地震液化流滑震害

通过地震液化的震害调查,从土种类、地形条件和坡度、液化土壤的赋存状况、地震能量和流滑的时间与空间分布等方面,简要总结了液化流滑的震害特征和规律,初步分析了液化引起流滑发生的条件、规模、剧烈程度、坡体运动规律以及流滑产生的破坏形式,分析了影响流滑的因素,可供进一步研究等参考。     

泥石流灾情评估指标体系

泥石流灾情评估指标体系的建立应满足适用性、完备性、可比性、综合性和系统性原则,而指标的选取还应在一定的要求下确定。依据上述原则,在泥石流灾情网络分析结果的基础上,建立了评估指标体系的结构层次模型,进而对各类灾情评估指标进行了分析,确定出评估泥石流灾情的具体指标和因子。最后建立了以成灾度为目标层,经济损失,社会影响,环境损害为准则层。评估指标和评估因子为指标层的泥石流灾情评估指标体系。     

四川德昌县凹米罗沟泥石流成灾过程与危险性评价

论述了四川德昌县凹米罗沟泥石流孕育环境、形成条件和发生过程.泥石流的暴发是由短历时、强暴雨激发的.分析了泥石流危险度和活动趋势,并提出了相应的防治建议.     

泥石流的运动机理和减阻

野外调查研究发现,存在着两种具有不同动力学特征和机理的泥石流,粘滞性泥石流和两相泥石流,粘滞性泥石流由卵石、沙和粘土构成,难以区分固相和液相,为典型的非牛顿体,具有间歇性流动,“铺床现象”,高达60％的减阻和显著超高等流动特点,粘滞性泥石流的阻力远小于流变参数所代表的阻力,传统的利用本构方程研究阻力的方法不能解决问题,研究表明,其30％的减阻是由于铺床作用,另外20％－30％,是由于流动混合物充气所致,两相泥石流主要由粗颗粒物质构成,两相之间有明显的相对流动,显示较大的阻力和发生“石街”现象。粘滞性泥石流沟谷的中值坡度为0．16,两相泥石流阻力大,因而河谷的平均坡度较大（0．19－0．27）。     

大渡河上游八步里沟泥石流防治中的资源综合利用研究

八步里沟位于大渡河上游,沟口堆积扇为金川县城,历史上泥石流灾害严重。20世纪80年代以来,对泥石流灾害进行了综合治理,工程防治效果明显,通过近30a的演化,防治工程与泥石流灾害共同作用形成了独特的泥沙资源并进行了初步开发。分析了八步里沟的资源特征、综合开发利用的制约因素、开发与保护的优化配置以及进一步开发的空间等问题,发现拦砂坝库区的建材开发有效延长了工程运行年限,沟内种植经济林抑制了泥石流灾害,拦砂坝抬高沟床侵蚀基准面为小水电开发和灌溉提供了水头,经济发展与灾害防治形成良性循环,达到可持续发展的目的。为提高资源利用率,最大化发挥防灾工程的经济效益和社会效益,可进一步利用现有治理工程建立泥石流防治的科普基地,沟口堆积扇泥石流排导工程两侧设立限制开发区、建立生态公园,达到优化资源开发的目的。     

利用冲击力信号判断泥石流颗粒垂向分选的试验研究

分别提出根据冲击力数据的波动强度和峰值情况进行泥石流颗粒垂向分选研究的系统方法,并配置了三组不同容重(2 095 kg/m3、2 008 kg/m3和1 960 kg/m3)的粘性泥石流样品开展泥石流冲击试验。两种方法的分析结果基本一致,即容重为2 095 kg/m3的泥石流分选不明显,其他两组泥石流呈现出正粒序分布且容重越小分选越显著。量纲分析表明,开展的试验粘滞力在运动中起主导作用,颗粒之间作用力较小,不容易发生反粒序分选,这与通过冲击力分析颗粒垂向分选的结果一致,因此提出的利用冲击力信号判断泥石流颗粒垂向分选的系统方法具有适用性。     

农村社区自然灾害应急演练方法的初步研究——以四川省广元市马口村自然灾害应急演练为例

通过对2009年11月12日在四川省广元市三堆镇马口村举行的自然灾害应急演练进行初步的分析研究,总结出了从前期准备、正式实施到演练评估的农村社区自然灾害应急演练基本流程和方法。在马口村自然灾害应急演练的前期准备阶段,根据当地实际情况选择了滑坡、泥石流为演练的自然灾害背景,制定了3级响应演练模式,并细化了各级响应的启动标准。在演练的正式实施阶段,采用了参与式的演练方案设计方法,充分调动了当地群众的积极性。演练结束后在现场发放调查问卷,对演练进行了多方面、多角度的评估,演练基本达到了预定目标。     

新化县水车镇泥石流灾害研究

以湖南省新化县水车镇泥石流为研究案例,根据初勘、详勘资料,分析了该泥石流的形成条件,定量计算了相应的运动参数,预测了它的发展趋势,最后指出,生物工程〔植树造林〕防治措施在花岗岩残坡积层泥石流场地的适宜性尚有待商榷。     

山区铁路沿线泥石流泥位自动监测预警系统

泥位预警是泥石流灾害预警的方法之一,目前主要有接触式和非接触式泥石流泥位报警两种方法。探讨了一种便于安装、适合山区铁路沿线泥石流监测预警的接触式泥位自动监测预警系统的构建及应用方法。首先探讨了泥石流泥位监测系统的工作原理及其软件、硬件的组成,其次探讨了泥位预警阈值确定方法,最后根据现场试验观测情况及所遇到的问题提出了泥位监测系统的应用方法。该泥石流泥位监测预警系统能实现泥山区铁路沿线石流泥位信息数据采集和传输的网络化、实时化、自动化、数字化(可视化),并根据监测信息及时向铁路相关部门发出预警信号。     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.