Integrated assessment for establishing an oil environmental vulnerability map: Case study for the Santos Basin region,Brazil

The growth of maritime transport and oil exploitation activities may increase the risk of oil spills. Thus, plans and actions to prevent or mitigate impacts are needed to minimize the effects caused by oil. However, tools used worldwide to support contingency plans have not been integrated, thus leading to failure in establishing priority areas. This investigation aimed to develop indices of environmental vulnerability to oil (IEVO), by combining information about environmental sensibility to oil and results of numerical modeling of spilled oil. To achieve that, a case study concerning to oil spills scenarios in a subtropical coastal area was designed, and IEVOs were calculated and presented in maps, in order to make the information about the areas’ vulnerability more easily visualized. For summer, the extension of coastline potentially affected by oil was approximately 150 km, and most of the coastline presented medium to high vulnerability. For winter, 230 km coastline would be affected, from which 75% were classified as medium to high vulnerability. Thus, IEVO maps allowed a rapid and clearer interpretation of the vulnerability of the mapped region, facilitating the planning process and the actions in response to an oil spill.     

Comparison of direct statistical and indirect statistical-deterministic frameworks in downscaling river low-flow indices

ABSTRACT

This work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other approaches with respect to goodness of fit and generalization ability.

Editor D. Koutsoyiannis; Associate editor K. Hamed     

甘肃岷县漳县6.6级地震发生日期的触发因素分析及对短临预测方法的思考

短临预报是目前地震预测的难点,通过对2013年甘肃岷县漳县MS6.6地震发生日期的研究,发现发生日期7月22日是节气、低点位移、异年倍七律和朔望共同作用的时间点。据此,本文用一些基于可能触发地震发生的非传统方法的时间预测方法,回顾性地讨论了甘肃岷县漳县MS6.6地震发生日期的临震日期预测问题。通过对岷县漳县MS6.6地震研究,认为在地震短临日期的预测上。一些非传统方法虽然在机理上还有待研究,但在统计上多次证明该方法具有预测准确性的效能。要基于传统方法与非传统方法结合,才能对临震预测的时间逼近,同时提出今后预测临震时间的思路:多因素不断拦截法。     

Response of the hydrological regime of the Yellow River to the changing monsoon intensity and human activity

Abstract

In the past 50 years, influenced by global climate change, the East Asian summer monsoon intensity (SMI) changed significantly, leading to a response by the water cycle of the Yellow River basin. The variation in SMI has three stages: (1) 1951–1963, SMI increased; (2) 1963–1965, SMI declined sharply, a feature that may be regarded as an abrupt change; and (3) 1965–2000, SMI remained at low levels and showed a tendency to decline slowly. The decreased SMI led to a reduction in water vapour transfer from the ocean to the Yellow River basin, and thus precipitation decreased and the natural river runoff of the Yellow River also decreased. Due to the increase in population and therefore in irrigated land area, the ratio of net water diversion to natural river runoff increased continuously. Comparison of the ratio of net water diversion to natural river runoff before and after the abrupt change in SMI indicates some discontinuity in the response of the man-induced lateral branch of the water cycle to the abrupt change in SMI. The frequently occurring flow desiccation in the lower Yellow River can be regarded as a response of the water cycle system to the decreasing summer monsoon intensity and increasing population. When the ratio of net water diversion exceeded the ratio of natural runoff of the low-flow season to the annual total natural runoff, flow desiccation in the lower Yellow River would occur. When the ratio of net water diversion is 0.3 larger than the ratio of the natural runoff of the low-flow season to the annual total natural runoff, an abrupt increase in the number of flow desiccation events is likely to occur.     

Evaluation of Composts from Agricultural Wastes with Fish Pond Sediment as Bulking Agent to Improve Compost Quality

Composts with five different ratios of agricultural wastes, viz. rice straw (RS), wheat straw (WS), potato plant (PP), and mustard stover (MS) were prepared with or without fish pond bottom sediment to investigate the compost maturity and their suitability for field application. The composting process was monitored through the changes in physico‐chemical parameters and germination index (GI) at every 7 days interval of the composting process. All the composts were dark brown and smelled like forest soil within 56 days of composting, which reflected its matured status. On the basis of the physico‐chemical parameters (bulk density: 0.84 g/cm³; pH 7.05; electrical conductivity: 3.52 mS/cm; cation exchange capacity:82.4 cmol/kg; total carbon:321.4 g/kg; total nitrogen: 16.9 g/kg; As: 6.8 mg/kg; Cd: 2.96 mg/kg; Cr: 29.6 mg/kg, Cu: 243.6 mg/kg; Hg: 0.019 mg/kg; Ni: 24.3 mg/kg; Pb: 62.1 mg/kg and Zn: 812 mg/kg) and GI (89–96%), it could be concluded that RS/WS/PP/MS, 1:1:2:1 v/v/v/v with fish pond sediment produced better compost in accordance with the Indian compost standard. Application of a combined randomized block design analysis revealed that there is a significant difference in the responses of the five composts, in relation to the time of composting. Hierarchical clustering algorithm was applied with a view to form homogeneous groups of five different composts on the basis of different physico‐chemical parameters. Therefore, the ratio of waste incorporation is an important decision for composting and addition of pond sediment can improve the quality of compost.     

Planning for growth in a natural resource boomtown: challenges for urban planners in Fort McMurray,Alberta

Between 2000 and 2010, the population of the city of Fort McMurray, Alberta increased by 80%, mainly due to the expansion of oil extraction projects and subsidiary industries. Population growth of this magnitude has significant consequences for city planning. While Fort McMurray struggles to keep up with enormous numbers of in-migrants, the cost of living in the city has skyrocketed. Using interviews with city planners and field experience in the city, in this paper I examine the current challenges faced by urban planners in Fort McMurray against the backdrop of global economic decision-making, corporate influence, and commodity dynamics. While the recession of 2008 gave city planners some breathing room, they still struggle with gathering accurate census information and predicting population growth, providing affordable housing, and balancing short-range planning with their long-term goals. Attempts by city planners to address these challenges could provide a contemporary model for urban planning in rapidly growing, resource-dependent communities.     

弱GPS信号捕获算法及其仿真研究

为满足低信噪比环境下的导航需要,介绍了一种基于改进循环相关的GPS基带信号捕获算法。本文借助于GPS信号基带数学模型以及FFT技术,从理论层面上对捕获算法的信号处理流程以及捕获性能进行了分析;并利用真实GPS基带数据对算法在低信噪比环境下的检测概率和捕获能力进行了重点仿真,仿真结果显示算法在低信噪比环境下是有效的,能够提高低信噪比环境下的检测概率和提高GPS接收机的检测灵敏度。     

Potentiality of feed-forward neural networks for classifying dark formations to oil spills and look-alikes

Radar backscatter values from oil spills are very similar to backscatter values from very calm sea areas and other ocean phenomena. Several studies aiming at oil spill detection have been conducted. Most of these studies rely on the detection of dark areas, which have high Bayesian probability of being oil spills. The drawback of these methods is a complex process, mainly because non-linearly separable datasets are introduced in statistically based decisions. The use of neural networks (NNs) in remote sensing has increased significantly, as NNs can simultaneously handle non-linear data of a multidimensional input space. In this article, we investigate the ability of two commonly used feed-forward NN models: multilayer perceptron (MLP) and radial basis function (RBF) networks, to classify dark formations in oil spills and look-alike phenomena. The appropriate training algorithm, type and architecture of the optimum network are subjects of research. Inputs to the networks are the original synthetic aperture radar image and other images derived from it. MLP networks are recognized as more suitable for oil spill detection.     

红鳍东方鲀(Takifugu rubripes)耐低温性状和生长性状遗传参数评估

采用人工控温的方式, 对构建的31个F₁红鳍东方鲀(Takifugu rubripes)全同胞家系开展低温胁迫实验, 获得耐低温性状低温累计存活时间(CDH), 基于混合线性模型分别开展耐低温性状和生长性状遗传参数评估,对每一性状是否需要考虑共同环境效应所构建的两种模型进行似然比检验。结果显示, 经似然比检验, 最终选用模型A和模型BF进行耐低温和生长性状遗传评估; 耐低温性状CDH遗传力为(0.27±0.08),属于中等遗传力; 体重BW遗传力为(0.36±0.13), 属于中等遗传力, 体长BL遗传力为(0.14±0.06), 属于低等遗传力, 经检验, 遗传力估计值均达到极显著水平(P<0.01)。CDH和体重、体长的遗传相关分别为(-0.40±0.22)和(-0.44±0.24), 表型相关分别为(-0.09±0.06)和(-0.16± 0.05), 均为负相关; 体重和体长之间的遗传相关为(0.92±0.05), 表型相关为(0.80±0.02), 呈正相关且结果极显著(P<0.01)。研究结果表明, 红鳍东方鲀的耐低温性状和生长性状都具有较好的改良潜力, 考虑到两性状间存在负遗传相关, 在开展耐低温选育时, 对首先不同性状进行品系选育, 然后利用品系间杂交培育出耐高温、生长快的新品种。该项研究首次完成了红鳍东方鲀耐低温性状的遗传参数评估, 为制订红鳍东方鲀耐低温选育育种规划提供了理论依据。     

陕北延安地区基底断裂及其油气地质意义

以重磁力资料为基础,结合钻井及地质地震资料,推测出研究区有8条基底断裂。已有油田大都沿基底断裂走向分布在断裂两侧,勘探井的试气产量高低与基底断裂分布关系密切,基底断裂的"隐性"活动导致沉积盖层中发育构造裂缝且以垂直裂缝为主,裂缝不仅能作为油气运移的通道,而且能提高储层的孔隙度和渗透率,对研究区内油气分布及储层产能起关键作用。