暴雨型滑坡灾害因素分析及预测试验研究

针对暴雨型滑坡灾害预报预警服务的需要, 以江西为研究区域, 从暴雨型滑坡灾害形成机理及预测理论入手, 通过8个滑坡灾害易发点的监测试验, 系统地研究了大气降水对地下水位、孔隙水压力、滑坡土体应力及滑坡稳定性的影响, 探讨了植被覆盖与滑坡的关系。结果表明:滑坡稳定系数与降水量有较好的负相关关系, 当降水量增大时, 滑坡稳定系数减小, 且略滞后于降水量的峰值; 在其他因素一定的条件下, 地下水位升高, 滑坡稳定系数直线下降。经计算得到8个试验点促使滑坡复活的临界指标是24 h降水量为60~203 mm, 值域的变化与滑坡体的土壤结构、力学性质、植被覆盖程度和降水强度的时空分布等因素有关。     

暴雨型滑坡灾害形成机理及预测方法研究思路

暴雨型滑坡灾害形成机理和预测方法研究,在国内外仍是个难题和热点。本研究的总体思路是：以江西为研究区域,从暴雨型滑坡灾害形成机理及预测理论入手。通过8个滑坡灾害易发点的监测试验,系统地研究大气降水对地下水位、孔隙水压力、滑坡土体应力及滑坡稳定性的影响,探讨植被覆盖与滑坡的关系;根据历史资料,进行滑坡风险区划和暴雨型滑坡的时空分布特征分析;应用统计学和试验研究相结合的方法,提出滑坡体发生滑动的临界雨量指标;开发基于Web—GIS的暴雨型滑坡灾害预报预警业务系统,并进行业务试验。     

诱发陕西黄土高原地质灾害降水因子分析

利用1960-2006年陕西黄土高原地质灾害和降水资料,统计分析该区域诱发崩塌、滑坡地质灾害降水因子特征。结果发现：地质灾害发生次数与月平均降水量、前10d平均累积降水量、暴雨频次成正相关,与前10d的平均累积降水量的正相关性最高。降水强度为30～60mm／d时,地质灾害主要发生在次日和当日;降水强度在60mm／d以上时,地质灾害主要发生在当日。陕西黄土高原地质灾害属于多日降水诱发型,诱发崩塌、滑坡的连续降水以3d为主。连续降水累积量达75mm以上,崩塌大量发生;累积雨量达100mm以上,滑坡大量发生。     

降水与滑坡稳定性临界值试验研究

针对暴雨型滑坡灾害预报预警服务的需要,以江西为研究区域,建立了8个滑坡灾害监测点.通过监测试验,较系统地研究了大气降水对地下水位、孔隙水压力、滑坡土体应力及滑坡稳定性的影响;进行了大气降水、地下水位和滑坡稳定性的模拟,初步确定了江西省8个代表点促使滑坡复活的临界降水量指标,初步划分出江西省滑坡灾害预警降水量临界值.     

柳州市积涝过程模拟及灾害风险评估

利用柳州市暴雨积涝灾害仿真模型,对不同类型降水过程造成的积涝灾害进行了数值模拟,并对柳州市积涝灾害风险进行了初步的量化评估。结果表明:大暴雨以下降水,积涝灾害风险以Ⅰ级和Ⅱ级为主,降水量级达大暴雨以上时,出现Ⅲ级的积涝灾害达25%以上,当降水量R>150mm时,Ⅲ级达37%。积水深度实测值与模拟值绝对误差主要分布在20cm以内,大暴雨以下降水,误差值主要分布在10cm以内,随着降水强度增加,绝对误差值也随之增大。每年第一场暴雨造成的积涝灾害往往比模拟结果严重,而久晴转暴雨过程则相反。此模型对拓展城市灾害预报服务领域,开展城市暴雨积涝灾害风险量化评估具有一定的参考作用。     

上海中心城区暴雨内涝阈值研究

基于上海暴雨积水110报警数据和自动气象站逐小时降水数据,利用时空过程分析法研究了暴雨积水与降水强度以及累积雨量的关系,建立了中心城区暴雨内涝的阈值指标,结果表明,中心城区暴雨积水程度与1 h降水强度和2 h累积雨量密切相关。当降水强度达30~40 mm·h-1时,中心城区就会出现暴雨积水。当降水强度达50 mm·h-1、2 h累积雨量达70 mm时,暴雨积水会明显增多。相对于暴雨发生的时间,暴雨积水具有明显的滞后效应,一般滞后1~2 h。下垫面状况、人口和道路密度也影响到暴雨积水的发生。综合海拔高程、下垫面类型、排水管网等多因素,开展中心城区精细化的暴雨内涝风险情景模拟及灾害损失评估,是下一步的研究方向。     

伏牛山南坡生态变化对降水的影响

利用1958～2000年有代表性的周边县树木增减资料、1984年10月～1986年9月树冠对降水的截流观测资料及1950～1999年西峡县山洪资料,分析了伏牛山南坡森林覆盖率对降水的影响,结果表明森林覆盖率高的地区,平均年雨量值大;林区树冠和植被对降水的截流率在60%以上,植被越好,树林郁闭越大,山地的山洪和水土流失就越小,不但可减轻洪水灾害,而且蓄水于地下,以丰补欠,调节林区水分供应;西峡县因森林覆盖率的降低,山洪次数增加.因此,应治山造林,绿化荒山.     

伏牛山南坡生态变化对降水的影响

利用1958～2000年有代表性的周边县树木增减资料、1984年10月～1986年9月树冠对降水的截流观测资料及1950～1999年西峡县山洪资料，分析了伏牛山南坡森林覆盖率对降水的影响，结果表明：森林覆盖率高的地区，平均年雨量值大；林区树冠和植被对降水的截流率在60％以上，植被越好，树林郁闭越大，山地的山洪和水土流失就越小，不但可减轻洪水灾害，而且蓄水于地下，以丰补欠，调节林区水分供应；西峡县因森林覆盖率的降低，山洪次数增加。因此，应治山造林，绿化荒山。     

一基于Web-GIS技术的滑坡灾害预报预警业务系统

2004年开始在江西地质灾害易发区内建立了8个滑坡灾害监测点。通过定点监测试验、历史资料的统计分析和应用滑坡稳定性原理等方法,揭示了我国东部丘陵区降雨诱发滑坡灾害的形成机理。分析表明,降水对滑坡的诱发作用,不仅取决于当日雨量,而且与前期过程降水量有关,但前期各日雨量的影响程度是不相同的;饱和状态下的滑坡,其稳定性主要与滑坡的条块重量(W)和总的孔隙水压力与总的上浮压力之比(ru)有关。在监测试验和统计分析的基础上,建立了滑坡稳定性预报预警报的数学模型,确定了滑坡灾害发生时的降水临界值。应用Web-GIS技术,建立了滑坡灾害预报预警的实时业务系统。在近年来的预报服务中,多次成功地发布了滑坡灾害预报和警报,取得了明显的成效。     

地基微波辐射计资料同化对一次特大暴雨过程影响的数值试验研究

基于暴雨中尺度数值预报模式AREMv2.3和三维变分同化系统GRAPES-3DVAR,以2008年7月22日08时至23日08时发生在我国东部地区的一次特大暴雨过程为例,研究了荆州、咸宁、常德3部地基微波辐射计反演的相对湿度廓线资料同化对降水预报的影响。结果表明:1)同化荆州、咸宁、常德3部微波辐射计反演的相对湿度廓线资料后,模式对降水落区预报改进不明显,但对降水强度预报改进明显,24 h降水最大增幅为45 mm;2)分别同化荆州、咸宁、常德微波辐射计湿度廓线资料,降水强度模拟均有所改进,24 h降水最大增幅分别达到42、10、24 mm;3)单站及两站微波辐射计资料同化均对降水强度预报有所改善,但不及对3部微波辐射计资料同时同化的结果,这表明同化的中尺度水汽场信息越多,初始场的质量越高,降水模拟效果越好;4)对上述暴雨过程而言,荆州微波辐射计湿度廓线资料同化对降水强度预报改进贡献最大,常德站次之,咸宁站作用最不明显。     

云南降雨型滑坡县级预警雨量阈值分析

根据云南省华坪县滑坡灾害历史数据和同期气象站实测小时降雨资料,以滇西北的华坪县为例动态地计算了每次滑坡灾害的有效降雨天数和对应前期的有效降雨量;并应用主成分分析法对44场降雨型滑坡进行分析,结果表明间接前期雨量、发生雨量和激发雨量对诱发滑坡都有重要影响,得出诱发滑坡的降水有短时强降雨和长时低强度降雨两种类型。由此建立了含有两类降雨特点的华坪县I〖CD*2〗D（降雨强度〖CD*2〗历时）阈值曲线,并在此过程中提出了确定降雨历时D结束时刻的方法和有待进一步研究的问题。通过对华坪县滑坡预警雨量研究,为其他县级滑坡灾害预警雨量阈值的确定提供一种方法。     

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941     

山地风电场开发过程中水土流失相关问题研究进展

风力发电在提供清洁能源的同时亦带来了一定程度的水土流失和生态环境破坏。特别是山地风电场,由于其所在的山区土壤抗蚀性低,且植被破坏后恢复难度大,在开发过程中引起的水土流失问题尤为突出。回顾了山区风电场水土流失特点、影响风电场水土流失关键因子等方面的相关研究成果,并对其进行了总结。山区风电场水土流失具有地域不完整性及扰动多样性的特点,道路施工区、风电机组建设区是水土流失的重点区域;水土流失呈现时空分布不均性特点,水土流失时段主要集中在施工期,且流失剧烈阶段主要发生在每年的降雨集中期;降雨是影响风电场水土流失的关键因子,滑坡稳定性系数在降水期间急剧下降,降水入渗作用促进了边坡变形破坏向不利的一面发展,容易引起水土流失及边坡不稳;降雨侵蚀力指标与降雨量及雨强有关,按照获取气象资料的不同,目前主要采用月降雨量及日降雨量来分别估算降雨侵蚀力;在进行山区风电场水土流失强度预测时,将整个预测区域划分为4~6个单元,确定各预测单元工程扰动前、施工期、扰动后的土壤侵蚀模数,采用类比法结合数学模型法预测造成的水土流失量。     

Rainfall thresholds for the initiation of landslides in central and southern Europe

Summary We review rainfall thresholds for the initiation of landslides world wide and propose new empirical rainfall thresholds for the Central European Adriatic Danubian South-Eastern Space (CADSES) area, located in central and southern Europe. One-hundred-twenty-four empirical thresholds linking measurements of the event and the antecedent rainfall conditions to the occurrence of landslides are considered. We then describe a database of 853 rainfall events that resulted or did not result in landslides in the CADSES area. Rainfall and landslide information in the database was obtained from the literature; climate information was obtained from the global climate dataset compiled by the Climate Research Unit of the East Anglia University. We plot the intensity-duration values in logarithmic coordinates, and we establish that with increased rainfall duration the minimum intensity likely to trigger slope failures decreases linearly, in the range of durations from 20 minutes to ∼12 days. Based on this observation, we determine minimum intensity-duration (ID) and normalized-ID thresholds for the initiation of landslides in the CADSES area. Normalization is performed using two climatic indexes, the mean annual precipitation (MAP) and the rainy-day-normal (RDN). Threshold curves are inferred from the available data using a Bayesian statistical technique. Analysing the obtained thresholds we establish that lower average rainfall intensity is required to initiate landslides in an area with a mountain climate, than in an area characterized by a Mediterranean climate. We further suggest that for rainfall periods exceeding ∼12 days landslides are triggered by factors not considered by the ID model. The obtained thresholds can be used in operation landslide warning systems, where more accurate local or regional thresholds are not available.     

Duration and Seasonality of Hourly Extreme Rainfall in the Central Eastern China

Compared with daily rainfall amount, hourly rainfall rate represents rainfall intensity and the rainfall process more accurately, and thus is more suitable for studies of extreme rainfall events. The distribution functions of annual maximum hourly rainfall amount at 321 stations in China are quantified by the Generalized Extreme Value（GEV） distribution, and the threshold values of hourly rainfall intensity for 5-yr return period are estimated. The spatial distributions of the threshold exhibit significant regional diferences, with low values in northwestern China and high values in northern China, the mid and lower reaches of the Yangtze River valley, the coastal areas of southern China, and the Sichuan basin. The duration and seasonality of the extreme precipitation with 5-yr return periods are further analyzed. The average duration of extreme precipitation events exceeds 12 h in the coastal regions, Yangtze River valley, and eastern slope of the Tibetan Plateau. The duration in northern China is relatively short. The extreme precipitation events develop more rapidly in mountain regions with large elevation diferences than those in the plain areas. There are records of extreme precipitation in as early as April in southern China while extreme rainfall in northern China will not occur until late June. At most stations in China, the latest extreme precipitation happens in August–September. The extreme rainfall later than October can be found only at a small portion of stations in the coastal regions, the southern end of the Asian continent, and the southern part of southwestern China.     

从小时尺度考察中国中东部极端降水的持续性和季节特征

相对于日降水量,小时尺度降水资料可以更准确地反映降水强度并描述降水过程,因而更适用于极端降水阈值确定及其特性研究.利用广义极值分布估计中国321个站最大小时降水量的分布函数,确定了5a重现期的小时降水强度阈值.阈值的空间分布呈现出明显的地域差异,西北地区阈值偏低,华北地区、长江中下游地区、华南沿海地区和四川盆地西部地区为高阈值中心.取各站5a一遇极端降水事件对其持续性特征和季节特征进行分析,发现在沿海地区、长江流域和青藏高原东坡极端降水事件的平均持续时间较长(超过12h);中国北部地区持续时间较短.在具有较大海拔落差的复杂地形区,极端降水事件较平原地区更快地发展到峰值.华南地区4月就可有极端降水事件出现,而中国北方地区要到6月底才出现极端降水;全中国大部分地区的年最晚极端降水在8-9月,但沿海地区、大陆南端和西南地区南部的少数站点在10月以后仍有极端降水发生.     

A Probabilistic Prediction Model for Heavy Rain-Caused Landslides in the Chongqing Region

Landslide (or rockslide) is a geological disaster that is mainly induced by strong precipitation, among a number of other natural inducing factors. Based on 1615 landslide cases, a statistical analysis is performed to find the relationship among the landslide occurrence time, rainfall 0-10 days ahead, and probability of landslides over the Chongqing region. The results show that 1) strong rainfall-caused landslides occur mainly on the day it rains or 1-2 days after the heavy rain, and as time goes on, the likelihood of the disaster reduces rapidly; 2) the heavier the rainfall, the closer the landslide time is to the precipitation time.A concept of "effective precipitation" is thus developed, and a categorical prediction model for heavy rain-caused landslides is established. Tests show that for categories III, IV, and V landslides, the model forecast accuracy arrives at 29.9%, 75%, and 100%, respectively. This indicates that the categorized probabilistic prediction can serve as a warning for the landslide prevention and mitigation.