A comparative study of landslide susceptibility mapping using weight of evidence,logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin,China

The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six conditionally independent environmental factors, elevation, slope, aspect, distance from fault, lithology and settlement density, were selected as the explanatory variables that may contribute to landslide occurrence based on principal component analysis (PCA) and Chi-square test. The relation between landslide distributions and these variables was analyzed using the three models and the results then used to calculate the landslide susceptibility (LS). The performance of the models was then evaluated using both the highly accurate deformation signals produced by using the Small Baseline Subset Interferometric Synthetic Aperture Radar technique and Receiver Operating Characteristic (ROC) curve. Results show more deformation points in areas with high and very high LS levels, and also more stable points in areas with low and very low LS levels for the SVM model. In addition, the SVM has larger area under the ROC curve. It indicates that the SVM has better prediction accuracy and classified ability. For the interpretability, the WoE derives the class of factors that most contributed to landsliding in the study area, and the LR reveals that factors including elevation, settlement density and distance from fault played major roles in landslide occurrence and distribution, whereas the SVM cannot provide relative weights for the variables. The outperformed SVM could be employed to determine potential landslide zones in the study area. Outcome of this research would provide preliminary basis for general land planning such as choosing new urban areas and infrastructure construction in the future, as well as for landslide hazard mitigation in Bailong River Basin.     

重力方法研究河南区域构造及控煤作用

河南地区存在三个明显的重力异常区,与其区内三个次一级的构造分区相一致,其重力异常曲线的挤压扭曲特征、剪切平移特征、张性舒展特征分别对应构造挤压变形机制、平移剪切机制及变形拉张机制。这些变形受印支、燕山及喜马拉雅期三大构造运动控制,其中印支期剥蚀及沉降程度是构成现今煤层埋藏条件的重要因素,燕山期形成河南煤田的逆冲推覆型控煤构造,喜马拉雅期构造运动,最终确立了河南煤系的展布范围及赋存状态,这表明控煤模式是构造运动的结果。     

准噶尔盆地表层沉积物的稀土元素特征与物源指示

准噶尔盆地的新生代沉积的物质来源对认识中亚地区乃至全球气候环境演变、亚洲内陆干旱化以及粉尘输送路径等关键科学问题都具有重要的意义,但目前对盆地内沉积物的物质来源的研究还比较粗略。文章以准噶尔盆地内不同类型的表层沉积物为研究对象,通过对稀土元素特征的研究进一步探讨盆地内不同沉积的物质来源与相互联系。研究结果表明：准噶尔盆地不同区域表层沉积物的稀土元素含量（不含Y元素）变化较大,变化范围为55.54~194.44 μg/g;大部分样品的δCe值在0.95~1.05之间,未见明显的Ce异常,指示了盆地内整体干旱环境下较弱的风化成壤作用,而Eu异常和UCC标准化配分模式表现出的复杂变化,可能指示了准噶尔盆地表层沉积物物质来源的多源性。根据盆地内表层沉积物的稀土元素总量、配分模式以及δEu值表现出的不同特征,结合了盆地内的区域地形和盛行风向等要素,认为盆地东部的戈壁砂和周围山地的基岩碎屑物之间存在着一定的物源继承,同时强劲的西北风也为该地带来了来自盆地北部和中部的物质来源;北部的阿尔泰山碎屑物质是盆地北部戈壁砂和沙漠砂的主要物质来源,但戈壁砂表现出的Eu中度亏损和较高的ΣREE值可能代表着该区域还存在更为广阔的物源;盆地西部各类沉积物之间表现出的稀土元素特征的相似性表明该地缺乏外界物质的参与,物源具有明显的局域性;盆地南缘的沙漠砂和河流表层沉积物主要来源于天山碎屑物质经冰川磨蚀及寒冻风化等作用形成的粉砂粒级物质,但是该地的黄土在地形和风向的影响下表现出了复杂的物质来源,盆地中的沙漠、天山碎屑物质、盆地东部的戈壁砂,甚至于中亚广大荒漠区的粉尘都为黄土提供了部分物源。

     

地电阻率井下观测装置抗干扰能力实验研究

开展地电阻率深井观测系统对地面已知干扰源的抗干扰能力测试,对测试结果进行量化研究,分析地表电磁干扰对地电深井观测的影响程度,期望为将来地电深井方法的研究提供帮助.     

一种适合于红藻的总RNA提取方法

以5种红藻(条斑紫菜(Porphyra yezoensis),日本多管藻(Polysiphonia japonica),长心卡帕藻(Kappaphycus alvarezii),扇形叉枝藻(Gymnogongrus ftabelliformis),带形蜈蚣藻(Grate-loupia turuturu))为实验材料,为了获得高质量的总RNA,比较了Trizol法、试剂盒法、CTAB法和Trizol+纯化柱法。结果显示:Trizol+纯化柱法对5种红藻总RNA的提取均取得了良好的效果。经琼脂糖凝胶电泳检测,所提取的总RNA 28S、18S条带清晰明亮,无降解;A260/A280、A260/A230值均符合要求,表明提取的总RNA质量较好;利用提取的总RNA进行RT-PCR扩增actin基因的保守片段,能够获得约550bp的目的片段,进一步表明Trizol+纯化柱法是适合于红藻总RNA提取的方法。     

风浪槽内风浪外频谱谱形的一些特征

利用实验室风浪槽内测得的波面序列资料估计风浪外频谱。通过与实测风浪内频谱的比较,研究实测风浪外频谱的谱形特征,探讨海浪外频谱与内频谱的相似性问题。此外,还检验一种理论海浪外频谱。     

库车坳陷克拉2气田异常流体压力演化史

根据克拉2气田现今实测地层压力分析了异常高压发育的特征,并通过流体包裹体测试求取包裹体形成时期的古压力。计算结果表明:下白垩统和古近系库姆格列木群砂岩储层在距今8～6Ma(康村组沉积期末)时,古压力系数大致为1.09～1.18,发育过剩压力为4.6～9.6MPa的异常高压。在此基础上,以古、今压力数据为约束条件,利用数值模拟技术定量恢复出下白垩统与侏罗系异常流体压力的演化历史。研究发现:下白垩统储层流体压力经历了沉积型异常流体压力形成发展(白垩纪-库车组沉积期末)和沉积型异常流体压力萎缩—构造挤压型异常流体压力孕育(库车组沉积期末至今)两个阶段。康村组沉积早期沉积型超压开始出现,库车组沉积期末达到顶峰,过剩压力达40～50MPa;此后,在沉积型超压萎缩—构造挤压型超压孕育过程的耦合下,过剩压力曾降至25～30MPa,更新世起超压略有升高。侏罗系流体压力演化较为简单,吉迪克组沉积期开始出现超压,至库车组沉积期末达到高峰,此后异常高压逐渐萎缩。在克拉2气田的主要成藏时期(距今3～1Ma),烃源岩较储层具有更高的异常压力,源—储压力差为10～30MPa。     

A general-purpose parallel raster processing programming library test application using a geographic cellular automata model

A general-purpose parallel raster processing programming library (pRPL) was developed and applied to speed up a commonly used cellular automaton model with known tractability limitations. The library is suitable for use by geographic information scientists with basic programming skills, but who lack knowledge and experience of parallel computing and programming. pRPL is a general-purpose programming library that provides generic support for raster processing, including local-scope, neighborhood-scope, regional-scope, and global-scope algorithms as long as they are parallelizable. The library also supports multilayer algorithms. Besides the standard data domain decomposition methods, pRPL provides a spatially adaptive quad-tree-based decomposition to produce more evenly distributed workloads among processors. Data parallelism and task parallelism are supported, with both static and dynamic load-balancing. By grouping processors, pRPL also supports data–task hybrid parallelism, i.e., data parallelism within a processor group and task parallelism among processor groups. pSLEUTH, a parallel version of a well-known cellular automata model for simulating urban land-use change (SLEUTH), was developed to demonstrate full utilization of the advanced features of pRPL. Experiments with real-world data sets were conducted and the performance of pSLEUTH measured. We conclude not only that pRPL greatly reduces the development complexity of implementing a parallel raster-processing algorithm, it also greatly reduces the computing time of computationally intensive raster-processing algorithms, as demonstrated with pSLEUTH.     

Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series

ABSTRACT

Accurate runoff forecasting plays a key role in catchment water management and water resources system planning. To improve the prediction accuracy, one needs to strive to develop a reliable and accurate forecasting model for streamflow. In this study, the novel combination of the adaptive neuro-fuzzy inference system (ANFIS) model with the shuffled frog-leaping algorithm (SFLA) is proposed. Historical streamflow data of two different rivers were collected to examine the performance of the proposed model. To evaluate the performance of the proposed ANFIS-SFLA model, six different scenarios for the model input–output architecture were investigated. The results show that the proposed ANFIS-SFLA model (R² = 0.88; NS = 0.88; RMSE = 142.30 (m³/s); MAE = 88.94 (m³/s); MAPE = 35.19%) significantly improved the forecasting accuracy and outperformed the classic ANFIS model (R² = 0.83; NS = 0.83; RMSE = 167.81; MAE = 115.83 (m³/s); MAPE = 45.97%). The proposed model could be generalized and applied in different rivers worldwide.     

无人化时代反水雷装备体系构想

根据我国海洋方向面临的战略安全环境、建设“海上丝绸之路”的要求,我国的反水雷作战范围将延伸到第一岛链以外的海域,反水雷任务除了传统的近岸/ 近海反水雷任务,还增加了海峡反水雷、交通线反水雷以及海外基地反水雷等任务。 为了满足我国反水雷作战需求,结合国际上反水雷技术装备发展方向,用信息化改造、无人化拓展现有反水雷装备,构建无人化时代反水雷装备体系,形成能够在近岸、近海、中远海实施快速、安全、高效的反水雷作战能力。