济源地区中-下三叠统碎屑锆石年代学特征及其物源分析

沉积物源组成及其演化是研究沉积盆地及盆山系统演化的关键。对济源地区中-下三叠统3个组进行了碎屑锆石U-Pb同位素分析,结果显示,下三叠统刘家沟组碎屑锆石具有6个年龄峰值:270,329,385,450,1885,2511Ma,其中晚古生代碎屑锆石应来自内蒙古隆起,早古生代碎屑锆石来自秦岭造山带,而新太古代-古元古代碎屑锆石则来自华北克拉通基底。下三叠统和尚沟组碎屑锆石年龄主峰值为420Ma,次峰值为745Ma和952Ma,均来自秦岭造山带。中三叠统二马营组碎屑锆石年龄主峰值为254Ma,可能来自华北板块南缘再旋回的沉积物,次峰值为1690Ma和2524Ma,应来自华北克拉通基底,其中1690Ma的碎屑锆石对应了华北板块南缘广泛出露的熊耳群。新元古界碎屑锆石由刘家沟组至和尚沟组增多,说明秦岭造山带基底逐渐剥露,是造山作用增强的体现。中三叠世末,秦岭造山带进入全面碰撞造山阶段,从地质演化过程来看,秦岭造山带在中三叠世也应处于持续隆升状态,然而二马营组中却没有来自秦岭造山带的碎屑锆石记录,而是以华北板块南缘盖层和基底为主,推测秦岭造山带的造山作用影响到了华北板块南缘,使华北板块南缘不断抬升,阻挡了秦岭造山带为济源地区提供沉积物。     

长三角地区民宿的空间分布及影响因素

近年来,民宿作为旅游业发展的新兴模式,日益受到关注,并呈现蓬勃发展状态。以民宿业发展最为成熟的长三角地区为研究对象,基于去哪儿网相关民宿数据,采用空间最邻近分析、密度分析等空间分析方法,研究民宿的空间分布格局与特征,并基于逐步回归分析,探讨影响民宿分布的因素,得出以下结论：① 长三角地区民宿呈现高度集聚的状态,整体上表现为多核心分布,并形成一、二、三级组团,密度由核心向外围递减。② 民宿集聚分布在经济较为发达的城市和核心景区周边,具有明显的中心性。③ 基于对经济基本状况、交通状况、人口条件、居民消费能力、旅游市场状况、旅游资源与环境条件等方面共15个影响因素分析,发现单位面积旅游收入、A级景区数量、人口密度、地区国内生产总值四个指标对民宿密度有显著正向影响,其中,影响力单位面积旅游收入>A级景区数量>人口密度>地区国内生产总值。     

人海关系地域系统视角下海洋本体的解构与研究重点

在揭示人海辩证关系与海洋社会属性的基础上,从人海关系地域系统的视角,解析了海洋的构成。第一海洋（自然海洋）是人海关系地域系统中自然存在而非人为构筑的海洋部分,其核心要素是地理位置、物质构成和空间形态。第二海洋（人工海洋）是人类海洋实践中所建造的设施及相应的物质、能量及信息流动,包括基地设施、人类主体之间的物质信息交流和人类与海洋之间的采集排放活动。第三海洋（关系海洋）是不同人类主体在海洋实践中形成的互动关系,核心内容是主体构成、内容组成以及表现形式。第四海洋（观念海洋）是人类对海洋及海洋实践活动的认知,核心是在处理人类与海洋、陆地与海洋和人类主体之间关系时所秉持的理念。现实中,自然海洋、实践性的人工海洋和关系海洋与构想性的观念海洋相互作用,形成了丰富多样的海洋世界。随着人类海洋实践的深化,关系海洋和观念海洋与自然海洋和人工海洋一并成为了研究与实践的重点。     

作物生产潜力变化的区域差异——以陕西省为例

作物生产潜力变化具有明显的区域差异性,亟需针对不同地理单元实施有效应对措施和调控策略。选择陕西省三大地理单元（陕北高原、关中盆地和秦巴山区）为研究对象,运用全球生态区模型（GAEZ）分析了陕西省不同地理单元作物生产潜力变化趋势,探讨了不同作物生产潜力变化的区域差异,辨识出影响不同作物生产潜力变化的主要因素,结果显示：（1） 1980—2015年间,陕西省玉米生产潜力总量增加了150.55×10⁴ t,小麦生产潜力总量则下降了402.69×10⁴ t。（2） 关中盆地的玉米和小麦生产潜力皆最大,陕北高原次之,秦巴山区的玉米和小麦生产潜力皆最小;陕北高原和秦巴山区的玉米生产潜力皆表现出先增加后减小再增加的变化趋势,关中盆地的玉米生产潜力则先减小后增加再减小;关中盆地和秦巴山区的小麦生产潜力都呈下降趋势,陕北高原的小麦生产潜力则有所提高。（3） 土地利用变化呈现减产效应,这一效应在关中盆地尤为显著,其次为陕北高原;气候变化导致玉米生产潜力增加,使小麦生产潜力下降;气候变化对不同地理单元的影响也不相同,在陕北高原表现为增产效应,在关中盆地和秦巴山区则为减产效应。（4） 在陕北高原,气候变化的增产效应是玉米和小麦生产潜力提高的主要原因,气候变化对玉米生产潜力的影响大于对小麦的影响,耕地向草地、林地和建设用地的转化是降低作物生产潜力最主要的土地利用变化因素;在关中盆地,作物生产潜力的变化主要是受气候变化的影响,小麦受气候变化的影响较玉米为大,以建设用地占用耕地为特征的土地利用变化对玉米生产潜力的影响大于对小麦的影响;在秦巴山区,土地利用变化是玉米生产潜力变化的主要原因,而小麦生产潜力的变化主要受气候变化影响。     

华北区域分米级北斗地基增强服务系统构建及精度分析

利用国家级北斗连续运行基准站和省级区域北斗CORS站,基于国家卫星导航定位服务平台,通过改造和直接利用的方式,在华北平原构建了我国首个跨区域北斗分米级地基增强服务系统。经采用双频终端实地测试,该系统覆盖京津冀晋全部区域及内蒙古部分区域,采用GPS+北斗双模定位静态精度达到分米级,动态定位精度达到亚米级,单北斗模式定位精度略低,但仍在分米-亚米量级,极大地提高了我国北斗导航系统的高精度应用能力,拓宽了我国北斗民用导航的应用范围和领域,可满足高精度北斗实时导航、定位服务的应用需求。     

Case Study of Fog Predictability for an Event with Cold-Front Synoptic Pattern

Fog has recently become a frequent high-impact weather phenomenon along the coastal regions of North China. Accurate fog forecasting remains challenging due to limited understanding of the predictability and mechanism of fog formation associated with synoptic-scale circulation. One frequent synoptic pattern of fog formation in this area is associated with cold front passage(cold-front synoptic pattern, CFSP). This paper explored the predictability of a typical CFSP fog event from the perspective of analyzing key characteristics of synoptic-scale circulation determining fog forecasting performance and the possible mechanism. The event was ensemble forecasted with the Weather Research and Forecasting model. Two groups of ensemble members with good and bad forecasting performance were selected and composited. Results showed that the predictability of this case was largely determined by the simulated strengths of the cold-front circulation(i.e., trough and ridge and the associated surface high). The bad-performing members tended to have a weaker ridge behind a stronger trough, and associated higher pressure over land and a weaker surface high over the sea, leading to an adverse impact on strength and direction of steering flows that inhibit warm moist advection and enhance cold dry advection transported to the focus region. Associated with this cold dry advection, adverse synoptic conditions of stratification and moisture for fog formation were produced, consequently causing failure of fog forecasting in the focus region. This study highlights the importance of accurate synoptic-scale information for improved CFSP fog forecasting, and enhances understanding of fog predictability from perspective of synoptic-scale circulation.     

Spatial Distribution Assessment and Source Apportionment of Land-Based Pollutant Yield from Qingdao,China

The spatial distribution of chemical oxygen demand(COD) and total nitrogen(TN) yield from Qingdao are studied by comparing pollutant yield amount, densities and spatial aggregation(Getis-Ord indexes) among the land-based pollutant source regions(PSRs) entering the three sub-seas(i.e. the Jiaozhou Bay(JZB), other coastal area in the Yellow Sea(OCAYS) and Laizhou Bay(LZB), respectively). Industrial composition of the loads are also studied by comparing pollutant yield among the sources of agriculture, rural domesticity, industry, urban domesticity and service, and calculation of Gini coefficient. Results show that spatial distribution of COD and TN yield from Qingdao are extremely unbalanced. The JZB, with less than 3% of the total coastal sea area of Qingdao, received 62% COD load and 65% TN yield from Qingdao, while the OCAYS, with more than 97% area, only received 23% COD and 20% TN, which consist with the much worsen water quality of JZB than that of OCAYS. On the other hand, the source apportionment of COD and TN loads in the PSRs entering JZB and the OCAYS was similar. The agricultural and domestic sources with high pollution intensity account for more than 80%, while the industrial and service sources with low pollution intensity account for less than 20%. While Gini coefficients, COD 0.81 and TN 0.84 which are much higher than the ‘imbalance' threshold of 0.4, show the uneven industrial structure of Qingdao. These results may be useful in the determination of land-based pollution total amount control at the PSR level.     

Time-Domain Full Waveform Inversion Using the Gradient Preconditioning Based on Transmitted Wave Energy

The gradient preconditioning approach based on seismic wave energy can effectively avoid the huge memory consumption of the gradient preconditioning algorithms based on the Hessian matrix. However, the accuracy of this approach is prone to be influenced by the energy of reflected waves. To tackle this problem, the paper proposes a new gradient preconditioning method based on the energy of transmitted waves. The approach scales the gradient through a precondition factor, which is calculated by the ‘approximate transmission wavefield' simulation based on the nonreflecting acoustic wave equation. The method requires no computing nor storing of the Hessian matrix and its inverse matrix. Furthermore, the proposed method can effectively eliminate the effects of geometric spreading and disproportionality in the gradient illumination. The results of model experiments show that the time-domain full waveform inversion(FWI) using the gradient preconditioning based on transmitted wave energy can achieve higher inversion accuracy for deep high-velocity bodies and their underlying strata in comparison with the one using the gradient preconditioning based on seismic wave energy. The field marine seismic data test shows that our proposed method is also highly applicable to the FWI of field marine seismic data.     

Simulation Study of Potential Impacts of Tidal Farm in the Eastern Waters of Chengshan Cape,China

The sea area east of Chenshan Cape has peak tidal current flows that exceed 2.3 m s-1, which make it a promising site for the development of tidal current energy. Before these resources can be exploited, a comprehensive assessment is needed of the potential environmental impacts of the extraction of this energy. In this paper, we describe our construction of a three-dimensional hydrodynamic model of the waters near Chengshan Cape, and verify the performance of the model using continuous data measured in situ. We modeled the potential impacts of the exploitation of these resources on the flow field by adding a momentum loss term in the governing equation of the model. Simulation results show that an assumed tidal farm with an estimated power output of 20.34 MW would have a significant impact on the surrounding water level, especially next to the farm, where fluctuation could reach 6 cm. The maximum drop in the flow velocity in the wake of the farm was predicted to be more than 0.8 m s-1, and this influence would extend 10 km downstream.     

Predictability of Chinese Summer Extreme Rainfall Based on Arctic Sea Ice and Tropical Sea Surface Temperature

Chinese summer extreme rainfall often brings huge economic losses, so the prediction of summer extreme rainfall is necessary. This study focuses on the predictability of the leading mode of Chinese summer extreme rainfall from empirical orthogonal function(EOF) analysis. The predictors used in this study are Arctic sea ice concentration(ASIC) and regional sea surface temperature(SST) in selected optimal time periods. The most important role that Arctic sea ice(ASI) plays in the appearance of EOF1 may be strengthening the high pressure over North China, thereby preventing water vapor from going north. The contribution of SST is mainly at low latitudes and characterized by a significant cyclone anomaly over South China. The forecast models using predictor ASIC(PA), SST(PS), and the two together(PAS) are established by using data from 1980 to 2004. An independent forecast is made for the last 11 years(2005-2015). The correlation coefficient(COR) skills between the observed and cross-validation reforecast principal components(PC) of the PA, PS, and PAS models are 0.47, 0.66, and 0.76, respectively. These values indicate that SST is a major cause of Chinese summer extreme rainfall during 1980-2004. The COR skill of the PA model during the independent forecast period of 2004-2015 is 0.7, which is significantly higher than those of the PS and PAS models. Thus, the main factor influencing Chinese summer extreme rainfall in recent years has changed from low latitudes to high latitudes. The impact of ASI on Chinese summer extreme rainfall is becoming increasingly significant.