)251818
残余摩擦角(°)151010
抗拉强度(kPa)1366
I型断裂能释放率(N/m)1002020
II型断裂能释放率(N/m)800160160
裂隙罚函数(Pa)2.6×1071.2×1071.2×107
法向接触罚函数(Pa)2.6×1071.2×1071.2×107
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基于无人机航测与数值模拟的黄土崩塌几何特征及形成机制研究
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高波 , 刘港 *
西北地质 | 西北地区环境岩土工程问题研究 2026,59(2): 153-160
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西北地质 |西北地区环境岩土工程问题研究 2026 , 59 (2) : 153 -160
基于无人机航测与数值模拟的黄土崩塌几何特征及形成机制研究
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高波(1981−),男,正高级工程师,从事地质灾害监测预警与风险评价研究工作。E−mail:

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高波 , 刘港*
作者信息
  • 自然资源部黄土地质灾害重点实验室,中国地质调查局西安地质调查中心,陕西 西安 710119
通讯作者:
刘港(1990−),副研究员,博士,主要从事地质灾害调查与研究工作。E−mail:。
作者简介:

高波(1981−),男,正高级工程师,从事地质灾害监测预警与风险评价研究工作。E−mail:

Research on the Geometric Characteristics and Formation Mechanism of Loess Collapse Based on UAV Aerial Survey and Numerical Simulation
Bo GAO , Gang LIU*
Affiliations
  • Key Laboratory of Loess Geological Hazards of the Ministry of Natural Resources, Xi'an Center of China Geological Survey, Xi'an 710119, Shaanxi, China
出版时间: 2026-04-20 doi: 10.12401/j.nwg.2025093
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针对黄土崩塌灾害形成机制复杂、传统调查手段精度不足的问题,本研究提出"空–地–数"协同分析方法,以2023年9月14日米脂县杨家沟镇产业园区发生的典型黄土崩塌体为研究对象,通过无人机航测技术获取厘米级分辨率的三维地形数据,重构崩塌体几何形态特征;结合现场地质调查揭示控制性结构面与地层组合特征。基于混合有限元–离散元数值模拟(Y-Mat)构建考虑真实几何形态与结构面分布的双尺度模型,通过模拟揭示:受地形与裂隙导水影响,坡脚遇水发生软化,强度降低,牵引上部黄土体产生形变,形变累计至一定程度,沿原有贯通性导水裂隙向下崩落,下落过程中部分黄土发生解体,堆积于坡脚一定范围内,形成大小不同的黄土块体和散土,对坡脚房屋产生冲击,造成房屋倒塌。研究成果可为黄土高原崩塌地质灾害演化机制研究提供多源数据融合分析方法与技术支撑。

无人机航测  /  黄土崩塌  /  几何特征  /  混合有限元离散元  /  形成机制

In response to the complex formation mechanism of loess landslide disasters and the insufficient accuracy of traditional investigation methods, this study proposes a "space ground number" collaborative analysis method. The typical loess landslide body that occurred in Yangjiagou Town Industrial Park, Mizhi County on September 14, 2023, is taken as the research object. Three dimensional terrain data with centimeter level resolution is obtained through unmanned aerial vehicle aerial survey technology to reconstruct the geometric shape characteristics of the landslide body; Reveal the characteristics of controlling structural planes and stratigraphic combinations through on-site geological surveys. Based on the mixed finite element discrete element numerical simulation (Y-Mat), a dual scale model considering the real geometric shape and structural plane distribution is constructed. Through simulation, it is revealed that due to the influence of terrain and crack water conduction, the slope foot softens when encountering water, the strength decreases, and the upper loess body is pulled to deform. When the deformation accumulates to a certain extent, it collapses downwards along the original through water conduction cracks. During the falling process, some loess disintegrates and accumulates within a certain range of the slope foot, forming loess blocks and loose soil of different sizes, which impact the buildings at the slope foot and cause them to collapse. The research results can provide multi-source data fusion analysis methods and technical support for the study of the evolution mechanism of landslide geological hazards in the Loess Plateau.

UAV aerial survey  /  loess collapse geometric features  /  mixed finite element  /  discrete element method  /  formation mechanism
高波, 刘港. 基于无人机航测与数值模拟的黄土崩塌几何特征及形成机制研究. 西北地质, 2026 , 59 (2) : 153 -160 . DOI: 10.12401/j.nwg.2025093
Bo GAO, Gang LIU. Research on the Geometric Characteristics and Formation Mechanism of Loess Collapse Based on UAV Aerial Survey and Numerical Simulation[J]. Northwestern Geology, 2026 , 59 (2) : 153 -160 . DOI: 10.12401/j.nwg.2025093
众所周知,黄土是一种典型的第四纪松散沉积物,垂直节理发育,干燥时结构稳定;湿润时结构松散,易发生崩塌、滑坡等地质灾害(曲晨飞等,2025;王新刚等,2025)。人类工程活动中,建房或筑路常以切坡方式开展。切坡打破了其原有应力平衡,应力释放回弹导致卸荷裂隙发育,在降雨入渗及冻融等因素的加持下,卸荷裂隙向外不断拉张,水沿裂隙入渗,裂隙面结构强度衰减,叠加重力的作用,易形成黄土崩塌、滑坡地质灾害(王家政等,2025;于国强等,2025;张文铎等,2025),严重威胁黄土高原区居民生命财产安全。针对黄土崩塌成因机制,前人做了大量且富有成效的工作。王根龙等(2011)提出了黄土崩塌的4种破坏机制,通过数值模拟再现和分析了延安黑龙沟黄土崩塌;叶万军等(2013,2014)阐明了黄土崩塌形成内因、外因并根据黄土崩塌常见的运动形式,提出崩塌体自由飞落及滚动情况下影响范围的理论公式;张宇宇(2016)以延安宝塔区典型黄土崩塌为研究对象,通过试验测试及理论分析研究了降雨作用下黄土崩塌形成的机理;成玉祥等(2021)以陕北黄土丘陵区崩塌灾害为例,统计分析厘定出溯源侵蚀作用引发崩塌的典型类型为拉裂–倾倒型,并分析了其形成机制;刘知等(2023)提出了晋西黄土崩塌的主控因素分类和变形破坏方式分类,并探索了滑落式黄土崩塌与黄土滑坡的界定条件。黄土高原区复杂的地形使得在野外人力调查变得困难,随着无人机航测技术的发展,依靠这些新技术对黄土崩滑灾害的研究越来越多。彭大雷(2018)以甘肃永靖黑方台为例,通过无人机航测结合现场调查,查明了滑坡区工程地质条件,厘清了黄土滑坡主要类型,揭示了滑坡发育分布规律,提出了4类黄土滑坡致灾模式毛正君(2022,2024)以宁夏彭阳县红河镇为例,构建了无人机航摄系统,确定了识别标志,结合现场确定了180处滑坡,并分析研究了滑坡空间分布、孕灾地貌等;刘军(2023)以延安市赵家岸滑坡为例,采用无人机航测技术获取了高分辨率滑坡影像,生成了滑坡空间几何数据,并结合层次分析和危险度计算方法评价赵家岸滑坡的危险性;邵建鸿(2023)基于人工巡查的局限性,提出了一种基于无人机倾斜摄影测量技术实现三维重建和点云数据分析的公路黄土边坡坡面病害巡查防范;刘宽富等(2023)以甘肃环县披覆型黄土高边坡为对象,建立了一种基于无人机倾斜摄影测量技术的数值模型构建方法。笔者以米脂杨家沟黄土崩塌为研究对象,针对黄土崩塌灾害形成机制复杂、传统调查手段精度不足的问题,提出“空–地–数”协同分析方法,分析了崩塌的几何特征并阐明了其形成机制,以期为区内黄土崩塌的研究提供实践参考。
2023年9月14日凌晨,陕西省榆林市米脂县杨家沟产业园区发生黄土崩塌灾害(崩塌点坐标:E 37°44′26.93″,N 110°19′28.52″),摧毁房屋3间,导致2人遇难。崩塌点原始微地貌为人工切坡,东侧为2级淤地坝,淤地坝内种植玉米等农作物,西侧为产业园区人工切坡(五级),斜坡坡面侵蚀严重,坡面发育多条冲沟,崩塌体北侧为一较大冲沟,坡面植被覆盖较好,坡脚处建筑为产业园区工人宿舍。崩塌体主要岩性为第四系上更新统马兰黄土,节理裂隙发育且具有一定导水性。崩塌点所处杨家沟镇位于米脂县东南部,区内地貌为典型的黄土高原丘陵沟壑地貌,地势起伏,上峁下梁,峁小梁短,区内地表大部被第四系黄土层覆盖,厚度较大。区内年降水量变化较大,多集中在7~9月,地下水主要受大气降水补给。区内沟谷发育,切割强烈,地形破碎,降雨入渗,斜坡松散层土体含水量的变化,直接影响斜坡的稳定性(图1)。
崩塌发生后,现场使用DJI MAVIC3无人机进行了航空摄影测量。基于无人机获得的航拍照片,使用大疆智图软件生成DOM数据和DEM数据(图2),坡度分布显示,这次崩塌的后壁近乎直立,接近90°;而堆积物的坡度相对较缓,大约为30°。
2023年9月14日拍摄的崩塌发生后航拍照片(图3b),地面分辨率为0.04 m。崩塌前图像来自吉林一号卫星影像,拍摄于2021年11月4日,分辨率分别为0.75 m(图3a)。崩塌后图像清晰地显示了崩塌体边界,崩塌方向大致为EW向。
根据无人机航摄数据三维重建(图4c)和现场调查,分别划定了崩塌物源区、崩塌堆积区,面积分别为13.74 m2、220.42 m2(图4a)。崩塌源在平面上呈直线形态,立面成三角面状,上窄下宽。平均倾角为80°,主崩方向为270°,垂直高度约为18.81 m,崩塌体长(L)为20.02 m,宽(W)为12.60 m,平均厚度(H)为2.5 m,面积(S)为220.42 m2,体积(V)为496.09 m3。崩塌体长宽比(L/W)为1.59,反映该崩塌总体运移优势方向为崩塌体长轴方向即为W向,宽厚比(W/H)为5.04,反映目前崩塌堆积体较为稳定,面积体积比(S/V)为0.44,反映该崩塌体破碎程度一般。
崩塌源存在明显的垂直节理,且崩塌后壁土体颜色明显深于其他部位,表现为土体含水量明显高于其他部位。崩塌堆积物沿坡脚不均匀分布,其中堆积前缘较为平缓,坡度为15°~30°,堆积区前部以土体为主,后部以大块土体碎屑为主,堆积体厚度由前部向后部逐渐增加,最大厚度约为7 m(图4b)。现场调查结果及崩塌体规模显示,该崩塌为一处典型的小型黄土崩塌。
就本次崩塌灾害而言,现场调查,崩塌后壁近直立,垂直节理发育,坡体下部颜色较上部深,触摸较潮湿,说明坡体下部处于长期湿润状态(图4b)。根据米脂县降雨量国家台站记录,2023年降雨量为453.80 mm,主要集中在4~10月(图5)。其中,9月累计降雨为71.6 mm,9月8日降雨量为30.40 mm,为最大单日降雨量;除9月11日降雨0.1 mm,9月10日至9月14日无降雨(图6)。结合崩塌点所处冲沟发育的梁峁地形综合分析可知,本次黄土崩塌发生主要受降雨导致,9月8日30.4 mm大雨,降雨随坡体北侧冲沟及坡体垂直节理下渗,聚集于坡脚,导致坡脚处黄土结构软化,强度降低,在自身重力影响下发生累进性变形,直至发生顺节理面坠落式破坏。
为了进一步精细刻画该黄土崩塌变形破坏过程,采用数值模拟开展分析。
杨家沟产业园区黄土崩塌模拟采用混合有限元离散元程序Y-Mat,其理论基础是混合有限元-离散元算法(FDEM),将有限元与离散元相耦合而集成二者优点。采用有限元方法计算模型中连续体的变形,利用离散单元方法计算模型中非连续体的变形,并且通过无厚度节理单元实现模型由连续向非连续的转变,从而实现计算模型的大变形和破坏模拟。采用该算法的优势在于其能够捕捉或再现崩塌完整土体开裂到离开母体再到运移堆积全过程,其基本原理实现如图7所示。其运动控制方程为:
$ MV+CU-f_{\mathrm{int}}(x)-f_{\mathrm{ext}}(x)-f_{\mathrm{c}}(x)=0 $
式中:M是集中质量矩阵,为对角线阵;C是粘滞阻尼矩阵,为对角线阵;V、U和x分别为节点的加速度、速率和位移;fint是内部作用力,包括弹性变形力、节理单元的粘结力等;fext是施加的外力;fc是接触力。
根据灾前的遥感影像数据和灾后现场调查数据,将杨家沟崩塌的原始地形进行还原概化,并进行网格剖分,获取其主剖面形态(图8)。经过调查,崩塌体主要岩性为第四系上更新统马兰黄土,节理裂隙发育且具有一定导水性,坡脚部分土体发生软化。
该崩塌体黄土属砂黄土,根据现场取样开展力学实验测试结果,确定本次模型的模拟参数,并通过标定,确定微观参数数值(表1)。
本次模型左边界、右边界和下边界均固定法相位移,上边界和斜坡表面为自由边界,边界上无外部卸载施加,整个模型受重力影响。
模拟开始前,在崩塌斜坡上设置4个监测点,分别位于崩塌体顶部、中部和坡脚,作为对照,在斜坡发育裂隙的另外一侧(相对稳定区域)设置1处监测点,位置和编号如图8所示。经过模拟计算,得到该崩塌的变形破坏过程(图9)。结果显示(图9),受地形与裂隙导水影响,坡脚遇水发生软化,强度降低,牵引上部黄土体产生形变,形变累计至一定程度,沿原有贯通性导水裂隙向下崩落,下落过程中部分黄土发生解体,堆积于坡脚一定范围内,形成大小不同的黄土块体和散土,对坡脚房屋产生冲击,造成房屋倒塌。
黄土崩塌剪切应力云图(图10)显示,无论是崩塌发生前、崩塌过程还是崩塌发生后,坡脚始终是剪应力集中带。崩塌发生前,坡脚因坡型而出现应力集中现象,当该部分土体湿润或饱和后,坡脚土体将会被部分挤出,坡体随之发生大变形乃至破坏。崩塌发生时和发生后,应力快速调整,坡脚仍是剪应力集中区,指示黄土斜坡稳定性评估不仅要关注裂隙,还要关注坡脚土体含水率或强度变化。
模拟过程中记录4个监测点的位移变化(图11)。监测点1和监测点4位于坡顶,根据位移历时曲线,监测点1所在位置的竖向位移明显大于水平位移,具有显著的坠落式崩塌特点,与现场调查相符,作为对照,监测点4因未发生崩落,变形相对较小。监测点2和监测点3位于坡中和坡脚,坡中黄土首先以竖向位移为主,待滑至坡脚后转为以水平位移为主,坡脚黄土发生水平运动的时间和最终数值均大于其他部位。
(1)基于野外调查及无人机航测,杨家沟产业园区崩塌物源区、堆积区,面积分别为13.74 m2、185.93 m2,主崩方向为270°,垂直高度约为18.81 m,最大崩落距离为20.02 m,崩塌堆积体积为496.09 m3,崩塌体长宽比(L/W)为1.59,宽厚比(W/H)为5.04,面积体积比(S/V)为0.44,为典型小型黄土崩塌。
(2)特殊的黄土沟壑地貌、疏松的土体结构、发育的垂直节理及持续的降雨等因素是造成杨家沟产业园区黄土崩塌发生的重要原因,特别是崩塌发生前一周即9月8日持续中雨是其重要诱发因素。
(3)基于混合有限元离散元模拟分析崩塌变形破坏过程:受地形与裂隙导水影响,坡脚遇水发生软化,强度降低,牵引上部黄土体产生形变,形变累计至一定程度,沿原有贯通性导水裂隙向下崩落,下落过程中部分黄土发生解体,堆积于坡脚一定范围内,形成大小不同的黄土块体和散土,对坡脚房屋产生冲击,造成房屋倒塌。
(4)为了避免再次发生类似惨剧,针对区内同类型黄土斜坡,需采取以工程排水为主的综合防控措施,降低其威胁程度。

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2026年第59卷第2期
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doi: 10.12401/j.nwg.2025093
  • 接收时间:2024-12-19
  • 首发时间:2026-09-16
  • 出版时间:2026-04-20
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  • 收稿日期:2024-12-19
  • 修回日期:2025-05-25
  • 录用日期:2025-05-26
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作者信息
    自然资源部黄土地质灾害重点实验室,中国地质调查局西安地质调查中心,陕西 西安 710119

通讯作者:

刘港(1990−),副研究员,博士,主要从事地质灾害调查与研究工作。E−mail:。
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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