内陆单斜构造内咸水入侵淡水含水层三维数值模拟：——以山西柳林？…

本文建立了内陆单斜构造内咸水入侵淡水含水层的三维可混溶溶质运移模型。同时,为了尽可能提高模拟精度,还建立了区域二维水流模型和水质模型,为三维模型提供边界条件。模型应用于描述柳林电厂水源地咸－淡水界面运移特征,模拟效果良好,还据此预报了咸水入侵的可能性并探讨了淡水流的强弱对咸－淡水界面运移的影响。     

Adaptive filtering of continuous GPS results

 An adaptive finite-duration impulse response filter, based on a least-mean-square algorithm, has been used to mitigate multipath effects, and to derive tectonic and fault movement signals from continuous global positioning system (CGPS) data. By applying the filter on both pseudo-range and carrier-phase multipath sequences from CGPS observations on consecutive days, multipath models have been reliably derived. The standard deviations of residual time series are reduced to about one-quarter on pseudo-range and to about one-half on carrier phase. The adaptive filter is then used to process baseline solutions from a five-station array. Tectonic and fault movements have been resolved, which are in good agreement with previous studies involving many more CGPS stations. Received: 11 February 2000 / Accepted: 28 June 2000     

Learning effects of interactive decision-making processes for climate change adaptation

Learning is gaining attention in relation to governance processes for contemporary environmental challenges; however, scholarship at the nexus of learning and environmental governance lacks clarity and understanding about how to define and measure learning, and the linkages between learning, social interactions, and environment. In response, this study aimed to advance and operationalize a typology of learning in an environmental governance context, and examined if a participatory decision-making process (adaptive co-management) for climate change adaptation fostered learning. Three types of learning were identified: cognitive learning, related to the acquisition of new or the structuring of existing knowledge; normative learning, which concerns a shift in viewpoints, values or paradigms, and relational learning, referring to an improved understanding of others’ mindsets, enhanced trust and ability to cooperate. A robust mixed methods approach with a focus on quantitative measures including concept map analysis, social network analysis, and self-reflective questions, was designed to gauge indicators for each learning type. A participatory decision-making process for climate change adaptation was initiated with stakeholders in the Niagara region, Canada. A pseudo-control group was used to minimize external contextual influences on results. Clear empirical evidence of cognitive and relational learning was gained; however, the results from normative learning measures were inconclusive. The learning typology and measurement method operationalized in this research advances previous treatments of learning in relation to participatory decision-making processes, and supports adaptive co-management as a governance strategy that fosters learning and adaptive capacity.     

Adaptive isogeometric finite element analysis of steady‐state groundwater flow

Numerical challenges occur in the simulation of groundwater flow problems because of complex boundary conditions, varying material properties, presence of sources or sinks in the flow domain, or a combination of these. In this paper, we apply adaptive isogeometric finite element analysis using locally refined (LR) B‐splines to address these types of problems. The fundamentals behind isogeometric analysis and LR B‐splines are briefly presented. Galerkin's method is applied to the standard weak formulation of the governing equation to derive the linear system of equations. A posteriori error estimates are calculated to identify which B‐splines should be locally refined. The error estimates are calculated based on recovery of the L₂‐projected solution. The adaptive analysis method is first illustrated by performing simulation of benchmark problems with analytical solutions. Numerical applications to two‐dimensional groundwater flow problems are then presented. The problems studied are flow around an impervious corner, flow around a cutoff wall, and flow in a heterogeneous medium. The convergence rates obtained with adaptive analysis using local refinement were, in general, observed to be of optimal order in contrast to simulations with uniform refinement. Copyright © 2015 John Wiley & Sons, Ltd.     

“Caribou was the reason,and everything else happened after”: Effects of caribou declines on Inuit in Labrador,Canada

For many Indigenous Peoples in the Circumpolar North, cultural engagement and continuity across generations is directly related to relationships between and among people, animals, and landscapes. However, minimal research outlines the emotional responses and disruptions to culture and identity that are driven by ecological change, and the subsequent cultural dimensions of coping and adapting to this uncertainty. Through a case study that explores how caribou population declines and a caribou hunting ban are impacting Inuit in the Nunatsiavut and NunatuKavut regions of Labrador, Canada, this article examines the critical interplay between cultural continuity and adaptive capacity for responding to ecological uncertainty. More specifically, this study: 1) described the central role that caribou play for Inuit emotional wellness, identity, and cultural continuity; 2) explored how the rapid declines of caribou in Labrador are affecting Inuit emotional wellness, identity, and cultural continuity; and 3) characterized the ways in which Inuit are adapting to these emotio-social, cultural, and ecological changes. Drawing from an Inuit-led, multi-year, multi-media qualitative and visual media research program, data from video interviews (n = 84: Nunatsiavut region: n = 54; NunatuKavut region: n = 30) were analyzed using a video-based qualitative analysis, constant-comparative methods, and inductive qualitative approach. Results indicated that caribou are a foundational element for Inuit emotional wellness, identity, and cultural continuity. The changes in caribou populations are resulting in complex emotional responses, losses to cultural meaning and knowledge, and alterations to Inuit identities. The impacts on emotions, identity, and cultural continuity related to Inuit-caribou relations at an individual and collective level reflect the interconnections between cultural continuity and adaptive capacity that underlie the loss of this culturally important species. Though this research focuses on two Inuit groups and caribou in Labrador, the insights from these lived experiences highlight the ongoing cultural and identity consequences associated with species declines occurring globally.     

Geographical imbalances and divides in the scientific production of climate change knowledge

Studies on scientific production of climate change knowledge show a geographical bias against the developing and more vulnerable regions of the world. If there is limited knowledge exchange between regions, this may deepen global knowledge divides and, thus, potentially hamper adaptive capacities. Consequently, there is a need to further understand this bias, and, particularly, link it with the exchange of knowledge across borders. We use a world-wide geographical distribution of author affiliations in >15,000 scientific climate change publications to show that (1) research production mainly takes place in richer, institutionally well-developed countries with cooler climates and high climate footprints, and (2) the network of author affiliations is structured into distinct modules of countries with strong common research interests, but with little knowledge exchange between modules. These modules are determined mainly by geographical proximity, common climates, and similar political and economic characteristics. This indicates that political-economic, social and educational-scientific initiatives targeted to enhance local research production and collaborations across geographical-climate module borders may help diminish global knowledge divides. We argue that this could strengthen adaptive capacity in the most vulnerable regions of the world.     

Framing the application of adaptation pathways for rural livelihoods and global change in eastern Indonesian islands

In developing countries adaptation responses to climate and global change should be integrated with human development to generate no regrets, co-benefit strategies for the rural poor, but there are few examples of how to achieve this. The adaptation pathways approach provides a potentially useful decision-making framework because it aims to steer societies towards sustainable futures by accounting for complex systems, uncertainty and contested multi-stakeholder arenas, and by maintaining adaptation options. Using Nusa Tenggara Barat Province, Indonesia, as an example we consider whether generic justifications for adaptation pathways are tenable in the local context of climate and global change, rural poverty and development. Interviews and focus groups held with a cross-section of provincial leaders showed that the causes of community vulnerability are indeed highly complex and dynamic, influenced by 20 interacting drivers, of which climate variability and change are only two. Climate change interacts with population growth and ecosystem degradation to reduce land, water and food availability. Although poverty is resilient due to corruption, traditional institutions and fatalism, there is also considerable system flux due to decentralisation, modernisation and erosion of traditional culture. Together with several thresholds in drivers, potential shocks and paradoxes, these characteristics result in unpredictable system trajectories. Decision-making is also contested due to tensions around formal and informal leadership, corruption, community participation in planning and female empowerment. Based on this context we propose an adaptation pathways approach which can address the proximate and systemic causes of vulnerability and contested decision-making. Appropriate participatory processes and governance structures are suggested, including integrated livelihoods and multi-scale systems analysis, scenario planning, adaptive co-management and ‘livelihood innovation niches’. We briefly discuss how this framing of adaptation pathways would differ from one in the developed context of neighbouring Australia, including the influence of the province's island geography on the heterogeneity of livelihoods and climate change, the pre-eminence and rapid change of social drivers, and the necessity to ‘leap-frog’ the Millennium Development Goals by mid-century to build adaptive capacity for imminent climate change impacts.     

Application of a fuzzy inference system for the prediction of longshore sediment transport

A fuzzy inference system (FIS) and a hybrid adaptive network-based fuzzy inference system (ANFIS), which combines a fuzzy inference system and a neural network, are used to predict and model longshore sediment transport (LST). The measurement data (field and experimental data) obtained from Kamphuis [1] and Smith et al. [2] were used to develop the model. The FIS and ANFIS models employ five inputs (breaking wave height, breaking wave angle, slope at the breaking point, peak wave period and median grain size) and one output (longshore sediment transport rate). The criteria used to measure the performances of the models include the bias, the root mean square error, the scatter index and the coefficients of determination and correlation. The results indicate that the ANFIS model is superior to the FIS model for predicting LST rates. To verify the ANFIS model, the model was applied to the Karaburun coastal region, which is located along the southwestern coast of the Black Sea. The LST rates obtained from the ANFIS model were compared with the field measurements, the CERC [3] formula, the Kamphuis [1] formula and the numerical model (LITPACK). The percentages of error between the measured rates and the calculated LST rates based on the ANFIS method, the CERC formula (K_sig = 0.39), the calibrated CERC formula (K_sig = 0.08), the Kamphuis [1] formula and the numerical model (LITPACK) are 6.5%, 413.9%, 6.9%, 15.3% and 18.1%, respectively. The comparison of the results suggests that the ANFIS model is superior to the FIS model for predicting LST rates and performs significantly better than the tested empirical formulas and the numerical model.     

自适应变异粒子群优化灰色模型在变形分析中的应用

标准灰色模型GM(1,1)以序列第一个分量作为初始条件进行灰色微分建模,未能充分利用序列中的新信息;其背景值的构造本质上采用了数值积分中的梯形法,精度不高。针对上述缺点,提出一种基于粒子群算法的灰色预测模型,即PSOGM(1,1)模型,对初始值和背景值参数进行优化,并将模型应用于岩体变形分析中。计算结果表明,PSOGM(1,1)模型具有较高的预测精度,可作为变形分析的一种新方法。     

两种GPS天线阵列抗干扰算法研究及仿真

介绍了自适应天线阵列信号响应的数学描述,论述了在GPS抗干扰应用中广泛采用的基于最小均平方（LMS）的自适应算法的原理和实现过程,并对算法进行了仿真。提出了一种优于LMS算法的自适应数字波束形成（DBF）技术,推导出了其最优权系数矢量的计算方法,并对该算法进行了仿真。仿真结果表明：4阵元LMS的自适应调零算法对于单干扰的抑制和双干扰的抑制都达到了较好的效果,同时也体现了该算法零陷的优点。