中国大北方上古生界油气勘探新领域（代序）

矿田构造是指在矿田范围内,控制矿床的形成和分布的地质构造因素的总和。在矿田构造和矿床构造的含义中,既包括构造形迹和岩石组构特征,又包括控矿构造的形成机制和发展历史。近10几年来的矿田矿床研究不仅强调构造对于矿体的形态、分布和组合的控制作用,也深入于构造作用对成岩成矿过程的研究。综合分析了矿田构造研究的研究历史、研究内容、研究现状与问题,对矿田构造与找矿研究的发展方向进行了展望。     

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice.Hence,the limiting velocity should be determined to keep the channel bottom clean from sediment deposits.Recently,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many researchers.The current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology...     

基于统计岩石物理模型的各向异性页岩储层参数反演

提出了各向异性页岩储层统计岩石物理反演方法.通过统计岩石物理模型建立储层物性参数与弹性参数的定量关系,使用测井数据及井中岩石物理反演结果作为先验信息,将地震阻抗数据定量解释为储层物性参数、各向异性参数的空间分布.反演过程在贝叶斯框架下求得储层参数的后验概率密度函数,并从中得到参数的最优估计值及其不确定性的定量描述.在此过程中综合考虑了岩石物理模型对复杂地下介质的描述偏差和地震数据中噪声对反演不确定性的影响.在求取最大后验概率过程中使用模拟退火优化粒子群算法以提高收敛速度和计算准确性.将统计岩石物理技术应用于龙马溪组页岩气储层,得到储层泥质含量、压实指数、孔隙度、裂缝密度等物性,以及各向异性参数的空间分布及相应的不确定性估计,为页岩气储层的定量描述提供依据.

     

SPOT地面场定标与星上定标结果的比较分析

本文研究是在遥感辐射定标场选择的基础。利用６Ｓ大气辐射传输模型进行ＳＰＯＴ遥感数据的定标和地物的光谱反射率反演,即在遥感器飞越辐射定标场上空,在定标场选择若干像元区,测量遥感器对应的各波段地物的光谱反射率和大气光谱参量,并利用大气辐射传输模型给出遥感器人瞳处各光谱带的辐射亮度,最后确定它与遥感器对应输出的数字量化的数量关系,求解定标系数。然后,对相应的研究训练区的遥感数据进行大气辐射校正,进而反演训练区内的地物光谱反射率。最后,通过将反演值与实地测量的地物光谱反射率进行对比分析,来估算定标不确定度,并比较说明两种不同方式定标差异及优势和限制。     

UNCERTAINTY AND SENSITIVITY ANALYSES OF SEDIMENT TRANSPORT FORMULAS

ＵＮＣＥＲＴＡＩＮＴＹＡＮＤＳＥＮＳＩＴＩＶＩＴＹＡＮＡＬＹＳＥＳＯＦＳＥＤＩＭＥＮＴＴＲＡＮＳＰＯＲＴＦＯＲＭＵＬＡＳＫｅｈＣｈｉａＹＥＨ１ａｎｄＳｅｎＬｏｎｇＤＥＮＧ２ＡＢＳＴＲＡＣＴＩｎｖｉｅｗｏｆｔｈｅｒａｎｄｏｍｃｈａｒａｃｔｅｒｉｓｔ...     

Probabilistic-fuzzy health risk modeling

Health risk analysis of multi-pathway exposure to contaminated water involves the use of mechanistic models that include many uncertain and highly variable parameters. Currently, the uncertainties in these models are treated using statistical approaches. However, not all uncertainties in data or model parameters are due to randomness. Other sources of imprecision that may lead to uncertainty include scarce or incomplete data, measurement error, data obtained from expert judgment, or subjective interpretation of available information. These kinds of uncertainties and also the non-random uncertainty cannot be treated solely by statistical methods. In this paper we propose the use of fuzzy set theory together with probability theory to incorporate uncertainties into the health risk analysis. We identify this approach as probabilistic-fuzzy risk assessment (PFRA). Based on the form of available information, fuzzy set theory, probability theory, or a combination of both can be used to incorporate parameter uncertainty and variability into mechanistic risk assessment models. In this study, tap water concentration is used as the source of contamination in the human exposure model. Ingestion, inhalation and dermal contact are considered as multiple exposure pathways. The tap water concentration of the contaminant and cancer potency factors for ingestion, inhalation and dermal contact are treated as fuzzy variables while the remaining model parameters are treated using probability density functions. Combined utilization of fuzzy and random variables produces membership functions of risk to individuals at different fractiles of risk as well as probability distributions of risk for various alpha-cut levels of the membership function. The proposed method provides a robust approach in evaluating human health risk to exposure when there is both uncertainty and variability in model parameters. PFRA allows utilization of certain types of information which have not been used directly in existing risk assessment methods.     

Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints

We propose a framework to systematically generate event landslide inventory maps from satellite images in southern Taiwan, where landslides are frequent and abundant. The spectral information is used to assess the pixel land cover class membership probability through a Maximum Likelihood classifier trained with randomly generated synthetic land cover spectral fingerprints, which are obtained from an independent training images dataset. Pixels are classified as landslides when the calculated landslide class membership probability, weighted by a susceptibility model, is higher than membership probabilities of other classes. We generated synthetic fingerprints from two FORMOSAT-2 images acquired in 2009 and tested the procedure on two other images, one in 2005 and the other in 2009. We also obtained two landslide maps through manual interpretation. The agreement between the two sets of inventories is given by the Cohen’s k coefficients of 0.62 and 0.64, respectively. This procedure can now classify a new FORMOSAT-2 image automatically facilitating the production of landslide inventory maps.     

Global urbanization projections for the Shared Socioeconomic Pathways

The new scenario process for climate change research includes the creation of Shared Socioeconomic Pathways (SSPs) describing alternative societal development trends over the coming decades. Urbanization is a key aspect of development that is relevant to studies of mitigation, adaptation, and impacts. Incorporating urbanization into the SSPs requires a consistent set of global urbanization projections that cover long time horizons and span a full range of uncertainty. Existing urbanization projections do not meet these needs, in particular providing only a single scenario over the next few decades, a period during which urbanization is likely to be highly dynamic in many countries. We present here a new, long-term, global set of urbanization projections at country level that cover a plausible range of uncertainty. We create SSP-specific projections by choosing urbanization outcomes consistent with each SSP narrative. Results show that the world continues to urbanize in each of the SSPs but outcomes differ widely across them, with urbanization reaching 60%, 79%, and 92% by the end of century in SSP3, SSP2, and SSP1/SSP4/SSP5, respectively. The degree of convergence in urbanization across countries also differs substantially, with largely convergent outcomes by the end of the century in SSP1 and SSP5 and persistent diversity in SSP3. This set of global, country-specific projections produces urbanization pathways that are typical of regions in different stages of urbanization and development levels, and can be extended to further elaborate assumptions about the styles of urban growth and spatial distributions of urban people and land cover occurring in each SSP.     

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2–26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias.     

Adaptive and risk-based approaches to climate change and the management of uncertainty and institutional risk: The case of future flooding in England

This paper focuses on how scientific uncertainties about future peak flood flows and sea level rises are accounted for in long term strategic planning processes to adapt inland and coastal flood risk management in England to climate change. Combining key informant interviews (n = 18) with documentary analysis, it explores the institutional tensions between adaptive management approaches emphasising openness to uncertainty and to alternative policy options on the one hand and risk-based ones that close them down by transforming uncertainties into calculable risks whose management can be rationalized through cost-benefit analysis and nationally consistent, risk-based priority setting on the other hand. These alternative approaches to managing uncertainty about the first-order risks to society from future flooding are shaped by institutional concerns with managing the second-order, ‘institutional’ risks of criticism and blame arising from accountability for discharging those first-order risk management responsibilities. In the case of river flooding the poorly understood impacts of future climate change were represented with a simplistic adjustment to peak flow estimates, which proved robust in overcoming institutional resistance to making precautionary allowances for climate change in risk-based flood management, at least in part because its scientific limitations were acknowledged only partially. By contrast in the case of coastal flood risk management, greater scientific confidence led to successively more elaborate guidance on how to represent the science, which in turn led to inconsistency in implementation and increased the institutional risks involved in taking the uncertain effects of future sea level rise into account in adaptation planning and flood risk management. Comparative analysis of these two cases then informs some wider reflections about the tensions between adaptive and risk-based approaches, the role of institutional risk in climate change adaptation, and the importance of such institutional dynamics in shaping the framing uncertainties and policy responses to scientific knowledge about them.