Response of riparian vegetation to water-table changes in the lower reaches of Tarim River, Xinjiang Uygur, China

The lower reaches of Tarim River in the Xinjiang Uygur region of western China had been dried out for more than 30 years before water began to be diverted from Konqi (Peacock) River via a 927-km-long channel in year 2000, aimed at improving the riparian ecological systems. Since then, eight intermittent water deliveries have been carried out. To evaluate the response of riparian vegetation to these operations, the groundwater regime and vegetation changes have been monitored along the 350-km-long stem of the river using a network of 40 dug wells at nine transects across the river and 30 vegetation plots at key sites. Results show that the water table rose remarkably, i.e. from a depth of 9.87 m before the water delivery to 3.16 m after the third water delivery. The lateral distance of affected water table extended to 1,050 m from the riverbank after the fourth water delivery. The riparian vegetation has changed in composition, type, distribution, and growing behavior. This shows that the water deliveries have had significant effects on restoration of riparian ecosystems.     

土壤剖面的磁学特征及其对交通污染的指示意义——以北京首都机场高速公路为例

对北京首都机场高速公路旁采集的土壤柱状T01剖面的磁学参数和金属元素分析,探讨了研究区内现代交通导致的土壤磁学性质的变化及其对环境污染的响应.结果表明,磁参数(χ,ARM和SIRM)与重金属含量呈同步垂向变化趋势.来源于交通运输排放的污染物是土壤剖面上部(0～8 cm)磁性和金属含量增强的主要原因,8cm以下,土壤基本未受到污染,磁性矿物和重金属含量较低,磁性颗粒变化稳定,基本代表了该地区土壤的自然背景.尽管土壤岩石磁学分析表明剖面上下部受污染和未受污染样品的磁载体均是粒度较粗的多畴磁铁矿,但是结合磁参数比值曲线,说明底部样品的磁颗粒的粒度较顶部偏细.磁性矿物的含量变化没有影响磁颗粒的粒度特征.指标聚类等相关分析表明,土壤磁参数(χ,ARM和SIRM)与重金属元素(Pb,Zn和Cu)含量显著相关;结合模糊聚类分析,磁参数可用于追踪、识别交通污染物质在土壤剖面中的富集、迁移状态,揭示不同深度土壤的污染程度.     

Soil moisture dynamics under different land uses on karst hillslope in northwest Guangxi,China

Temporal and spatial dynamics of soil moisture are little known on karst hillslope with shallow soil in subtropical region. The objectives of this paper were (1) to investigate the temporal dynamics of soil moisture at depth of 0–10 cm under different land uses; and (2) to understand the relationship between mean and coefficient of variation (CV) of moisture contents on karst hillslope in northwest Guangxi, China. Soil moisture contents had a moderate variation (CV 17.5–30.3%) over an 8-month period and they had a significant difference among different land uses at the 0.01 level with a decreasing order: native scrubland > abandoned cropland and sloping cropland > economic forestland. There were higher mean and lower CV of moisture contents in rainy season than those in drought season. Mean and CV of moisture contents had a significant negative linear relationship except in abandoned cropland with higher soil and vegetation heterogeneity. This suggested that spatial variability of soil moisture within sampling sites would decrease when soils were wet and increase when soils were arid. Compared with rainy season, more soil samples may be needed and the interval for sampling should be shortened in drought season. Such information provided some insights to better understand the dynamics and variability of soil moisture at a larger scale in karst region of southwest China.     

Identifying influence areas with connectivity analysis – application to the local perturbation of heterogeneity distribution for history matching

Numerical representations of a target reservoir can help to assess the potential of different development plans. To be as predictive as possible, these representations or models must reproduce the data (static, dynamic) collected on the field. However, constraining reservoir models to dynamic data – the history-matching process – can be very time consuming. Many uncertain parameters need to be taken into account, such as the spatial distribution of petrophysical properties. This distribution is mostly unknown and usually represented by millions of values populating the reservoir grid. Dedicated parameterization techniques make it possible to investigate many spatial distributions from a small number of parameters. The efficiency of the matching process can be improved from the perturbation of specific regions of the reservoir. Distinct approaches can be considered to define such regions. For instance, one can refer to streamlines. The leading idea is to identify areas that influence the production behavior where the data are poorly reproduced. Here, we propose alternative methods based on connectivity analysis to easily provide approximate influence areas for any fluid-flow simulation. The reservoir is viewed as a set of nodes connected by weighted links that characterize the distance between two nodes. The path between nodes (or grid blocks) with the lowest cumulative weight yields an approximate flow path used to define influence areas. The potential of the approach is demonstrated on the basis of 2D synthetic cases for the joint integration of production and 4D saturation data, considering several formulations for the weights attributed to the links.     

Breadth and depth in research on health disparities: commentary on the work of Nancy Krieger

Geocoding and spatial analysis of data describing populations and health events are important methods in health social science now carried out using GIS technology. This commentary considers Nancy Krieger’s work on health disparities in light of the various ways individuals and organizations use geocoded population and health data: analyzing spatial patterns of health and disease including health disparities, aggregating data spatially, assessing health status of individuals based on characteristics of aggregates, modeling neighborhood contextual factors affecting health, designing observation and intervention studies, and delivering health interventions and services. The extent to which her work addresses each of these purposes is considered. The strengths and limitations of the research including choice of spatial analytic units and techniques as reported in the published work are discussed. Krieger’s work, with her colleagues, has used standard methods of spatial analysis to raise the profile of GIS and spatial analysis in the public health community.     

An approximate analytical solution for measuring air permeability of asphalt samples partially saturated with water

In coastal areas, abnormally high pressure may be caused by the tide-induced water table variation under extensive pavements, particularly during rainfall. To simulate the rainfall infiltration effects on the air permeability of asphalt pavements in coastal area, column-shaped asphalt sample was fixed in the upper part of a steel cylinder with its upper surface saturated with ponding water (depth < 5 mm) and open to the atmosphere. The cylinder’s lower part formed an air chamber. The chamber was pressurized and then the air therein was released naturally through the sample. The pressure variation with time in the chamber was recorded for analysis. Based on the Green–Ampt piston model for the surface water infiltration, an approximate analytical solution was derived to describe the pressure–time relationship in the chamber. A new parameter called the escape pressure was introduced to describe the air pressure needed for the chamber air to break through the capillary pressure induced by the ponding water. The analytical solution gave good estimations of both the escape pressures and the harmonic averages of the permeabilities of the wet and dry parts of 14 samples in the sense that excellent fittings were obtained between the observed and predicted air pressures in the air chamber. The estimated escape pressure ranges from 0.0 to 1.74 kPa. The harmonic average of the permeabilities of the wet and dry parts is 5–94% of the dry sample’s permeability.     

The characteristics of the seismic signals induced by landslides using a coupling of discrete element and finite difference methods

Landslide seismic signals support researchers to estimate magnitudes and locations of landslides. They can serve as a crucial data for landslide warning systems. However, the randomness of landslide locations makes the acquisition of landslide-induced seismic signals difficult and limits the number of available field data. The objectives of this study are to establish a numerical modeling approach to examine the characteristics of seismic signals induced by landslides and perform parametrical study. The two-dimensional particle flow code (PFC) and Fast Lagrangian Analysis of Continua (FLAC) are coupled to simulate the landslide process. The force and velocity data at the coupled interfaces of FLAC and PFC are transferred back and forth via a Socket I/O connection. Four locations were monitored for the induced vertical seismic signals, including velocity, acceleration, and stress histories. The signals were analyzed by Hilbert-Huang transform to obtain the time-frequency spectrograms for examining the characteristics of the signals. The particle size, wall friction, particle friction, and parallel bond of PFC input parameters were parametrically investigated. The Xiaolin landslide in 2009 was successfully simulated, and the characteristics of the seismic signals were studied and compared with the data from a broadband seismic station. These results demonstrate that terrain and transition in the movement type of a complex landslide do influence the seismic signals. A landslide with larger rock particles generates lower-frequency content seismic signals. Also, there can be approximately 40 s to escape before a large-scale landslide hits if seismic instrumentation is installed. The method proposed can be further applied for studies on many other large-scale rock avalanches to verify recorded signals and further correlate the signals with the landslide characteristics.     

Lithological and geochemical record of anthropogenic changes in recent sediments of a small and shallow lake (Lake Pusty Staw,northern Poland)

The article presents the results of lithological and geochemical investigations of recent sediments of Lake Pusty Staw. The analysed sediments document about 300 years of the history of this lake. Historical materials indicate that significant changes in the catchment of the lake took place from the beginning of the 18th century (deforestation and afforestation) followed by 19th century tourist development, and 20th century industrialisation. The sediments were dated using the ²¹⁰Pb and ¹³⁷Cs method and core lithology. These made it possible to establish a reliable chronology to the year 1730. The calculated sedimentation rates ranged between 0.17 and 0.83 cm year^–1. There was a period of intensified erosion caused by land clearance between 1734 and 1810, which resulted in an acceleration in sedimentation rate (0.36 cm year^–1) and a change of lithological type of sediment from detritus gyttja to clayey gyttja. On the basis of Cu, Zn, Cd and Pb content in the sediments, it was determined that the beginning of pollution of the lake dates back to the 19th century and was caused probably by the existence of a health resort. A systematic increase in pollution occurred in the 20th century as a result of industrial plants. Normalised with respect to Al, the content of heavy metals in polluted sediments was from several to twenty times higher than in sediments of the preindustrial period, and a comparison of historical materials with changes of sediments in most cases made it possible to identify the direct causes of the increase in pollution.     

Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province,China

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a^-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a^-1<θ<1.7 d·10a^-1, θ is the change slope of maize phenology). The length of vegetative period (VPL) (from emergence to tasseling) was shortened by 0.9 d·10a^-1, while the length of generative period (GPL) (from tasseling to maturity) was lengthened by 1.7 d·10a^-1. The growing season length (GSL) (from emergence to maturity) was lengthened by 0.4 d·10a^-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days (GDD) (p<0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.     

<Emphasis Type="Italic">3D</Emphasis> Modelling of Urban Area Using Synthetic Aperture Radar (SAR)

Synthetic aperture radar (SAR) is a newly-developed remote sensing technology that works in all weather and independent of daylight. Recent satellite designs such as TerraSAR-x, which have resolutions of a couple of meters and sub-meters, have provided appropriate data for modelling and monitoring of urban areas. Image classification and height information extraction is possible considering the nature of SAR data. In this paper, a proper classification method for high-resolution SAR images has been used in urban areas. This classifier is based on statistical models. First, statistical models that are well adapted to urban SAR images are selected. Initial labelling is performed using the maximum likelihood method. A method based on Markov random fields is applied to improve the results by considering neighbourhood information. Meanwhile, topographic information is extracted using the phase difference obtained from SAR interferometry. After classification and height extraction, the homogeneous regions consisting of locations with similar objects are determined. The homogeneous region adjacency graph are generated using vectors containing classification information, extracted objects, height of pixels forming each region, and information on the neighbouring areas. Height and classification information are then merged by assigning height conditions based on the nature of objects and optimizing an energy function. The results obtained, including buildings, streets, and corner reflectors, are easily recognizable. The overall accuracy is improved from 57% in the initial classification to 95% in the employed procedure. Moreover, the accuracy of height estimation is about 2.74 m, which is acceptable for height estimations of buildings with more than one floor.