The application and comparison of several flux profile relations in CoLM

This paper discusses the important role that flux profile relations play in momentum flux, sensible heat flux, and latent heat flux simulations in CoLM （Common Land Model） and compares the application of three flux profile relation schemes in CoLM by means of the Loess Plateau Land-Atmosphere Interaction Pilot Experiment （LOPEX） of 2005. It reveals that the results simulated by the model barely changed in the original flux profile schemes of the models a~er eliminating the very stable condition and the very unstable condition, and there were only tiny changes in numerical values. This indicates that the corrected terms added to fm（ξm）,fh（ξh） were very tiny and can be ignored under very stable and very unstable circumstances. According to a comparison of the three flux profile relations, the simulation results were basically coherent by using any CoLM： the correlation coefficient of the simulation value and the observed value was 0.89, and this bears on the coherence with the numerical procedures for the flux pro- file relations under unstable circumstances. The simulation results were improved considerably by utilizing the Lobocki flux pro- file schemes, which numerical procedures under unstable circumstances differed significantly fi＇om other three flux profile schemes; in this case the correlation coefficient of the value of simulation and the observed value became 0.95. In the next itera- tion of this study, it will be of great importance for the development of the land surface process model to continue experimenting with the application of some novel flux profile schemes in the land surface process models in typical regions.     

中国北方风蚀区风速变化时空特征分析

利用北方风蚀区155个气象站点1971-2015年平均风速数据,采用气候趋势分析、空间插值和小波分析等方法分析北方风蚀区平均风速的时空变化趋势。结果表明：近45 a来,北方风蚀区年平均风速为2.70 m·s^-1,呈明显减小趋势,其递减速率为0.017 m·s^-1·a^-1（α=0.001）,1980s风速减小最快,1990s减小最缓慢,2010s风速出现增大趋势;我国北方风蚀区四季的平均风速均呈现下降趋势,下降速度春季>夏季>秋季>冬季（α=0.001）,不同年代不同季节风速变化存在较大差异,2010s除春季外其他季节风速均呈现增大趋势;空间分布上显示,风速变化幅度空间分布差异明显,北方风蚀区内的新疆西北部和东南部、青海、内蒙古中部和东北部、黑龙江以及吉林为风速降低较快的区域,甘肃东南部、宁夏、陕西和山西北部以及新疆的东北部和西部等地区是风速降低不明显的区域。春季和夏季风速降低较快的区域面积扩大,冬季和秋季风速降低较缓的区域扩大;平均风速存在多时间尺度的周期性结构特征,28 a时间尺度左右为风速变化的主周期,平均变化周期为18 a。     

2001—2020年黄河流域植被覆盖变化及其影响因素

基于MODIS NDVI植被指数和气象数据集,以集合经验模态分解、趋势分析和随机森林回归分析等方法,分析了黄河流域2001—2020年植被覆盖时空变化特征,并对其气候驱动因素进行探讨。结果表明：（1）2001—2020年黄河流域植被覆盖整体呈显著增长趋势,增速为0.055/10a （P<0.05）,2010年之前增速（0.067/10a）大于2010年之后的增速（0.051/10a）。（2）空间上,植被覆盖增加区域主要分布在陕北黄土高原、甘肃省东南部、内蒙古自治区河套平原等退耕还林还草生态工程实施区域,而植被覆盖显著下降区域则集中在关中平原城市群、黄淮海平原以及青藏高原等区域。（3）气温、降水和CO₂浓度等对黄河流域植被生长起到正向促进作用,且绝对敏感性依次降低,而大气饱和水汽压差、太阳辐射等对植被生长起到抑制作用。本研究结果可为评估气候变化对黄河流域植被覆盖变化的综合影响提供参考依据。     

国外脆弱性理论模型与评估框架研究评述

目前,脆弱性研究作为一种新的研究范式已经在多学科领域中得到了广泛应用,并取得了丰硕成果.但随着研究的深入,学者们发现,由于学科背景及研究视角的差异性,不同研究领域之间存在着结论不兼容和工作重复等问题,迫切需要一个可行的理论模型与评估框架来整合其理论和实践的研究.在对脆弱性概念内涵的发展演变过程分析的基础上,对国外多学科领域中的脆弱性理论模型及评估框架进行了对比研究和评述.研究发现:脆弱性概念的泛化是制约通用脆弱性理论模型与评估框架的关键因素,结合未来脆弱性研究的发展方向,对整合的脆弱性理论模型与评估框架提出了4个方面的要求,即多时空尺度特征、多重扰动特征、耦合系统特征和人文特征.     

基于主体功能区约束的大气污染物总量控制目标分配研究

考虑经济发展水平、污染物排放现状、污染物治理水平、空气质量,特别是国家主体功能区环境目标约束等因素,构建大气污染物排放总量分配的指标体系,用改进的等比例分配方法对2015年国家SO2,NOx总量控制目标进行区域分配。分配结果表明:SO2和NOx削减量大的省份主要集中在华北平原及其周围地区,这些地区污染物排放量大、空气质量较差;削减比例较大的地区主要集中在西部地区以及北京、天津2个直辖市,这些地区单位GDP能耗高、工业污染物去除率低、空气质量差;削减量相对较小的地区主要集中在西南和南部一些省份;削减比例较小的地区主要集中在中南部和南部几个省份,这些地区污染物排放量相对较少,空气质量好于其他省份。     

Research on Creep Deformation and Control Mechanism of Weak Surrounding Rock in Super Large Section Tunnel

Geotechnical and Geological Engineering - In order to solve the difficulties of creep deformation of surrounding rock in super large section tunnel, taking Letuan tunnel of Binlai expressway, a...     

基于CiteSpace的《热带地理》创刊40年文献计量分析

在《热带地理》创刊40年之际,基于CiteSpace软件对其1980—2019年的2 938篇有效文献进行计量分析,以每10年为间隔,分时段对相应文献作关键词共现分析、关键词突现性检测、作者共现分析及机构共现分析,以探究《热带地理》的研究主题演变、历史热点、核心作者及核心机构的合作关系。结果表明,在前20年,《热带地理》研究主题及研究区较为集中,多聚焦于华南地区及其资源开发利用;核心作者间的合作较弱,整体分散,且期刊主要报道的是广州地理研究所等广州地区的研究成果,机构间合作较少。自2000年后研究主题明显增多,形成多元研究热点,研究区范围有所扩大,但仍集中于中国南部;核心作者间形成较多合作团队,团队间合作交流明显增强;高校与其他研究所的研究成果所占比重大幅增加,机构间合作大大加强。     

Location choices of Chinese enterprises in Southeast Asia: The role of overseas Chinese networks

Journal of Geographical Sciences - With the implementation of the “Going out” strategy and the Belt and Road Initiative, China’s investments have become increasingly influential...     

The spatial local accuracy of land cover datasets over the Qiangtang Plateau,High Asia

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.