Article(id=1276897215666852293, tenantId=1146029695717560320, journalId=1276577071032668183, issueId=1276897056350405403, articleNumber=null, orderNo=null, doi=10.13244/j.cnki.jiwhr.20240219, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730390400000, receivedDateStr=2024-11-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1782365619818, onlineDateStr=2026-06-25, pubDate=1779897600000, pubDateStr=2026-05-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782365619818, onlineIssueDateStr=2026-06-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782365619818, creator=13701087609, updateTime=1782365619818, updator=13701087609, issue=Issue{id=1276897056350405403, tenantId=1146029695717560320, journalId=1276577071032668183, year='2026', volume='24', issue='3', pageStart='261', pageEnd='428', issueExtLink='null', onlineDate='null', pubDate='1779897600000', pubDateStr='2026-05-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1782365581834, creator='13701087609', updateTime=1782367082282, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1276903349781926250, tenantId=1146029695717560320, journalId=1276577071032668183, issueId=1276897056350405403, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1276903349781926251, tenantId=1146029695717560320, journalId=1276577071032668183, issueId=1276897056350405403, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=333, endPage=342, ext={EN=ArticleExt(id=1276897217474597319, articleId=1276897215666852293, tenantId=1146029695717560320, journalId=1276577071032668183, language=EN, title=Risk analysis of flood and debris flow in the Zhenghe River Basin of Beichuan County in Sichuan Province, columnId=null, journalTitle=Journal of China Institute of Water Resources and Hydropower Research, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Flood and debris flow occur frequently in mountain streams - due to multiple factor such as landslides, loose solids, and heavy rainfall. Their carrying of sediment, rocks, driftwood, and other debris obstructs road embankment and bridge culverts, amplifying the magnitude of flood disasters and seriously troubling flood prevention efforts. Based on the investigation of flash flood and debris flow disasters in the Zhenghe River basin of Beichuan County in Sichuan Province and by combing the types of floods and the debris jam characteristics of culverts, the process of floods and debris flow, as well as the maximum flow depth and flow velocity characteristics under six disaster scenarios, are investigated using numerical simulation approach. The dynamic factor v2d (where v is the flow velocity and d the flow depth), is introduced as an index of the intensity of the external load acting on buildings or disaster-bearing bodies to divide floods and debris flow risk zones and determine the level of hazard. The findings demonstrate that there are significant differences in the spatial distribution of the maximum depth and flow velocity under the six simulation scenarios of flood and debris flow. The scenario of culvert blockage has the smallest difference between simulated and measured flood marks in mud depth. The hazard grades can well represent the actual degree of damage to buildings the amplification effect of flow and the diversion of the main flow caused by the blockage of road embankment and bridge culverts are the main reasons for the amplification of disaster-affected areas. The research results can provide an important reference for disaster prevention and reduction planning in mountainous areas, the assessment of building location and structural type, the selection of temporary safe evacuation sites, and potential risk investigation , etc.

, authors=null, authorsList=Zhuangxian TIAN, Dongya SUN, Xiekang WANG, Changzhi LI, Qiuling YAO, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, 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=1276897218678362581, articleId=1276897215666852293, tenantId=1146029695717560320, journalId=1276577071032668183, language=CN, title=四川省北川县正河流域山洪泥石流危险性分析, columnId=0, journalTitle=中国水利水电科学研究院学报(中英文), columnName=, runingTitle=null, highlight=null, articleAbstract=

受暴雨、松散固体物源、临河滑坡体等多因素影响,山区河流频繁发生山洪泥石流,其挟带的泥沙石块、漂木等杂物淤堵路基桥涵,常放大山洪灾害量级,严重困扰山洪灾害防御工作。本文以四川省北川县正河流域山洪泥石流灾害调查为基础,结合洪水类型和桥涵阻水特性,采用数值模拟方法探究了6种灾害情景的山洪泥石流过程、最大流深和流速特征,引入动力因子v2dv为流速,d为流深)作为建筑物承灾体外荷载作用强度指标,评估其危险性等级并划分山洪泥石流危险区域。结果表明,6种模拟情景的山洪泥石流最大流深和流速空间分布差异较大,桥涵堵塞情景下山洪泥石流模拟与实测洪痕泥深相差最小;危险性等级可较好表征建筑物实际受损程度;流量放大效应及路基桥涵堵塞壅水导致主流改道是灾害规模放大的主要原因。研究成果可为山区防灾减灾规划、建筑物位置和结构型式论证、临时转移避险点选择及隐患排查等灾害防治工作提供参考。

, authors=

田壮显(1999—),硕士生,主要从事防洪减灾研究。E-mail:

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田壮显(1999—),硕士生,主要从事防洪减灾研究。E-mail:

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田壮显(1999—),硕士生,主要从事防洪减灾研究。E-mail:

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Risk level of floods and debris flow

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v2d/(m3/s2山洪泥石流危险性等级破坏概率/%
毁坏严重破坏中等破坏轻微破坏基本完好
<10002476
1~<1005324814
10~<100323521120
≥100极高8551000
), ArticleFig(id=1276897227272491542, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=CN, label=表1, caption=

山洪泥石流危险性等级

, figureFileSmall=null, figureFileBig=null, tableContent=
v2d/(m3/s2山洪泥石流危险性等级破坏概率/%
毁坏严重破坏中等破坏轻微破坏基本完好
<10002476
1~<1005324814
10~<100323521120
≥100极高8551000
), ArticleFig(id=1276897227339600407, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=EN, label=Table 2, caption=

Simulation scenarios

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情景编号水流类型桥梁阻水特征
S1山洪洪水(清水)无桥梁
S2山洪洪水(清水)桥梁正常过流
S3山洪洪水(清水)桥梁阻塞
S4山洪泥石流无桥梁
S5山洪泥石流桥梁正常过流
S6山洪泥石流桥梁阻塞
), ArticleFig(id=1276897227427680792, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=CN, label=表2, caption=

模拟情景

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情景编号水流类型桥梁阻水特征
S1山洪洪水(清水)无桥梁
S2山洪洪水(清水)桥梁正常过流
S3山洪洪水(清水)桥梁阻塞
S4山洪泥石流无桥梁
S5山洪泥石流桥梁正常过流
S6山洪泥石流桥梁阻塞
), ArticleFig(id=1276897227490595353, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=EN, label=Table 3, caption=

CN numbers and Manning's roughness coefficients in the model

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土地利用类型不同水文土壤分组的CN数初值选取的CN糙率备注
ABCD
耕地62717881880.070水田、旱地等
草地49697977780.050天然草覆盖,超过10%
林地30557084850.090树木覆盖,植被覆盖超过30%
房屋建筑区77859092940.060居民地、厂矿、交通用地等
河道989898981000.035
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模型中CN数及糙率取值

, figureFileSmall=null, figureFileBig=null, tableContent=
土地利用类型不同水文土壤分组的CN数初值选取的CN糙率备注
ABCD
耕地62717881880.070水田、旱地等
草地49697977780.050天然草覆盖,超过10%
林地30557084850.090树木覆盖,植被覆盖超过30%
房屋建筑区77859092940.060居民地、厂矿、交通用地等
河道989898981000.035
), ArticleFig(id=1276897227649978907, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=EN, label=Table 4, caption=

The verification of the model simulation results

, figureFileSmall=null, figureFileBig=null, tableContent=
洪痕点

实测洪痕

流深/m

模拟流深/m误差/m
S1S2S3S4S5S6S1S2S3S4S5S6
平均绝对误差/m1.321.160.970.400.220.17
11.520.640.680.871.201.231.40-0.88-0.84-0.65-0.33-0.29-0.12
22.761.761.701.613.223.103.01-1.00-1.06-1.150.460.340.25
31.130.370.330.341.031.111.11-0.76-0.8-0.80-0.1-0.02-0.02
42.670.791.211.202.542.902.91-1.88-1.46-1.47-0.130.230.24
51.810.690.790.911.431.641.79-1.12-1.02-0.9-0.38-0.17-0.02
61.460.000.220.221.171.451.38-1.46-1.24-1.24-0.30-0.01-0.08
72.430.290.731.881.301.982.92-2.14-1.7-0.55-1.13-0.450.49
), ArticleFig(id=1276897227725476380, tenantId=1146029695717560320, journalId=1276577071032668183, articleId=1276897215666852293, language=CN, label=表4, caption=

模拟验证

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洪痕点

实测洪痕

流深/m

模拟流深/m误差/m
S1S2S3S4S5S6S1S2S3S4S5S6
平均绝对误差/m1.321.160.970.400.220.17
11.520.640.680.871.201.231.40-0.88-0.84-0.65-0.33-0.29-0.12
22.761.761.701.613.223.103.01-1.00-1.06-1.150.460.340.25
31.130.370.330.341.031.111.11-0.76-0.8-0.80-0.1-0.02-0.02
42.670.791.211.202.542.902.91-1.88-1.46-1.47-0.130.230.24
51.810.690.790.911.431.641.79-1.12-1.02-0.9-0.38-0.17-0.02
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四川省北川县正河流域山洪泥石流危险性分析
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田壮显 1, 2 , 孙东亚 1, 2 , 王协康 3 , 李昌志 1, 2 , 姚秋玲 1, 2
中国水利水电科学研究院学报(中英文) | 2026,24(3): 333-342
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中国水利水电科学研究院学报(中英文) | 2026 , 24 (3) : 333 -342
四川省北川县正河流域山洪泥石流危险性分析
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田壮显1, 2 , 孙东亚1, 2, 王协康3, 李昌志1, 2, 姚秋玲1, 2
作者信息
  • 1中国水利水电科学研究院,北京 100038
  • 2水利部防洪抗旱减灾工程技术研究中心,北京 100038
  • 3四川大学 山区河流保护与治理全国重点实验室,四川 成都 610065
Risk analysis of flood and debris flow in the Zhenghe River Basin of Beichuan County in Sichuan Province
Zhuangxian TIAN1, 2 , Dongya SUN1, 2, Xiekang WANG3, Changzhi LI1, 2, Qiuling YAO1, 2
Affiliations
  • 1China Institute of Water Resources and Hydropower Research , Beijing100038, China
  • 2Research Center on Flood and Drought Disaster Reduction , Beijing100038,China
  • 3State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University,Chengdu610065, China
出版时间: 2026-05-28 doi: 10.13244/j.cnki.jiwhr.20240219
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受暴雨、松散固体物源、临河滑坡体等多因素影响,山区河流频繁发生山洪泥石流,其挟带的泥沙石块、漂木等杂物淤堵路基桥涵,常放大山洪灾害量级,严重困扰山洪灾害防御工作。本文以四川省北川县正河流域山洪泥石流灾害调查为基础,结合洪水类型和桥涵阻水特性,采用数值模拟方法探究了6种灾害情景的山洪泥石流过程、最大流深和流速特征,引入动力因子v2dv为流速,d为流深)作为建筑物承灾体外荷载作用强度指标,评估其危险性等级并划分山洪泥石流危险区域。结果表明,6种模拟情景的山洪泥石流最大流深和流速空间分布差异较大,桥涵堵塞情景下山洪泥石流模拟与实测洪痕泥深相差最小;危险性等级可较好表征建筑物实际受损程度;流量放大效应及路基桥涵堵塞壅水导致主流改道是灾害规模放大的主要原因。研究成果可为山区防灾减灾规划、建筑物位置和结构型式论证、临时转移避险点选择及隐患排查等灾害防治工作提供参考。

山区河流  /  山洪泥石流  /  承灾体  /  路基桥涵  /  危险性评价

Flood and debris flow occur frequently in mountain streams - due to multiple factor such as landslides, loose solids, and heavy rainfall. Their carrying of sediment, rocks, driftwood, and other debris obstructs road embankment and bridge culverts, amplifying the magnitude of flood disasters and seriously troubling flood prevention efforts. Based on the investigation of flash flood and debris flow disasters in the Zhenghe River basin of Beichuan County in Sichuan Province and by combing the types of floods and the debris jam characteristics of culverts, the process of floods and debris flow, as well as the maximum flow depth and flow velocity characteristics under six disaster scenarios, are investigated using numerical simulation approach. The dynamic factor v2d (where v is the flow velocity and d the flow depth), is introduced as an index of the intensity of the external load acting on buildings or disaster-bearing bodies to divide floods and debris flow risk zones and determine the level of hazard. The findings demonstrate that there are significant differences in the spatial distribution of the maximum depth and flow velocity under the six simulation scenarios of flood and debris flow. The scenario of culvert blockage has the smallest difference between simulated and measured flood marks in mud depth. The hazard grades can well represent the actual degree of damage to buildings the amplification effect of flow and the diversion of the main flow caused by the blockage of road embankment and bridge culverts are the main reasons for the amplification of disaster-affected areas. The research results can provide an important reference for disaster prevention and reduction planning in mountainous areas, the assessment of building location and structural type, the selection of temporary safe evacuation sites, and potential risk investigation , etc.

mountain stream  /  flood and debris flow  /  disaster-bearing bodies  /  road embankment and bridge culvert  /  risk assessment
田壮显, 孙东亚, 王协康, 李昌志, 姚秋玲. 四川省北川县正河流域山洪泥石流危险性分析. 中国水利水电科学研究院学报(中英文), 2026 , 24 (3) : 333 -342 . DOI: 10.13244/j.cnki.jiwhr.20240219
Zhuangxian TIAN, Dongya SUN, Xiekang WANG, Changzhi LI, Qiuling YAO. Risk analysis of flood and debris flow in the Zhenghe River Basin of Beichuan County in Sichuan Province[J]. Journal of China Institute of Water Resources and Hydropower Research, 2026 , 24 (3) : 333 -342 . DOI: 10.13244/j.cnki.jiwhr.20240219
山区地形陡峭、地质条件复杂,受极端降雨和人类活动影响,山洪灾害事件频繁发生。山洪危险性是山洪灾害防御的重要基础信息1,一般用灾害发生的可能性和危害程度表达2。现有研究通常以降雨或洪峰流量的重现期表征灾害发生的可能性,以单个或多个危险性地学要素或水力要素特征值表征危险程度。地学要素表征危险性方法多以格网或小流域为单元,选择研究区的降雨量、坡度、植被覆盖、土壤质地与类型、土地利用等因子3-4,赋予各因子不同权重,采用层次分析、聚类法等5-6,通过叠加图层信息从而量化区域危险性,也常用统计模型、信息量模型、逻辑回归模型或几种方法耦合等方法7-9。水力要素表征危险性方法多以水文模型、水动力模型等手段10-12,分析水深、流速、流量、淹没范围、淹没时间等变量特征,并据此划分危险性等级。然而,山洪致灾常包括洪水与挟带泥沙、石块及漂浮物等固体物质的共同作用13,尤其是发生山洪泥石流或路基桥涵淤堵壅水等链生灾害14-15。地学要素可在较大空间尺度表征山洪危险性,但难充分体现具体成灾位置的致灾动力机制;水力要素可较好表征山洪洪水危险性,但对山洪引起的链生灾害考虑不足。上述两种方法对山洪泥石流桥涵淤堵链生灾害的危险性评估具有较大局限性。本文以四川省北川县正河流域山洪灾害为例,调查桥梁、河床质组成及洪痕等参数数据,基于HEC-RAS二维水动力16和泥石流模型17,构建了不同流体类型(清水、山洪泥石流)和桥梁阻水特征(无桥梁、桥梁正常过流、桥涵堵塞)的组合模拟方案,分析因桥涵堵塞引起的山洪泥石流流深、流速变化;通过实测数据验证了桥涵堵塞模拟方案的有效性;选取山洪泥石流强度指数v2d划分沿河区域危险性等级并分析其空间分布特征。
正河流域位于北川县西北部,集水面积156.63 km2,具有以下自然和社会特征属性:(1)河道比降大。河流发源于牛奔山以西南麓,源头海拔3968 m,全长22 km,河道宽10~20 m,纵比降6.25%。西北和东北部地势较高,东南部地势较低,流域呈V字形。(2)多暴雨。流域位于亚热带湿润季风气候区的西部边缘与高原气候交汇地带,处于龙门山暴雨区,暴雨集中、强度大。(3)固体物源丰富。流域位于后龙门山褶皱带,变质岩出露范围大、基岩破碎,受汶川大地震影响,松散固体物源和漂木丰富。(4)滑坡隐患多。调查表明,流域内有10个临河滑坡点(4个为中型,6个为小型)。(5)桥梁密集。研究区有7座桥梁,均在两河口至流域出口之间,多为小型桥梁,桥长20 m左右、净高5 m左右。(6)上游监测难度大。两河口五龙寨以上面积达127.93 km2,占流域总面积81.67%,为无人区,人迹罕至,交通条件差,雨量监测设施等难以部署和维护。(7)承灾体分散。两河口及以下面积28.7 km2,占流域面积18.33%,共有5个村组和1个集镇。流域内以旅游、林业、农业为主,沿河村镇及旅游点等是主要保护对象。受上述自然和社会因素影响,正河流域暴雨山洪强度大,致灾机理复杂,损失严重。例如,2022年8月18日夜至19日,正河流域普降暴雨,发生严重山洪泥石流灾害。山洪量大峰急,沟道松散物质和上游废弃漂木等杂物降低了河道行洪能力,致使山洪改道冲入居民区,加大了灾害规模,参见图1。流域内5栋房屋被整体冲走,泥石淤积房屋51栋,道路受损、通讯中断,直接经济损失1.06亿元。
山洪泥石流模拟采用HEC-RAS模型,以分析山洪泥石流过程最大流深和流速空间分布。
根据土壤水文分组(Hydrologic Soil Groups)和土地利用数据估计Curve Number(CN)参数,并通过SCS(Soil Conservation Service)18模型计算时段产流量q,从而满足以降雨作为输入条件展开水动力模型计算。径流量q计算方法如下:
q=P-Ia2P-Ia+S       P>Ia            0             PIa
Ia=rS
S=25400CN-25
式中:q为时段径流量,mm;P为时段降水量,mm;Ia为初损量,mm;r为初损率;S为潜在蓄水能力,mm;CN为径流曲线数。
采用二维浅水动力方程(SWE),进行全流域山洪模拟16。连续方程:
ht+(hu)x+(hv)y=q
动量方程:
ut+uux+vuy=-gZsx+1hxvxxhux+1hyvyyhuy-τb,xρh
vt+uvx+vvy=-gZsy+1hxvxxhvx+1hyvyyhvy-τb,yρh
式中:t为时间,s;Zsh为水位高程和流深,m;uvxy方向速度分量,m/s;q为时段产流量,m;ρ为流体密度,kg/m3g为重力加速度,m/s2vxxvyyxy方向水平涡黏系数,m2/s;τb,xx方向的基床剪切应力,Pa;τb,yy方向的基床剪切应力,Pa。
山洪泥石流在形成过程中,通常伴随河床和河岸的冲刷侵蚀,相较于山洪洪水,流量和流体性质发生了改变。本文在动量方程底部摩擦源项中增加泥石流剪切应力,并改变流体密度以反映山洪泥石流的非牛顿流体性质;将连续性方程的产流量q乘以膨胀因子BF,体现山洪泥石流固体物质对流量过程的放大作用。其中山洪泥石流摩阻计算采用O’Brien方程17,该方程考虑了山洪泥石流体积浓度、沙石粒径等重要参数,适用于较低屈服应力和黏度的流体,以x方向为例,山洪泥石流应力摩阻计算方法如下:
τ=τb+τmd
ρmd=Cvρs+1-Cvρw
BF=11-Cv
τmd,x=τy+μmdudy+ρmdlm2dudy2+0.01ρs0.615Cv13-12ds2dudy2
式中:τ为总剪切应力,Pa;τb为基床剪切应力,Pa;τmd为泥石流剪切应力,Pa;ρmd为泥石流混合密度,kg/m³;lm2为泥石流湍流长度尺度的平方,m²;μm为泥石流黏滞系数,Pas;τy为屈服应力,Pa;ρs为泥石颗粒密度,kg/m3Cv为泥石体积浓度,%;ds为泥石代表粒径,mm。
研究流域的桥梁多为小型桥梁,从流动面积中减去桥墩、桥台和桥面所阻挡的面积,并添加湿周,以计算桥梁引起的水力特征变化。对于桥涵堵塞过流计算,采用堰流公式。
山洪泥石流危险性主要体现在运动过程中对沿途建筑物的冲击、冲刷、淤积、淹没破坏19,多用流深20、流速21或其组合参数22-23表征山洪泥石流的破坏能力。Jakob等24对流速(v)、流深(d)、v2dvd2等4个强度参数与建筑物灾损程度的关系进行对比分析,认为选择v2d最具代表性。本文以v2d作为山洪泥石流危险性指标,以常用对数量化等级,并根据王甜恬25对四川地区砖混建筑物受泥石流破坏的样本数据,估计建筑物破坏概率,如表1所示。
采用当地雨量站实测典型降雨过程数据,见图2(a)
采用北川县河湖划界地形数据(空间分辨率2.0m),见图2(b)
采用2020年全国10m分辨率地表覆盖数据集(http://www.ngcc.cn/),见图2(c)
桥涵资料来源于北川县专业部门,主要包括桥宽、净深、桥长和桥梁地理位置。
山区河道洪水常伴有沙石输送,是具有不同固体颗粒含量的水流或流体,根据固体颗粒含量或流体性质,水流类型可能是清水、山洪泥石流、高含沙水流和泥石流中的一种。山洪泥石流触发机制主要分为三种:洪水挟带山洪沟砂石、砾石等固体颗粒形成山洪泥石流、泥石流演变成山洪泥石流和溃坝形成的山洪泥石流26-27。研究区受地震影响,大量树木枯枝、石块散落于沟道,山洪泥石流堵塞桥涵链生灾害频繁发生28。为此,本文考虑水流类型和桥梁阻水特征,对比分析六种山洪泥石流堵塞桥涵情景下的水力特征和破坏能力变化,如表2所示。
模型建立步骤如下:
剖分正河全流域网格,河岸、桥涵、道路等对象设置接缝线(Breaklines),沿河村落、集镇等区域设置细化区域(Refinement Regions),网格以四边形为主,一般地区10 m×10 m;对河道、桥梁、沿河村落、集镇等进行局部细化,网格尺寸2 m×2 m。
图2所示的2022年8月18日夜至19日典型降雨过程作为模型上边界条件,采用曼宁公式计算流域出口的流量水位关系曲线作为下边界条件,其主要参数水面比降根据流域出口河道比降估算,河道比降为0.03。
糙率与土地利用类型、地面粗糙程度、坡度及地表阻水特性相关。CN数作为SCS模型计算径流的重要参数之一,与土地覆盖类型、土壤渗透性和前期土壤湿润程度有关。表3为本研究流域土壤含水量中等状况下不同土地利用类型的糙率、CN参数取值29
根据桥面宽度、桥面高程、梁底高程、桥墩宽度等信息构建桥梁,并概化为相应的堰坝,模拟桥梁阻塞情景。
通过分析河床组成粒径30,泥石体积浓度Cv设置为30%、泥石代表粒径ds为400 mm。
图3给出了在图2典型降雨条件下正河流域沿河村落6个情境下的最大淹没水深和泥深。表明狭窄沟道行洪能力不足,各情境下均出现洪水漫溢或主流改道,左右岸均有建筑物被淹没。以正河村两河口组沿河居民区为例,水位涨幅随无桥梁、有桥梁、桥梁堵塞逐渐增大,受山洪泥石流流量放大作用影响,山洪泥石流淹没流深明显大于山洪洪水。
各情景模拟流深与2022年8月18日夜至19日洪水实测洪痕对比如表4所示。洪痕点位于桥涵上下游,处于桥涵壅水和主流改道影响范围内,桥涵堵塞情景下流深大于桥涵正常过流、无桥梁情景的流深,如洪痕点1、5、7;若洪痕点未在桥涵影响范围内,桥涵堵塞和桥涵正常过流情景流深相近,并大于无桥涵的流深,如洪痕点3、4、6;洪痕点距离桥涵下游很近时,因受桥涵堵塞影响主流改道,致使无桥涵流深大于桥涵正常过流、桥涵堵塞流深,如洪痕点2。模拟值与实测洪痕误差分析表明,山洪泥石流桥涵堵塞平均绝对误差最小,以山洪洪水计算值(S1、S2、S3)均比实测洪痕数据小,其中S1误差范围为-2.14~-0.76 m、S2误差范围为-1.70~-0.8 m、S3误差范围为-1.47~-0.55 m;山洪泥石流(S4、S5、S6)相较于山洪洪水计算,其误差明显减小,其中S4误差范围为-1.13~0.46 m、S5误差范围为-0.45~0.34 m、S6误差范围为-0.12~0.49 m。
图4给出了正河流域在不同模拟情境下最大流速分布。受河道局部地形变化影响,大于8 m/s的流速主要分布在河道纵坡突增段、窄宽段、急弯段。在桥梁阻水特征相同、上游来水特征不同情境下,就河道流速而言,因研究区为较低屈服应力和黏度的泥石流,且受泥石流的流量放大作用,泥石流流速大于山洪流速。对于桥梁阻水特征不同、上游来水特征相同的情境下,河道流速在桥梁影响范围内呈无桥梁、桥梁正常过流、桥梁阻塞逐步减小趋势。以正河村两河口组为例,上游左支流河道和沿河建筑物呈现不同的流速分布。结果显示,在S1和S3无桥梁情景下,河道流速较大,多在6~9 m/s,沿河建筑物流速较小,多在0.5~4 m/s。相比于无桥梁,在S2和S4桥梁正常过流情景下,河道流速减小,多在4~7 m/s,沿河建筑物处流速增大,多在2~6 m/s。在S3和S6桥梁阻塞情境下,河道流速相比于无桥梁和桥梁正常过流明显减小,多在1~4 m/s,沿河建筑物处流速明显增大,多在3~7 m/s。可见,受桥梁阻水影响,临近桥涵区域流速减小,水流改道增大了附近岸上建筑物处的流速,放大了危险性。
由上述淹没和流速分析可知,不同模拟情景下,流深、流速局部变化明显,各模拟情景均出现洪水漫滩或改道,其中 S6(山洪泥石流桥涵阻塞)情景模拟值与实测洪痕值误差最小。在本次模拟的“8.18”山洪泥石流事件中,当地居民已提前转移,无人员伤亡,但房屋受损严重。其中,正河村两河口组沿河建筑多以砖木和砖混结构为主,冲毁破坏4座、严重破坏3座,破坏形式以冲击和冲刷破坏为主,如图5所示(图中紫色标框的房屋均被冲毁,橙色表框房屋发生严重损坏)。结合山洪泥石流强度指数v2d,以S6模拟情景为例,分析建筑物的灾害破坏等级,如图6所示。结果表明,居民地多位于山洪泥石流高强度影响范围,部分区域处于极高范围;部分处于极高强度和完全处于高强度范围的沿河建筑物均被山洪泥石流冲毁,部分处于高强度的沿河建筑物发生严重损坏,山洪泥石流强度指数v2d可较好地表征建筑物的实际受破坏程度。
正河流域暴雨强度大,特殊流域几何特征和下垫面条件易发生山洪泥石流灾害,叠加桥涵堵塞壅水影响,致灾物理机制复杂。本文以小流域为单元,考虑山洪、泥石流、桥涵堵塞等致灾因素,分析了桥梁阻水程度和流体类型6种情景的山洪泥石流淹没深度、流速致灾分布特征。以沿河建筑物为承灾体,根据指数v2d划分了S6情境正河村两河口组的山洪泥石流强度等级,主要结论如下:
(1)山洪致灾因子多,在流域尺度分析洪水、沙石、桥涵等危险性因素影响,分析获取沿河集镇、村落位置等处淹没深度、流速等信息,进而分析和划分危险性等级,可较为全面地获得沿河区域危险性等级及其空间分布信息。
(2)山洪泥石流叠加桥涵堵塞将放大山洪灾害的影响范围和严重程度。以正河村两河口为例,虽然桥涵堵塞蓄水量不大,但它将导致主流改道,从而冲淹沿河房屋;且受泥石流的流量放大作用,导致沿河人口密集区的流深和流速进一步增大,可达2~3 m和3~7 m/s,显著增加沿河村落受灾程度。
(3)北川县正河流域山洪泥石流和桥涵阻塞情景下的模拟最大流深与实测洪痕较为吻合,平均绝对误差流深为0.17 m。根据山洪泥石流强度指数v2d的危险区等级划分结果,表明正河村两河口组多处高危险等级并于实际受灾情况基本一致,指数v2d可较好地表征沿河建筑物受山洪泥石流影响的危险性。

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doi: 10.13244/j.cnki.jiwhr.20240219
  • 接收时间:2024-11-01
  • 首发时间:2026-06-25
  • 出版时间:2026-05-28
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  • 收稿日期:2024-11-01
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    1中国水利水电科学研究院,北京 100038
    2水利部防洪抗旱减灾工程技术研究中心,北京 100038
    3四川大学 山区河流保护与治理全国重点实验室,四川 成都 610065
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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
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红菇属 Russula 17 8.13
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