基于拉格朗日拟序结构的黑潮区域海流运输结构提取和分析

海流的拉格朗日运动对于研究物质输送有着重要意义，拉格朗日拟序结构(LCSs)作为研究海流结构的新型方法，相比于传统欧拉方法更为客观。本文提出了一种新的计算LCSs束的方法，基于25年的平均速度场，利用变分方法计算得到黑潮区域的气候态LCSs，并通过简化合并的方法得到了气候态LCSs束，该LCSs束能够突出地显示出海流特性和运输模式，其代表的平均拉格朗日环流有很强的约束作用，且具有鲁棒性。最终我们获得了气候态下12个月份的流场结构图，揭示了月周期性拉格朗日环流规律。本文还利用虚拟粒子输运、多年浮标轨迹以及气候态温盐异常3种方法进行了验证，与拉格朗日运输模式相吻合，证明了海流拉格朗日拟序结构的准确性和可靠性。     

Tracing the settlement region of massive floating green algae in the Yellow Sea

Outbreaks of large-scale green tides formed by Ulva prolifera in the Yellow Sea(YS)cause heavy ecological damages and huge economic losses.However,the ecological consequences of green tides remain poorly understood due to the lack of knowledge on the settlement region of massive green algae floating in the YS.In this study,we established a method to trace the settlement region of floating green algae,using 28-isofucosterol preserved in sediment as the specific biomarker for green algae.Sterols including 28-isofucosterol in surface sediment samples collected during an investigation in the YS and the Bohai Sea(BS)in August 2015 were analyzed using gas chromatography coupled with a mass spectrometer(GC-MS).Based on the content of 28-isofucosterol in sediment samples,the potential settlement region of loating green algae was identified in the sea area southeast to the Shandong Peninsula around the sampling site H06(122.66°E,36.00°N).This paper presents a first result on the settlement region of floating green algae in the YS for providing a solid basis to elucidate the ecological consequences of green tides in the area.     

One-dimensional consolidation of soil under multistage load based on continuous drainage boundary

In engineering practice, a rapid loading rate can result in ground failure when the strength of soft soils is relatively low, and a multistage loading scheme is always utilized to deal with this situation. Firstly, under a multistage load and the continuous drainage boundary, an analytical solution of excess pore-water pressure and consolidation degree is obtained by virtue of the superposition formula of excess pore-water pressure, and a more general continuous drainage boundary under arbitrary time-dependent load is developed. Then, a comparison with existing analytical solutions is conducted to verify the present solution. A preliminary attempt on applying the continuous drainage boundary into the finite element model is made, and the feasibility of the numerical model for the one-dimensional consolidation under the continuous drainage boundary is verified by comparing the results calculated by FEM with that from present analytical solution. Finally, the consolidation behavior of soil is investigated in detail for different int erface parameters or loading scheme. The results show that, in land reclamation projects, a horizontal drain should be placed close to the boundary with a smaller interface parameter to improve the consolidation efficiency. The degree of consolidation is also related to the applied time-dependent load and interface parameters.     

Hydrological cycle and water balance estimates for the megadune–lake region of the Badain Jaran Desert,China

The hydrology and water balance of megadunes and lakes have been investigated in the Badain Jaran Desert of China. Field observations and analyses of sand layer water content, field capacity, secondary salt content, and grain size reveal 3 types of important natural phenomenon: (a) vegetation bands on the leeward slope of the megadunes reflect the hydrological regime within the sandy vadose zone; (b) seepage, wet sand deposits, and secondary salt deposits indicate the pattern of water movement within the sandy vadose zone; (c) zones of groundwater seeps and descending springs around the lakes reflect the influence of the local topography on the hydrological regime of the megadunes. The seepage exposed on the sloping surface of the megadunes and gravity water contained within the sand layer confirm the occurrence of preferential flow within the vadose zone of the megadunes. Alternating layers of coarse and fine sand create the conditions for the formation of preferential flows. The preferential flows promote movement of water within the sand layer water that leads to deep penetration of water within the megadunes and ultimately to the recharging of groundwater and lake water. Our results indicate that a positive water balance promotes recharge of the megadunes, which depends on the high permeability of the megadune material, the shallow depth of the surface sand layer affected by evaporation, the occurrence of rainfall events exceeding 15 mm, and the sparse vegetation cover. Water balance estimates indicate that the annual water storage of the megadunes is about 7.5 mm, accounting for only 8% of annual precipitation; however, the shallow groundwater per unit area under the megadunes receives only 3.6% of annual precipitation, but it is still able to maintain a dynamic balance of the lake water. From a water budget perspective, the annual water storage in the megadunes is sufficient to serve as a recharge source for lake water, thereby enabling the long‐term persistence of the lakes. Overall, our findings demonstrate that precipitation is a significant component of the hydrological cycle in arid deserts.     

“东方之星”客轮翻沉事件周边区域风灾现场调查与多尺度特征分析

2015年6月1日21:30左右长江湖北监利段发生"东方之星"客轮翻沉特大事故。本文根据事发周边陆地区域现场天气调查结果,结合卫星和雷达观测资料分析认为,6月1日21:00-21:40左右事发江段和周边区域发生了下击暴流导致的强烈大风灾害,最强风力超过12级,并具有空间分布不连续、多尺度和强灾害时空尺度小等特征。事发周边区域北部受中气旋影响陆地区域(顺星村、老台深水码头、四台村养猪场附近、新沟子养鸡场附近等)灾情较南部阵风锋及其后侧下击暴流影响的陆地区域更为显著。综合雷达观测资料和现场调查资料分析判断多数调查点灾害为显著微下击暴流所致,其中老台深水码头有龙卷发生的可能。导致此次风灾的强对流风暴气流具有显著的多尺度性;事发周边区域北部的四台村养猪场附近树林中同时发生了多条相邻的微下击暴流条迹,呈现出辐散和辐合交替分布的特征,展示了此次强对流风暴中大气运动的复杂分布特点。虽然下击暴流会伴随中小尺度的涡旋特征,但此次现场调查发现的与下击暴流相联系的辐合特征水平尺度仅几十米,远小于弓形回波两端的书挡涡旋或者中涡旋等几千米级的水平尺度。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data

The Paris agreement signed in April, 2016 aims to balance global anthropogenic carbon emissions and terrestrial carbon sinks by the middle of the 21^st century. To fulfill this goal, it is necessary to calculate carbon fluxes of different regions reliably. The global carbon assimilation system is an effective technique for achieving this goal. The Ministry of Science and Technology of China supports the project entitled as study on the global carbon assimilation system based on multisource remote sensing data through the national key research and development programs for global change and adaptation during the thirteen-five period. This project will develop synergic inversion techniques for retrieving key parameters of biological and atmospheric cycles and for assimilating multisource remote sensing and ground based data. Then, the high resolution global carbon assimilation system coupled with an ecological model will be constructed. This system is able to assimilate jointly multisource observation data and to optimize key model parameters, photosynthesis and respiration carbon fluxes of global terrestrial ecosystems, and anthropogenic carbon emission fluxes of key regions. This system will be used to study quantitatively the spatial and temporal patterns of carbon fluxes of global terrestrial ecosystems and anthropogenic carbon emission fluxes of key regions and to identify the mechanisms driving the global terrestrial carbon sinks and sources. The outputs of this study will be helpful for the fulfillment of the key research and development programs for global change and adaptation and provide valuable data and technical support for the decision-making in China.