Probability Prediction Model for Landslide Occurrences in Xi’an,Shaanxi Province,China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall （IR） and antecedent effective rainfall （AER）. Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.     

A Regional-Scale Method of Forecasting Debris Flow Events Based on Water-Soil Coupling Mechanism

A debris flow forecast model based on a water-soil coupling mechanism that takes the debrisflow watershed as a basic forecast unit was established here for the prediction of disasters at the watershed scale.This was achieved through advances in our understanding of the formation mechanism of debris flow.To expand the applicable spatial scale of this forecasting model,a method of identifying potential debris flow watersheds was used to locate areas vulnerable to debris flow within a forecast region.Using these watersheds as forecasting units and a prediction method based on the water-soil coupling mechanism,a new forecasting method of debris flow at the regional scale was established.In order to test the prediction ability of this new forecasting method,the Sichuan province,China was selected as a study zone and the large-scale debris flow disasters attributable to heavy rainfall in this region on July 9,2013 were taken as the study case.According to debris flow disaster data on July 9,2013 which were provided by the geo-environmental monitoring station of Sichuan province,there were 252 watersheds in which debris flow events actually occurred.The current model predicted that 265 watersheds were likely to experience a debris flow event.Among these,43 towns including 204 debrisflow watersheds were successfully forecasted and 24 towns including 48 watersheds failed.The false prediction rate and failure prediction rate of thisforecast model were 23% and 19%,respectively.The results show that this method is more accurate and more applicable than traditional methods.     

黄河上游径流长期变化及趋势预测模型

分析了黄河上游唐乃亥以上流域年径流序列的长期变化特征，在此基础上将时间序列分析与随机离散过程理论相结合，提出了一个用于黄河上游径流变化趋势超长期预测的时间序列—Markov链辐合模型．应用表明，该模型兼具时间序列模型与Markov链模型的优点，既能预调总体趋势，又适合于波动性较大的随机序列变化．分析与计算结果表明，黄河上游径流目前正处于20世纪80年代末期开始的第5个枯水段的底部，未来10a内，黄河上游年径流量的变化将呈现一个震荡递增的趋势，但这期间的平均径流量仍将低于多年平均水平，     

沙三中亚期东营三角洲-滑塌浊积体系预测模型研究

沙三段中亚段沉积时期,东营凹陷物源供给充足,三角洲-滑塌浊积体系极为发育。研究发现,滑塌浊积岩厚度h（m）与三角洲前缘沉积特征（前缘厚度H（m）、砂岩百分含量x（%）、斜坡坡角a（°））以及浊积岩滑移距离s（m）可以建立定量关系。通过控制变量的方法建立单因素关系,即滑移距离s（m）与浊积体厚度h（m）呈负相关,且相关性高,作为主因素;砂体厚度H（m）、砂岩百分含量x（%）及斜坡坡角a（°）与h（m）呈正相关,作为子因素。利用灰关联分析法,计算各子因素相对于主因素的权重系数,确定灰关联系数,建立滑塌浊积岩厚度h（m）的定量预测模型:h=55.359Q1.522 3,Q=0.355s’+0.223x’+0.221H’+0.201a’（Q为综合评价系数,s’、x’、H’、a’分别表经过最大值标准化后的滑移距离、前缘砂体厚度、百分含量以及斜坡坡角数据）。     

总体最小二乘回归预测模型的方差分量估计

回归预测模型是对传统回归模型的进一步扩展,不仅涉及回归模型的固定参数估计,而且将模型预测纳入平差的部分内容,更加符合实际解算需求.针对在回归模型预测中经常出现待预测非公共点(自变量)含有观测误差和随机模型不准确的问题,基于EIV (errors-in-variables)模型提出了一种同时顾及所有变量观测误差的整体解法...     

焦作矿区底板突水预报模型

选取对突水有影响的地质因素，如构造、矿压、构造裂隙、断层断距、断层至突水点距离、隔水层厚度、水压等为自变量，以突水点及未突水点的这些资料为基础，用数量化理论（Ⅰ、Ⅱ）的方法，将定性变量数量化，并参与计算，建立了焦作矿区底板突水的定量预报模型。经检验表明，所建模型可靠，可用于实际预测     

隧道开挖地表沉降动态预测及影响因素分析

城市地铁隧道施工不可避免地对围岩产生扰动引起地表沉降,动态预测隧道开挖引起的地表沉降是确保地表建构筑物与隧道施工安全的重要基础。针对隧道施工过程中地表沉降难以准确动态预测的问题,在定义纵向开挖度系数? 的基础上,建立横向地表沉降动态预测模型。该模型能够描述同一监测位置沉降曲线随掌子面推进而不断变化的规律,实现施工现场沉降动态预测。结果表明：在特定约束条件下,该模型能够退化为Peck模型以及随机介质理论预测模型;通过现场施工验证了该动态预测模型的准确性与适用性;基于纵向开挖度系数? 将隧道沿纵向分为强烈、中度和轻度共3个影响段,较好地反映了开挖掌子面在不同位置对同一监测截面的影响程度;通过分析建筑物和隔离桩对地表沉降曲线的影响可知,建筑物与其附近地层呈现出协同变形、共同承载的特征,在隧道一侧添加地质钻隔离桩对该侧地表沉降值的减小程度可达71.9%。研究成果对滇中引水工程现场施工与类似工程具有一定指导和借鉴意义。     

均生函数—最优子集回归在高温极值预测中的应用

根据南京等城市1961年以来历年气温极值资料序列，采用均生函数—最优子集回归法设计的短期气候预测模型不但能较好地拟合历史实况，而互对未来l～5年的演变趋势也具有一定的预报能力。     

水资源环境与社会经济系统耦合发展的仿真模拟——以洞庭湖生态经济区为例北大核心CSCD

以洞庭湖生态经济区水资源环境与社会经济系统为研究对象,引入灰色关联度算法测度耦合状况,结合GM（1,1）模型预测演化趋势,并进行仿真模拟。研究表明：2004~2013年生态经济区水资源环境优于社会经济发展状况,但水资源条件对快速增长的社会经济发展产生的约束作用较为明显,水资源与生态环境危机正在进入潜伏期;10 a间系统耦合度较高,处于较为协调发展的磨合耦合阶段,耦合度呈现大幅攀升后回落趋势,进一步对2014~2023年状况预测证实经济发展对水资源环境呈现越来越显著的胁迫效应。研究表明,应着力提高水资源利用效益,缓解水资源经济系统矛盾,实现社会经济和水资源环境的协调发展。     

河南老和尚帽预查区资源量及靶区预测

老和尚帽预查区位于桐柏地区围山城金银成矿带以南,老湾金矿带以北,圈有大量1∶ 1万土壤地球化学衬值异常.在大调查桐柏地区银多金属调查评价项目中,以桐柏地区已探明银资源储量的8个矿床、矿点形成的银(衬值)异常为模型单元,采用矿床模型法,建立预测模型;然后对老和尚帽预查区40个预测单元(衬值综合异常)进行资源定量预测与靶区定位预测,确定了8个找矿靶区.经对确定的靶区进行初步查证,发现了矿体和矿化体,取得了一定找矿效果.