Modeling fluvial response to in‐stream woody vegetation: implications for stream corridor restoration

River restoration and bank stabilization programs often use vegetation for improving stream corridor habitat, aesthetic and function. Yet no study has examined the use of managed vegetation plantings to transform a straight, degraded stream corridor into an ecologically functional meandering channel. Experimental data collected using a distorted Froude‐scaled flume analysis show that channel expansion and widening, thalweg meandering and riffle and pool development are possible using discrete plantings of rigid, emergent vegetation, and the magnitudes of these adjustments depend on the shape of the vegetation zone and the density of the vegetation. These experimental results were verified and validated using a recently developed numerical model, and model output was then used to discuss mechanistically how rivers respond to the introduction of in‐stream woody vegetation. Finally, a hybrid method of meander design is proposed herein where managed vegetation plantings are used to trigger or force the desired morphologic response, transforming a straight, degraded reach into a more functional meandering corridor. It is envisioned that such numerical models could become the primary tool for designing future stream restoration programs involving vegetation and assessing the long‐term stability of such activities. Copyright © 2007 John Wiley & Sons, Ltd.     

我国省域工业主导产业的遴选与发展

工业主导产业在国民经济发展中起着决定性和指向性的作用。主导产业的选择是经济发展阶段的重要课题。依据6个量化指标,从4个维度对"十一五"期间主导产业进行遴选,发现以能源及相关产业为代表的重化工业是各省的重点,高新技术产业成为主导产业的省份较少,劳动密集型产业依然是东部发达省市的重点,预期中的产业转移并未实现;以行业为变量对各省份的主导产业进行聚类分析,可将31个省份划分为5类,反映了我国各省份主导产业布局特点;在此基础上,依据产业生命周期理论和各地区"十二五"发展趋势,提出了相应的对策建议。     

δ~(18)O, δD and d-excess signatures of ground ice in permafrost in the Beiluhe Basin on the Qinghai-Tibet Plateau,China

In this paper, stable isotope(δ~(18)O, δD) investigations were completed in ground ice from a deep borehole in the Beiluhe Basin on northern Qinghai-Tibet Plateau to unravel the isotopic variations of ground ice and their possible source water. The δ~(18)O and δD of ground ice show distinctive characteristics compared with precipitation and surface water. The near-surface ground ice is highly enriched in heavier isotopes(δ~(18)O and δD), which were gradually depleted from top to bottom along the profile. It is suggestive of different origin and ice formation process. According to isotopic variations, the ice profile was divided into three sections: the near-surface ground ice at 2.5 m is frozen by the active-layer water which suffered evaporation. It is possible that ground ice between 3 and 4.2 m is recharged by the infiltration of snowmelt. From 5 to 6 m, the ground ice show complex origin and formation processes. Isotopic variations from 6 to 11.1 m and 20.55 m indicate different replenishment water. The calculated slope of freezing line(S=6.4) is larger than the experimental value(5.76), and is suggestive of complex origin and formation process of ground ice.     

地方依恋对城市居民社区参与的影响研究 ——以广州为例

基于2015年广州市1 273份居民问卷调查和半结构性访谈数据,结合逐步LPM回归和中介效应模型,探讨地方依恋和社区参与两者关系中存在的中介效应及其传导机制,并系统对比本地居民与外来移民之间的差异。研究发现：① 社区居民的地方依恋能够直接提升其社区参与期望;② 社区参与行为作为一个中介变量,在地方依恋对社区参与期望的影响中发挥中介效应;③ 对比本地居民,外来移民的社区参与行为和期望程度相对较低;④ 外来移民的社区参与行为对其社区参与期望影响的中介效应相对较弱。揭示了中国城市居民社区参与中存在户籍制度壁垒,需要进一步通过社区公共服务均等化措施,提升居民尤其是外来移民的获得感、幸福感和安全感。     

Calculation method for thickness of discontinuous boundary layer of engineering pavement

The boundary layer is a buffer layer of water and heat exchange between the atmosphere and permafrost.Based on the atmospheric boundary layer and heat transfer theory,we established a method for determining the boundary layer thickness of engineering pavement(asphalt and sand pavement)in permafrost region.The boundary layer can be divided into the Boundary Layer Above Surface(BLAS)and the Boundary Layer Below Surface(BLBS).From in-situ monitoring data,the thickness of BLAS was determined through the laminar thickness,and the thickness of BLBS was determined through ground temperature,the heat conduction function,and the mean attenuation function(α).For asphalt pavement,the BLAS thickness varied between 2.90 and 4.31 mm and that of BLBS varied between 28.00 and 45.38 cm.For sand pavement,the BLAS thickness varied between 2.55 and 3.29 mm and that of BLBS varied between 15.00 and 46.44 cm.The thickness varied with freezing and thawing processes.The boundary layer calculation method described in this paper can provide a relatively stable boundary for temperature field analysis.     

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960–2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001–2010) and the predicting period (2011–2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.