长江口邻近海域夏季大型底栖生物群落特征

本文根据2014年6月长江口邻近海域大型底栖生物的调查资料, 采用优势度指数, 物种多样性指数、丰富度指数、均匀度指数, Bray-Curtis相似性聚类和非参数多维标度排序(nMDS)标序方法, 分析了长江口邻近海域夏季大型底栖生物的群落特征。本次调查共采集大型底栖生物135种, 其中多毛类66种, 甲壳动物33种, 棘皮动物14种, 软体动物13种, 其他类群9种。调查海域的大型底栖生物平均丰度为122.2ind/m₂,平均生物量为7.8g/ m₂。丰度、生物量和多样性指数在不同海区间的空间差异均不显著。大型底栖生物在20%的相似性水平上可以划分为8个群组,各站位间相似性水平较低。ABC曲线表明,伴随海岸带开发及人类活动的持续影响, 长江口邻近海域底栖生境的稳定性受到轻微扰动, 建议继续开展长期连续的监测, 为研究长江口海域环境变化和大型底栖生物群落演替提供基础资料。     

内蒙古科尔沁右翼中旗协和尔斯德中生代火山沉积地层时代研究

内蒙古科尔沁右翼中旗协和尔斯德一带出露一套中生代地层,岩石组合主要为酸性火山碎屑岩、火山碎屑沉积岩夹碎屑沉积岩及酸性火山熔岩。1∶50000区调依据在该套地层上部层位发现的木化石组合确定其时代为中—晚侏罗世,结合岩石组合,将该套地层划分为上侏罗统满克头鄂博组。为了准确厘定该套地层时代,为木化石延限研究及区域生物地层划分对比提供依据,本次研究在低于产木化石层位的酸性火山碎屑岩中采取了锆石测年样品(LA-ICP-MS),获得锆石U-Pb年龄(165±1)Ma,时代为中侏罗世。同时采取了侵入该套地层的斑状细晶闪长岩测年样品,获得锆石年龄(131±1)Ma,限定了地层形成的上限年龄。根据岩性组合的区域对比、测年结果、木化石组合时限、地层产状特征,认为该套地层应划为中侏罗统新民组,是突泉火山-沉积盆地充填物的一部分。     

Effect of climate change on water resources in the Yuanshui River Basin: a SWAT model assessment

The Yuanshui River Basin is one of the most important river basins ensuring food production and livelihoods in the Hunan and Guizhou Provinces of China. Based on digital elevation model, land use, soil, and meteorological data, the soil and water assessment tool was used to analyze the response of water resources in the basin to climate change. Specifically, the monthly runoff from the Yuanshui River Basin was simulated. Runoff measurements from the 1961–1990 series were used to calibrate model parameters, and measurements from the 1991–2010 series were used for model validation. The Nash–Sutcliffe efficiency coefficient, correlation coefficient, and water balance error were used to evaluate the simulation results; the values obtained for these parameters were 0.925, 0.929, and 2.0%, respectively, indicating that the established model can be applied successfully to runoff simulations. To evaluate the effects of climate change and human activities on runoff, 24 different climate scenarios were modeled. By comparing the model simulation results with the baseline scenario, the effects of climate change were analyzed by year, during the dry season, and during extremely dry conditions. The results showed that runoff decreased with increasing air temperature and decreasing precipitation, and that the effects of rainfall on runoff were greater than those of air temperature. Under the same baseline conditions, the effects of climate change on runoff were most pronounced during extremely dry months.     

Carbon dioxide emission reduction quota allocation study on Chinese provinces based on two-stage Shapley information entropy model

Chinese central government made a commitment to achieve a 40–45% reduction in carbon dioxide (CO₂) per unit of GDP by 2020 compared with 2005. This targeted reduction was allocated averagely among all the provinces rather than individually according to different situations of each province. Though some research has been done regarding this rough allocation, two shortcomings in previous studies exist: Firstly, CO₂ marginal abatement cost (MAC) has been ignored as one of the CO₂ emission reduction allocation indexes. Secondly, either subjective or objective method has been used rather than comprehensively of both subjective and objective method to calculate the weight of each index in the previous studies. In order to fill the gaps, this paper builds a two-stage Shapley information entropy model to allocate CO₂ emission reduction quota among the Chinese provinces based on the equity and efficiency principles. Afterward, three CO₂ emission reduction quota allocation scenarios have been proposed. The results show that the CO₂ MAC is an indispensable index in CO₂ emission reduction quota allocation, because its value of CO₂ Shapley information entropy is the highest among five indexes. CO₂ emission reduction quota of lower-MAC provinces should be allocated larger, while the quota of higher-MAC provinces should be allocated smaller. Therefore, two suggested policies have been proposed: First, differential CO₂ emission reduction quota allocation should be proposed. Second, synergetic development should be promoted.     

Network-based triple-frequency carrier phase ambiguity resolution between reference stations using BDS data for long baselines

Network-based ambiguity resolution (AR) between reference stations is the prerequisite to realize a precise real-time kinematic positioning service. With the help of BDS triple-frequency signals, we can efficiently deal with the ionospheric delay and tropospheric delay, and achieve rapid and reliable AR. To overcome the inaccurate ionospheric delay estimated by the geometry-free three carrier ambiguity resolution (GF TCAR) technique, which leads to failure in the original ambiguity resolution, we propose an ionospheric-free (IF) TCAR method to resolve the ambiguity between the reference stations over long baselines. Taking full advantage of the known positions of the reference stations, the easily resolved extra-wide-lane (EWL) ambiguity, and the IF phase combinations, we can reliably fix the wide-lane (WL) ambiguity. A Kalman filter is applied to estimate precise IF ambiguities and the original ambiguity is resolved with the fixed WL ambiguity. A numerical analysis with triple-frequency BDS data from three long baselines of a CORS network is provided to compare the AR performance of GF TCAR with that of IF TCAR. The results show that both methods can reliably resolve the WL ambiguity with a remarkable correctly-fixed rate of higher than 99%, and the reliably-fixed rates of the IF TCAR slightly increase from 92.19, 94.67 and 94.61–98.26, 99.54 and 97.51% for the three baselines. Herein “correctly-fixed” and “reliably-fixed” mean the difference between the float ambiguity and the true one are less than ± 0.5 and ± 0.25 cycles, respectively. On the other hand, the AR performance of the original signals with the IF TCAR method is much better than that with the GF TCAR method attaining a 100% correctly-fixed rate, while the GF TCAR method can hardly fix the original ambiguity with the largest bias being as much as 4 cycles because of the amplified systematic bias.     

An improved ionosphere interpolation algorithm for network RTK in low-latitude regions

A traditional interpolation algorithm with the linear interpolation method (LIM) using a fixed number of reference stations is widely used in network RTK to obtain the ionospheric delays for the users. In low-latitude regions, where the ionosphere is relatively active, however, large interpolation errors exist, especially for satellites at low elevation angles. Considering the characteristics of “coinciding ionospheric pierce points (CIPPs)” with a similar nature of ionospheric delays, an improved interpolation algorithm is proposed. In this algorithm, all stations with CIPPs are used to establish the interpolation model; thus, more precise interpolation model is achieved. To validate the performance of the proposed algorithm, data from some reference stations in Guangdong Province of China were used, and the results are compared with those with the traditional interpolation algorithm. Numerical analysis shows that the interpolation accuracy of the proposed algorithm increases by 10–30% compared with the traditional one. Since the number of reference stations is flexible, the proposed algorithm can also balance the model accuracy with the computation burdens. In addition, the proposed algorithm is less affected by the selection of master reference station. In terms of network RTK on-the-fly positioning, the time-to-first-fix is reduced when replacing the traditional interpolation algorithm with the proposed one.     

地理国情普查基本统计专题地图实践与探讨

利用地理国情基本统计分析软件对地理国情普查预处理后数据进行基本统计分析。根据基本统计结果、基本统计汇总表及统计报告,制作行政区划四至点、高程分级、坡度分级、水域分布、水域统计、铁路与道路、行政村驻地分布图,并对地理国情普查成果及统计分析成果的应用推广服务提出建议。     

Performance evaluation of ensemble learning techniques for landslide susceptibility mapping at the Jinping county,Southwest China

Natural Hazards - The objective of this study is to investigate different ensemble learning techniques namely Bagging, Boosting, and Stacking for LSM at the Jinping county, Southwest China. Two...