两类经典滑坡发生时间预报模型的理论分析

老化和应变速率对土体强度和变形性质的影响研究,以及野外事例观察,已经证实大多数滑坡的形成机制可以由深部蠕变理论解释.土体蠕动速率在滑坡爆发之前将随着造成滑坡因素的增加而增加.根据这一理论,人们可以建立早期滑动的唯象蠕变方程来预测滑坡.早期的这类代表模型是Saito模型和Voight模型.本文重新进行的理论分析表明:这些模型具有丰富的理论内涵和深入的理论基础,具备滑坡预报模型要求的所有条件,包含的参数物理意义明确,因而具有新的生命力.

木本植物对大气污染指示与监测作用研究

本文研究了木本植物的不同部位即叶片、枝条和树皮以及植物的生理指标如气孔阻力对大气S02、TSP和重金属污染的指示和监测作用，并用树木年轮指示大气污染的历史和程度。结果认为： 承德市大气污染自1703年城市化以来开始出现，但达到严重污染水平则出现在本世纪50年代以来尤其是最近10-20年城市化与工业化的加剧，主要污染物以S02为主，从避暑山庄修建前的<0.1μg m-3达到目前的30μg m-3，重金属污染Fe自1927-45大庙铁矿开采后出现，Mn、Ni、Pb等出现在工业化以来的最近40-50年中，上述污染物含量在木质部年轮中明显升高，如S增加了10倍以上，Pb增加了560% (P<0.00l)。 不同城市功能区树皮pH和气孔阻力不同，主要与大气中的S02和TSP有关，据此可监测大气S02和TSP污染。前者以榆树、加拿大杨、垂柳和国槐最佳，相关系数分别可达-0.8384 (P<0.0l)，-0.7447、-0.6904和-0.6552 (P<0.05);后者则以白腊和旱柳下表皮最好，相关系数达0.9968和0.9951 (P<0.00l)。在扫描电镜下发现气孔受大气TSP影响出现不同程度的堵塞现象，主要有2种途径，小型颗粒物(<5μm)进入气孔腔，大型颗粒物(>30μm)可将气孔封盖。 植物不同器官部位污染物含量以树皮为最高，其次是枝条或叶，因而适宜的指示或监测部位是叶或枝条。主分量分析认为：承德市大气污染物以S为主，重金属Fe、Zn、Mn也有一定的贡献，Pb仅出现在繁忙道路区。不同季节污染物含量变化以休眠期最高，生长初期次之，生长旺盛期最低，如S和Pb分别从0.75 mg g-1和0.7 mg g-1上升到1.5 mg g-1和2.0 mg g-1(P<0.001)。植物不同季节污染物含量的变化反应了大气污染物季节变化特点，因而可以指示或监测大气污染尤其是S02污染。其中刺槐多部位复相关模型监测效果最佳，复相关系数可达0.987;某些植物单一部位的监测作用也较好，叶以珍珠梅最佳，相关系数为0.8695 (P<0.001)，枝以油松、珍珠梅、垂柳为好(r≥0.8，P <0.001)，树皮以刺槐为佳，r=0.8615 (P<0.0l)。植物不同部位的污染物含量还可用来评价大气环境质量，其中复合污染指数可以 评价总的大气环境质量，S污染指数和重金属污染指数可以评价S02、重金属和TSP污染，与直接利用污染物浓度法基本一致。油松不同部位对于大气S02的指示作用可表现为年轮对大气污染历史的指示或监测，针叶对现状S02污染的预测，并利用针叶对于S02的监测结果，绘制了大气S02污染分布图。 总之，本文利用古松年轮和现状城市植物的枝条、叶和树皮中的污染物含量以及树皮酸度等不同方面的指标，对承德市大气污染的历史和现状进行了指示与监测，即承德市大气污染从过去到现在均以S02为主，植物不同部位可以非常有效地进行大气S02污染的监测与评价，其中多部位的复相关模型预测效果极佳。另外，由植物监测而绘制的大气S02分布图，较准确地揭示了承德市大气S02现状分布规律。

~7Be示踪坡耕地次降雨细沟与细沟间侵蚀

对于坡面细沟与细沟间侵蚀过程的了解是建立侵蚀预报模型的基础,但传统方法难以对其进行深入研究。利用7Be示踪技术并结合人工模拟降雨,考虑坡脚沉积作用,研究了25°坡耕地径流小区次降雨过程中细沟与细沟间侵蚀动态。结果表明:根据流出径流小区泥沙7Be含量变化计算坡面明显细沟出现时间,由于坡脚沉积作用使得A、B两试验小区这一时间比实际细沟出现分别延迟了45min和11min;根据坡面-侵蚀泥沙中7Be总量守恒和泥沙质量平衡原理,坡面细沟间侵蚀及细沟侵蚀在坡面总侵蚀、坡脚沉积区泥沙及流出径流小区泥沙中的比例被定量区分开;总体上,细沟间侵蚀量在径流泥沙中的比例逐渐减少,而细沟侵蚀量逐渐增加。两试验小区中7Be示踪计算坡面细沟侵蚀量和坡脚沉积量与实测值相比相对误差均较小,因此7Be示踪技术可以对土壤侵蚀进行较为准确地定量研究。

土壤侵蚀预报模型研究进展

介绍了国内外土壤侵蚀预报模型的主要研究成果。所介绍的国外土壤侵蚀预报模型除众所周知的USL E/ RUSL E,WEPP,L ISEM和 EUROSEM外 ,还有浅沟侵蚀预报模型 (EGEM)和切沟侵蚀预报模型。国内的侵蚀预报模型主要有在 GIS支持下的陡坡地包括浅沟侵蚀的坡面侵蚀预报模型、有一定物理成因的坡面侵蚀预报模型和流域预报模型。在总结和评价国内外土壤侵蚀预报模型的基础上 ,提出了中国今后土壤侵蚀预报模型研究的设想。

基于MRF模型的油气储层属性随机建模方法研究

Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.

滑坡和泥石流致灾条件叠合技术及风险分析-以川藏公路然乌至鲁朗段为例

As one part of national road No. 318, Sichuan-Tibet (Chengdu-Lasha) Highway is one of traffic life lines connecting Tibet municipality to the inland, which is very important to the economic development of Tibet. In addition, it is still an important national defence routeway, with extremely important strategic position on maintaining the stability and solidarity of Tibet municipality and consolidating national defence. Particular geological condition, terrain and landform condition and hydrometeorological condition induce large-scale debris flows and landslides (including landslips) and the like geological hazards frequently occur along the highway. High frequency geological hazards not only result in high casualties and a great property loss, but also block traffic at every turn, obstructing the Sichuan-Tibet highway seriously. On the basis of considerable engineering geological investigation and analysis to the relative studying achievements of predecessors, it is found that one of the dominating reason incurring landslides or debris flows again and again in a place is that abundant loose materials are accumulated in valleys and slopes along the highway. Taking landslides' and debris flows along Ranwu-Lulang section of Sichuan-Tibet highway as studying objects, the sources and cause of formation of loose accumulation materials in the studying area are analyzed in detail, the major hazard-inducing conditions, hazard, dynamic risk, prediction of susceptibility degree of landslides and debris flows, and the relations between landslides and debris flows and various hazard-inducing conditions are systematically researched in this paper. All of these will provide scientific foundation for the future highway renovating and reducing and preventing geological hazards. For the purpose of quantitatively analyzing landslide and debris flow hazards, the conception of entropy and information entropy are extended, the conception of geological hazard entropy is brought forward, and relevant mathematics model is built. Additionally, a new approach for the dynamic risk analysis of landslide and debris flow is put forward based on the dynamic characteristics of the hazard of hazard-inducings and the vulnerability of hazard-bearings. The formation of landslide and debris flow is a non-linear process, which is synthetically affected by various factors, and whose formation mechanics is extremely complex. Aiming at this question, a muli-factors classifying and overlapping technique is brought forward on the basis of engineering geomechanics meta-synthesis (EGMS) thought and approach, and relevant mathematics model is also built to predict the susceptibility degree of landslide or debris flow. The example analysis result proves the validity of this thought and approach. To studying the problem that whether the formation and space distribution of landslides and debris flows are controlled by one or several hazard-inducing conditions, the theme graphics of landslides and debris flows hazard and various hazard-inducing conditions are overlapped to determine the relationship between hazard and hazard-inducing conditions. On this basis, the semi-quantitative engineering zonation of the studying area is carried out. In addition, the overlapping analysis method of the hazard-indue ing conditions of landslides and debris flows based on "digital graphics system" is advanced to orderly organize and effectively manage the spatial and attributive data of hazard and hazard-inducing conditions theme graphics, and to realize the effectively combination of graphics, images and figures.

Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder

The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength (Ben-Zion, 1996) They include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency-magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency-magnitude distribution, being greatly reduced if a pure Gutenburg-Richter form is assumed to hold out to high magnitudes.

Bayesian mixed models and divergence time estimation of Chinese cavefishes (Cyprinidae : Sinocyclocheilus)

The genus Sinocyclocheilus is distributed in Yun-Gui Plateau and its surrounding region only, within more than 10 cave species showing different degrees of degeneration of eyes and pigmentation with wonderful adaptations. To present, published morphological and molecular phylogenetic hypotheses of Sinocyclocheilus from prior works are very different and the relationships within the genus are still far from clear. We obtained the sequences of cytochrome b (cyt b) and NADH dehydrogenase subunit 4 (ND4) of 34 species within Sinocyclocheilus, which represent the most dense taxon sampling to date. We performed Bayesian mixed models analyses with this data set. Under this phylogenetic framework, we estimated the divergence times of recovered clades using different methods under relaxed molecular clock. Our phyloegentic results supported the monophyly of Sinocyclocheilus and showed that this genus could be subdivided into 6 major clades. In addition, an earlier finding demonstrating the polyphyletic of cave species and the most basal position of S. jii was corroborated. Relaxed divergence-time estimation suggested that Sinocyclocheilus originated at the late Miocene, about 11 million years ago (Ma), which is older than what have been assumed.

油气勘探风险评价与决策技术研究

PetroChina and other national petroleum incorporations need rigorous procedures and practical methods in risk evaluation and exploration decision at home and abroad to safeguard their international exploration practice in exploration licence bidding, finding appropriate ratio of risk sharing with partners, as well as avoiding high risk projects and other key exploration activities. However, due to historical reasons, we are only at the beginning of a full study and methodology development in exploration risk evaluation and decision. No rigorous procedure and practical methods are available in our exercises of international exploration. Completely adopting foreign procedure, methods and tools by our national incorporations are not practical because of the differences of the current economic and management systems in China. The objective of this study is to establish a risk evaluation and decision system with independent intellectual property right in oil and gas exploration so that a smooth transition from our current practice into international norm can take place. The system developed in this dissertation includes the following four components: 1. A set of quantitative criteria for risk evaluation is derived on the basis of an anatomy of the parameters from thirty calibration regions national wide as well as the characteristics and the geological factors controlling oil and gas occurrence in the major petroleum-bearing basins in China, which provides the technical support for the risk quantification in oil and gas exploration. 2. Through analysis of existing methodology, procedure and methods of exploration risk evaluation considering spatial information are proposed. The method, utilizing Mahalanobis Distance (MD) and fuzzy logic for data and information integration, provides probabilistic models on the basis of MD and fuzzy logic classification criteria, thus quantifying the exploration risk using Bayesian theory. A projection of the geological risk into spatial domain provides a probability map of oil and gas occurrence in the area under study. The application of this method to the Nanpu Sag shows that this method not only correctly predicted the oil and gas occurrence in the areas where Beibu and Laoyemiao oil fields are found in the northwest of the onshore area, but also predicted Laopu south, Nanpu south and Hatuo potential areas in the offshore part where exploration maturity was very low. The prediction of the potential areas are subsequently confirmed by 17 exploration wells in the offshore area with 81% success, indicating this method is very effective for exploration risk visualization and reduction. 3. On the basis of “Methods and parameters of economic evaluation for petroleum exploration and development projects in China”, a ”pyramid” method for sensitivity analysis was developed, which meets not only the need for exploration target evaluation and exploration decision at home, but also allows a transition from our current practice to international norm in exploration decision. This provides the foundation for the development of a software product “Exploration economic evaluation and decision system of PetroChina” (EDSys). 4. To solve problem in methodology of exploration decision, effort was made on the method of project portfolio management. A drilling decision method was developed employing the concept of geologically risked net present value. This method overcame the dilemma of handling simultaneously both geological risk and portfolio uncertainty, thus casting light into the application of modern portfolio theory to the evaluation of high risk petroleum exploration projects.

An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure-activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 +/- 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.