四川雅安市雨城区降雨诱发滑坡临界值初步研究

四川省雅安市雨城区位于四川盆地西部,素有"雨城"之称。地质灾害以滑坡为主,且有群发性、浅层、规模小、降雨诱发的特点。作者分析了雨城区大量历史滑坡和降雨量数据,结合雨城区滑坡发育特点,选择3日(72h)内发生2个以上滑坡的点作为统计分析样本,进行不同阶段降雨量耦合关系分析,应用滑坡前3日累计降雨量与3日前15日累计降雨量,建立了滑坡发生与降雨量的统计关系:在雨城区,当前期无降雨、3日累计降雨量达到70mm时,将有滑坡发生;15日累计降雨量达到339mm时,也将可能出现滑坡。     

基于WEB的浙江省降雨型滑坡预警预报系统

滑坡发生的最主要诱发因素是降雨.基于浙江省淳安、磐安、庆元和永嘉4个县的历史滑坡资料, 在研究降雨量、降雨强度和降雨过程与滑坡灾害的空间分布、时间上的对应关系, 建立起滑坡灾害时空分布与降雨过程的统计关系, 确定区域性滑坡的临界降雨量和降雨强度阀值的基础上, 开发出了降雨型滑坡预警预报系统, 其中采用临界降雨量模型和有效降雨量模型来进行预警预报.系统留给浙江省气象台一个传送数据的接口, 气象台将每天按时上传降雨数据, 数据保存在后台数据库MicrosoftSQLServer中.建成的系统能够自动获取数据库中的数据生成时间与降雨量实时曲线, 当降雨量达到降雨强度阀值时, 触发MAPGIS图件, 在Internet上发布区域预警预报信息, 并提供预警措施.      

降雨引发的兰州黄土滑坡时空规律分析和临界降雨量预测

开展降雨型黄土滑坡预警对于区域性防治滑坡具有重要意义。本研究在收集1985~2015年兰州市降雨型黄土滑坡历史数据的基础上,运用反距离权重插值(IDW)和核密度估算(KDE)方法揭示了降雨引发黄土滑坡的时空分布规律。该文基于统计学的基本原理,运用相关性和偏相关性等方法建立适合兰州市的有效降雨量模型。通过拟合有效降雨量与滑坡因子的线性回归关系,确定引发黄土滑坡的临界降雨量阈值,设定兰州市黄土滑坡的降雨量危险性预警等级。研究表明:(1)兰州市黄土滑坡灾害点沿着黄河及其支流沿岸分布,城关区滑坡点最多且呈环形分布,西固区次之,其他地区分布较少;(2)降雨是兰州市及其周边地区黄土滑坡的关键诱因,10d有效降雨量与滑坡因子均呈现显著正相关特性,其相关系数达到0.698;(3)依据10mm、20mm和40mm临界降雨量阈值将预警等级划分为低、中、高3个危险性等级。     

江西省滑坡与降雨的关系研究

对江西全省1973 年~2002 年间1 158个降雨型滑坡,从考虑滑坡所处地层岩性条件和坡向因素的角度,分析了江西省降雨型滑坡发生的概率与降雨的关系。从坡向因素角度分析,江西省有64 %的滑坡发生于阳坡,但降雨对于不同坡向的滑坡影响近乎相同,只是阴坡所需激发雨量和有效临界雨量较阳坡稍大3 %。6 d累计降雨量、14 d有效降雨量(有效降雨系数为0.82)、3 d累计降雨量和9 d累计降雨量分别是变质岩、岩浆岩、碳酸岩和碎屑岩类地层中发育的滑坡所对应的最相关的降雨因子。各岩类地层中发育的滑坡有80 %发生于降雨当日;岩浆岩、变质岩和碎屑岩类滑坡约12 %～14 %滞后于降雨发生,碳酸岩类滑坡有22 %滞后于降雨发生。滞后时间多为1～3 d,其中碳酸岩类滑坡滞后时间相对较短。这与降雨对不同滑体物质成分的渗透性能、岩土体强度弱化程度和速度等有关。     

四川雅安市雨城区降雨诱发滑坡研究

降雨是滑坡灾害的重要诱发因素之一。通过详细的地质灾害调查及地质灾害与降雨相关关系的研究,得出降雨对雅安雨城区地质灾害诱发作用的规律并进一步定量评价了诱发因素级别。研究发现,降雨量对滑坡的诱发因素可划分为4级,1d降雨量分级临界值分别为20mm、50mm和100mm,3d降雨量分级临界值分别为100mm、150mm和240mm。这一研究成果为雅安雨城区地质灾害预警预报提供了基础。     

降雨与滑坡灾害相关性分析及预警预报阀值之探讨

详细研究了深圳市降雨与滑坡的历史资料,对区域性滑坡与降雨量进行偏相关分析,与降雨强度进行相关分析以及与降雨时间进行了系统地统计分析。研究结果表明,（1）滑坡的活动1～4日的降雨量及一次降雨过程的降雨量偏相关系数较大,表明一次性降雨量达到或超过某一数值时区域性滑坡就可以出现;（2）暴雨尤其是大暴雨及特大暴雨与滑坡的关系非常密切,相关系数达0.8以上,大暴雨或特大暴雨具有直接触发滑坡的作用;（3）滑坡活动时间与季节性降雨相对应,季节雨量越多,滑坡亦越多;另外滑坡活动时间与暴雨、大暴雨相吻合或略滞后,滞后时间一般不超过4 d,暴雨的当天及次日发生滑坡的可能性最大。在此基础上,探讨了区域性滑坡发生的临界降雨量和降雨强度阀值。最后将滑坡灾害的地质模型与降雨模型耦合建立了滑坡灾害的空间预警预报区划指标和等级系统,为区域滑坡灾害发生的时间与空间预报预警提供了科学依据。     

重庆地区降雨型滑坡相关性分析及预报模型

整理大量重庆地区降雨诱发滑坡资料,对降雨因子、累积降雨因子、前期降雨衰减系数与滑坡发生与否及滑坡发生数量之间进行系统的相关分析。结果表明:(1)当日降雨量对滑坡的诱发作用最显著,当日最大小时降雨与当日降雨量高度相关;(2)据滑坡发生前日期增加,降雨因子与滑坡相关及偏相关系数随之降低,在据滑坡发生前3d之后已变得很小;(3)大范围滑坡一般在暴雨当日或滞后一天产生,仅有短时强降雨很难诱发大范围滑坡,还需要一定前期降雨量为基础;(4)累积降雨因子与滑坡因子间都显著相关,且随着累积降雨日数的增加,其相关系数先上升后下降;(5)重庆地区适宜的前期降雨衰减系数在0.6左右。在此基础上拟合出了有效累积降雨量-滑坡发生概率预报模型,并使用当日最大小时降雨量-滑坡发生概率模型对其进行修正。最后使用降雨诱发滑坡实例检验该修正模型,结果可为重庆地区降雨型滑坡的预测预报提供科学依据。     

有限元法分析降雨条件下斜坡稳定性——以邻水县马鞍坪滑坡为例

通过对华蓥市马鞍坪滑坡现有变形监测情况表明,斜坡变形位移与降雨的关系十分密切,马鞍坪滑坡的后部强变形区,斜坡位移与50mm以上持续降雨几乎呈对应关系。研究人员采用工程地质条件分析与有限元分析法相结合,对马鞍坪滑坡进行了滑坡体在降雨条件下饱和一非饱和渗流分析与坡体稳定性分析。分析结果表明,降雨量是华蓥山地区斜坡失稳下滑的主要引发因素,不同雨量决定斜坡演化成滑坡的不同阶段,其影响作用也不近相同。计算结果表明,当日降雨量达到150mm左右且累积降雨量超过300mm的情况下,斜坡土体将出现变形,出现滑坡可能性大。该分析结果为今后华蓥山地区地质灾害监测预警示范中的地质灾害单体预警预报,提供了可靠预警参数。     

降雨型滑坡失稳概率计算方法

为了解决滑坡风险评价中的滑坡失稳概率计算问题,利用前人在降雨阈值的研究成果,结合气象学中降雨概率分布理论,以云南省盐津县庙坝滑坡为例进行计算,建立降雨型滑坡失稳概率计算模型。结果表明,盐津县降雨型滑坡的降雨阈值类型为累积降雨量-历时关系阈值,即为单日降雨阈值,降雨阈值为29.7 mm;盐津县在当日降雨量达到或超过阈值水平时可能诱发滑坡,对滑坡影响的滞后天数最大为5天;庙坝滑坡在8月20—25日6天内单日降雨达到或超过29.7 mm的降雨概率为46.49%;庙坝滑坡在8月25日因前5天或当天单日降雨量超过29.7 mm而失稳的概率为0.2853%。     

基于“阶跃”变形特征的降雨型滑坡预警判据探讨

由于滑坡灾害的发生具有随机性和复杂性,经常给人们生活造成严重的经济损失,甚至威胁生命安全,故建立滑坡预警判据及模型是减小损失的重要手段。文章首先确定了有效降雨量-变形速率-改进切线角为降雨型阶跃滑坡的预警关键判据。然后运用斜率单变点法确定滑坡“阶跃”变形曲线上的“破坏拐点”和“稳定拐点”并提取变形加速区间的详细信息,以此求解有效降雨量-变形速率-改进切线角综合预警判据阈值。最后,结合麻池村1号滑坡各发展阶段宏观变形特征,将时空演化规律有机结合,建立了4级递进式综合判据分级预警模型。结果表明：麻池村1号滑坡的运移形式为牵引式,在降雨因素的激发下,累计位移曲线呈典型的“阶跃”变形特征;麻池村1号滑坡变形受前期降雨影响,前期降雨与当期降雨组成一个降雨过程的时间间隔阈值为10 d,“前期+当期降雨”模式下对应的降雨阈值分别为24 mm、 32 mm;基于监测数据精细化分析以及改进切线角法获取的麻池村1号滑坡的位移速率阈值为12 mm/d。研究可为此类型滑坡灾害的预警提供理论基础和技术指导。     

Examination of influences of rainfall patterns on shallow landslides due to dissipation of matric suction

The influences of rainfall patterns on shallow landslides due to the dissipation of matric suction are examined in this study. Four representative rainfall patterns including the uniform, advanced, intermediated, and delayed rainfalls are adopted. The results show that not only the occurrence of shallow landslides but also the failure depth and the time of failure are affected by the rainfall pattern. The different rainfall patterns seem to have the same minimum landslide-triggering rainfall amount. There is a rainfall duration threshold for landslide occurrence for a rainfall event with larger than the minimum landslide-triggering rainfall amount. For each rainfall pattern, the rainfall duration threshold for landslide occurrence decreases to constant with the increase of rainfall amount. The uniform rainfall has the least rainfall duration threshold for landslide occurrence, followed by the advanced rainfall, and then the intermediated rainfall. For each rainfall pattern, the failure depths and the times of failure from the same amount of rainfall with different durations could be largely different. In addition, the differences of the failure depths and the times of failure between various rainfall patterns with the same amount and duration of rainfall could be also significant. The failure depth and the time of failure, as compared with the occurrence of shallow landslides, are more sensitive to the rainfall condition. In other words, in comparison with the evaluation of the occurrence of shallow landslides, it needs more accurate rainfall prediction to achieve reliable estimations of the failure depth and the time of failure.     

The influence of rainstorm pattern on shallow landslide

In this study, the influence of the rainstorm pattern on shallow landslide is examined. The physically-based shallow landslide model is used to conduct this examination with considering four representative rainstorm patterns including uniform, advanced, central, and delayed rainstorms. The results show that in spite of the rainfall duration and the rainfall pattern, the rainstorm with less than the minimum landslide-triggering rainfall amount will not trigger landslide. However, for the rainstorm with greater than the minimum landslide-triggering rainfall amount, the occurrence of landslide significantly depends not only on the rainfall duration but also on the rainfall pattern. Among the four representative rainstorm patterns, the delayed rainstorm has the greatest rainfall duration threshold for landslide occurrence, followed by the central rainstorm, and then the uniform rainstorm. In addition, for each rainstorm pattern, the corresponding rainfall duration threshold for landslide occurrence decreases with the increase of rainfall amount, and seems to be constant for large rainfall amount.     

Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy)

Researchers have long attempted to determine the amount of rainfall needed to trigger slope failures, yet relatively little progress has been reported on the effects of climate change on landslide initiation. Indeed, some relationships between landslides and climate change have been highlighted, but sign and magnitude of this correlation remain uncertain and influenced by the spatial and temporal horizon considered. This work makes use of statistically adjusted high-resolution regional climate model simulations, to study the expected changes of landslides frequency in the eastern Esino river basin (Central Italy). Simulated rainfall was used in comparison with rainfall thresholds for landslide occurrence derived by two observation-based statistical models (1) the cumulative event rainfall–rainfall duration model, and (2) the Bayesian probabilistic model. Results show an overall increase in projected landslide occurrence over the twenty-first century. This is especially confirmed in the high-emission scenario representative concentration pathway 8.5, where according to the first model, the events above rainfall thresholds frequency shift from ~?0.025 to ~?0.05 in the mountainous sector of the study area. Moreover, Bayesian analysis revealed the possible occurrence of landslide-triggering rainfall with a magnitude never occurred over the historical period. Landslides frequency change signal presents also considerable seasonal patterns, with summer displaying the steepest positive trend coupled to the highest inter-model spread. The methodological chain here proposed aims at representing a flexible tool for future landslide-hazard assessment, applicable over different areas and time horizons (e.g., short-term climate projections or seasonal forecasts).     

滑坡降雨阈值模型的应用

在数字高程模型（DEM）的基础上,运用滑坡降雨阈值模型,以楚雄丁家坟一斜坡作为试验研究工点,结合现场勘察、监测数据以及斜坡岩土体主要特性、地形地貌、降雨强度与降雨持续时间、地下水位等因素,模拟斜坡单元产生潜在滑动时的临界降雨量,研究降雨对滑坡发生、分布的影响。研究结果表明：各斜坡单元产生潜在滑动时的临界降雨量各不相同,在不同的降雨量及地下水位条件下滑坡降雨阈值模型模拟的潜在滑坡位置主要位于楚勐公路下边坡处,与实际发生滑坡的位置吻合率达80%以上,滑坡降雨阈值模型可实现对斜坡稳定性进行可视化分析与预测,为降雨型滑坡提供一种有效的预测与分析方法。     

基于Logistic回归的陕南秦巴山区降雨型滑坡预测方法

通过建立陕南秦巴山区降雨型滑坡灾害数据库,分析了不同降雨因子的雨强分布,计算了降水突发型滑坡灾害、降水滞后型滑坡灾害的雨强与滑坡发生概率的相关系数,采用Logistic回归方法确定不同时效降雨因子,得到陕南秦巴山区降雨型滑坡预测模型,并利用滑坡灾害实例,运用ROC曲线和kappa系数法对模型进行了验证。结果表明：滑坡前第m日降雨量R_dm(m=0,1,2)及综合雨量R_c四个降雨因子为诱发降雨型滑坡较为显著的因子。当降雨强度≥75 mm·h^-1时,最易引起突发型滑坡;当连续降水达到2 d,且24小时雨量达到小雨或中雨时,应警惕滞后型滑坡灾害的发生。模型预测准确率达82.1%,ROC曲线的AUC值为0.836,kappa系数为0.616,验证结果显示该模型可靠。研究成果可作为陕南秦巴山区降雨型滑坡预报预警研究工作的重要参考。     

基于位移比模型的三峡库区云阳县域内蠕变型滑坡降雨预警

建立高效合理的区域滑坡灾害降雨预警模型对滑坡防治具有重要意义.然而以往的研究多侧重于临滑预警,对蠕变型滑坡在强降雨工况下的短暂加速变形的预警研究还有待深入.以三峡库区云阳县域内滑坡为例,首先根据滑坡地表位移监测数据的特点对统计样本进行合理筛选.再通过降雨因子与滑坡发生的相关性分析以及对滑坡在降雨条件下位移变化情况的数值模拟,确定了适用于不同时间阶段的降雨统计变量.然后将考虑了滑坡规模特征的滑坡位移比（累计位移与滑坡纵长之比）作为变形指标,分时段统计滑坡地表位移监测数据与历史降雨信息,建立了日降雨数据与月位移数据的对应关系,得到了可用于确定降雨量阈值的位移比模型,并获得了云阳县蠕变型滑坡的五级预警分区.最后分别选用研究区滑坡险情实例、长年位移监测数据及极端降雨事件对模型预警效果进行检验.结果显示基于专业监测数据的位移比模型的滑坡降雨预警结果与实际情况相符,可为蠕变型滑坡的预警预报提供依据.      

The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years.     

降雨诱发区域性滑坡预报预警方法研究

论文以四川省雅安市雨城区为研究区，将逻辑回归模型引入区域降雨型滑坡预警预报，建立了同时考虑降雨强度和降雨过程的降雨临界值表达式。在滑坡危险性区划的基础上，研究提出了区域降雨型滑坡预警预报指标，包括临界值降雨指数R和滑坡发生指数L，并利用20台自动遥测雨量计和地质灾害群测群防网络，采用历史记录雨量和预报雨量，建立了区域降雨型滑坡预报预警体系。