翁泉沟含铀硼铁矿床综合开发利用研究与对策

翁泉沟含铀硼铁矿中硼(B2O3)储量约占我国总储量的一半,矿床经勘探后一直没有很好得到利用。在综合利用资料积累与地质研究基础上,认为影响矿床利用的因素主要为矿石分解状况。研究认为矿床中硼镁铁矿-磁铁矿和硼镁石-磁铁矿两种主要类型矿石中绝大部分为可利用的变质后期热液作用产生的硼镁石-磁铁矿型矿石。这种热液作用形成的矿石是有规律可寻的。为达到综合利用的目的,有必要按不同类型矿石重新圈定矿体,根据不同矿体中硼镁铁矿分解率指标,选择两种不同综合利用方案。     

燕山造山带构造变形格局研究及相关问题

燕山造山带具有极其复杂的地质结构构造，其复杂性在现有公开出版的地质图件中未能有效地反映出来。从事地学研究的科研人员，以公开出版的地质图件为基础所衍生的相关分析图件和由此作出的结论与野外实际地质情况往往相去甚远。本文作者近年来所做基础地质调查成果显示，基础地质调查成果的缺陷成为制约国家地学科研发展的严重障碍。影响基础地质调查成果质量提高的原因很多，但较为重要的是国家对基础地学科研资金的政策性投入存在问题。     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

京津唐地区HFMD时空变异分析与影响因子探测

手足口病（HFMD）是一种多发于儿童的常见传染病。近年来,中国HFMD发病人数逐年上升,疾病疫情也日益受到社会广泛关注。虽已有不少相关研究,但对于探测其时空异质性及量化潜在影响因子解释力的研究仍然较少。本文采用地理探测器及贝叶斯时空层次模型,对2009-2013年京津唐地区HFMD发病率的时空异质性进行分析,并量化各影响因子及其两两交互作用对HFMD发病率的解释力。结果表明：① HFMD的相对风险存在时间异质性,其发病风险在春夏季（5-7月）达到峰值,而冬季（12-次年2月）发病风险最低;② HFMD的相对风险存在空间异质性,在经济发达的地区HFMD发病率较高;③ 影响HFMD发病率时间异质性的主要气象因子为平均温度、累积降水、相对湿度,解释力分别为0.38,0.27,0.13,且交互作用都大于独自影响的作用,如平均温度和相对湿度、平均温度和降水,平均温度和风速两两交互的解释力分别为0.43, 0.40, 0.42。通过研究京津唐地区HFMD发病率的时空异质性以及影响因子的量化状况,为本地区HFMD的预防和控制提供理论依据。     

Evaluation of NLDAS‐2 evapotranspiration against tower flux site observations

The North American Land Data Assimilation System project phase 2 (NLDAS‐2) has run four land surface models for a 30‐year (1979–2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS‐2 for investigating land–atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997–30 September 1999 and daily ET u‐sing in situ observations at the AmeriFlux network over the conterminous USA for an 8‐year period (2000–2007). The NLDAS‐2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd.     

1983—2017年宁夏盐池县生态治理政策的类型与变化——基于政策工具视角

政策工具是政府实施政策的手段。结合盐池县1983—2017年出台的生态治理政策，运用内容分析法，从政策工具视角，对盐池县生态治理政策的类型与变化进行了分析，并深入探讨其原因。结果表明：强制型和混合型政策工具占主导地位，其中，规制、直接提供、信息与劝诫、补贴与奖励4种工具使用频率最高，自愿型工具的使用还很缺乏。政策工具的运用受到中央政策的显著影响。以后应当开发更多可利用的政策工具，并对不同政策工具进行优化组合。通过本研究可深入了解生态脆弱区地方政府生态政策的政策工具使用情况，为生态脆弱区生态保护的政策工具选择与优化组合提供参考。     

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

The potential of contribution of mangrove-derived organic matter in intertidal sediments as a proxy of mangrove development in the northern Beibu Gulf

Located between terrestrial and marine ecosystems, mangrove forests are sensitive to changes in climate. The responses of mangrove ecosystems to climate change in the future can be understood by reconstructing past mangrove dynamics using proxies preserved in the intertidal sediments. Considering the complexity of the proxies commonly used, it is necessary to develop a relatively simple, inexpensive proxy. In this study, available chemical tracers (δ13C_org and C:N) of the four cores (YLW02, YLW03, O18, and Q37) from the intertidal zone of the northern Beibu Gulf (NBG) and a three-end-member (mangrove, sea grass, and suspended particulate matter) model was utilized to determine the contribution of mangrove-derived organic matter (CMOM) in carbonate-free sediments. Compared with the summed concentration of mangrove pollen (SCMP), a significant positive correlation between CMOM and SCMP is displayed. The calculated CMOM for an additional 210Pb-dated sediment core from the Yingluo Bay, NBG (YLW01) clearly indicates a mangrove development going through degradation, flourishing, relative degradation, and relative flourishing, which are separately in correspondence with the lowest, highest, lower, and higher air temperature and rainfall in the time intervals of 1890–1918 AD, 1919–1956 AD, 1957–1990 AD, and 1991–2010 AD. This suggests that CMOM preserved in intertidal sediments has a potential to reconstruct historical mangrove development in high resolution, at the very least, along the coasts of the NBG.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Prediction of the South China Sea Dipole Using SSA-MEM

ABSTRACT

A dipole structure appears in the sea surface height off the central coast of Vietnam during boreal summer in the South China Sea. This dipole, which possesses a chlorophyll signature associated with higher phytoplankton concentrations arising from nutrient upwelling, is important for the productivity of local fisheries. Multi-satellite sea level anomalies are used to investigate the life cycle of the dipole structure. By applying empirical orthogonal function (EOF) analysis, the third EOF mode (EOF 3) is found to represent the major variations of the dipole structure. By removing the temporal noise of EOF 3, a South China Sea dipole index is defined. This index captures the life cycle of the dipole including its generation, mature strength, and final termination. Both one-dimensional and two-dimensional forecasts are generated using a statistical forecasting method that combines singular-spectrum analysis and the maximum entropy method. The appearance of the dipole structure can be predicted with an accuracy of 78% at one-month lead times and an accuracy of 61% at one-year lead times.