Analytical investigation of the exact groundwater divide between rivers beyond the Dupuit–Forchheimer approximation

The groundwater divide is a key feature of river basins and significantly influenced by subsurface hydrological processes. For an unconfined aquifer between two parallel rivers or ditches, it has long been defined as the top of the water table based on the Dupuit–Forchheimer approximation. However, the exact groundwater divide is subject to the interface between two local flow systems transporting groundwater to rivers from the infiltration recharge. This study contributes a new analytical model for two-dimensional groundwater flow between rivers of different water levels. The flownet is delineated in the model to identify groundwater flow systems and the exact groundwater divide. Formulas with two dimensionless parameters are derived to determine the distributed hydraulic head, the top of the water table and the groundwater divide. The locations of the groundwater divide and the top of the water table are not the same. The distance between them in horizontal can reach up to 8.9% of the distance between rivers. Numerical verifications indicate that simplifications in the analytical model do not significantly cause misestimates in the location of the groundwater divide. In contrast, the Dupuit–Forchheimer approximation yields an incorrect water table shape. The new analytical model is applied to investigate groundwater divides in the Loess Plateau, China, with a Monte Carlo simulation process taking into account the uncertainties in the parameters.     

2007-2017年中国沙尘气溶胶的三维分布特征及输送过程

利用最新发布的CALIPSO产品，构建了2007-2017年中国沙尘气溶胶的三维分布，并结合HYSPLIT-4模式和再分析数据，探讨了沙尘的三维输送过程。结果表明：中国的沙尘排放源区主要是塔克拉玛干沙漠和巴丹吉林沙漠，沙尘气溶胶出现频率分别为60%和35%。塔克拉玛干沙漠排放的沙尘主要（50%~70%）停留在源地0~6 000 m高度，少部分向东输送至甘肃和内蒙古；巴丹吉林沙漠排放的沙尘则主要向东输送。中国沙尘排放量在春季最大，向东输送最强；夏季，东亚夏季风限制了沙尘向东输送；秋季，沙尘排放减弱，输送强度和夏季相当；沙尘排放量在冬季最小，输送最弱。夏季，沙尘在输送过程中可被抬升至高度5 000 m以上，春季次之，秋、冬季的沙尘主要在低层大气输送。沙尘在向东输送的过程中被抬升并和当地人为污染物混合变为污染性沙尘，华北地区污染性沙尘出现频率高达30%；输送到海洋的沙尘也会与洋面上（0~3 000 m高度）的海盐气溶胶混合，出现频率约为10%。     

四川盆地广安地区中二叠统栖霞组岩石特征与沉积环境

四川盆地中二叠统栖霞组勘探发现系列油气，资源潜力巨大。但广安地区中二叠统栖霞组的岩石学特征及沉积环境研究薄弱。在野外地质调查的基础上，结合室内岩石学、岩相学等综合分析，对广安地区栖霞组碳酸盐岩岩石特征、沉积相类型及其古地理展布特征进行了系统研究。结果表明：广安地区栖霞组主要发育亮晶颗粒灰岩、亮晶生物碎屑灰岩、微晶生物碎屑灰岩、微晶颗粒灰岩、生物碎屑微晶灰岩、含生物碎屑微晶灰岩和泥晶灰岩7种岩石类型；碳酸盐岩颗粒主要以生物碎屑为主，部分层位发育球粒；古生物化石以三叶虫、腕足和有孔虫为主，同时可见棘皮类和藻类；栖霞组沉积期主要为碳酸盐岩台地沉积环境，其中栖霞组晚期（栖二段）台缘滩和台内滩较为发育，为该区油气成藏提供了有利条件。     

大口径射电望远镜电磁兼容评估技术研究

电磁兼容性是设备或系统的重要性能指标, 也是保障系统的工作效能和提高系统可靠性的重要因素. 大口径射电望远镜运行阶段, 台址周围无线电业务及内部潜在的电磁干扰会降低观测系统灵敏度、影响天文观测的质量. 本论文针对拟建的新疆110 m全向可动射电望远镜(Qi Tai raido Telescope, QTT)开展了系统电磁兼容评估技术及控制方法研究, 具有重要的工程应用价值. 首先, 依据现有电波环境测量方法的不足, 深入分析了仪器设备的关键参数配置方法及测量时间计算方法, 采用Y因子法校准测量数据, 提出一种准实时电波环境测量方法. 面向高重复性宽带频谱, 分析了宽带频谱信号和噪声特征, 结合标准差理论, 提出一种基于邻值比较的信噪分离方法, 并采用邻值统计方法优化关键参数, 提高信噪分离精度. 针对QTT台址, 开发了自动化电波环境监测系统, 该系统6 GHz以下频段系统增益大于40 dB, 系统噪声系数小于2 dB, 测量不确定度小于1.49 dB, 具有极高的系统灵敏度和测量精度; 分析了频谱监测数据流, 设计了基于HDF5 (Hierarchical Data Format version 5)的数据存储格式, 开发了自动化电波环境测量和监控软件及数据处理软件. 依据QTT台址长期监测数据, 评估分析了台址电磁环境、主要干扰源特征及其影响. 其次, 提出大口径射电望远镜馈源口面干扰电平限值量化方法, 建立了基于台址地形的电波传播模型, 分析了现有电波传播模型的优缺点及适应性, 结合QTT台址实际地形及地质特征, 采用Longley-Rice和Two-Ray电波传播模型, 预测分析了QTT台址潜在干扰区域电磁干扰达到射电望远镜的电波路径衰减, 结合大口径射电望远镜天线增益量化方法, 提出设备所在位置干扰电平限值量化方法, 运用该方法对QTT台址潜在干扰区域的干扰电平限值进行量化. 依据设备所在位置干扰电平限值, 调研分析了国内外军用、民用电磁兼容测量标准, 结合电磁干扰对射电天文观测的影响, 提出一种大口径射电望远镜电磁兼容控制方法, 解决了现有电波暗室测量系统无法直接测量评估电子设备电磁兼容的问题, 该电磁兼容控制方法计划应用于QTT建设及运行阶段, 确保系统拥有良好的电磁兼容性. 最后, 依据QTT台址潜在干扰区域干扰电平限值, 结合典型电子设备电磁辐射频谱, 分析了QTT电磁兼容设计需求, 提出电磁兼容设计初步方案. 另外, 针对台址建筑设施内的中低电磁辐射干扰源, 提出一种低成本建筑屏蔽方法, 应用于QTT台址现有建筑.     

Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.     

鄂尔多斯盆地南缘黄陵地区煤铀兼探钻孔数据集成与三维地质模型构建

鄂尔多斯盆地南缘黄陵地区铀成矿前景良好。中国地质调查局在该地区组织实施了含铀岩系三维地质调查工作，以寻找可地浸砂岩型铀矿找矿靶区为目标，采用“煤铀兼探”、“油铀兼探”的新思路，对煤田钻孔资料进行“二次开发利用”，开展勘查选区研究，完成了354口煤田钻孔（其中筛选出潜在砂岩型铀矿（化）孔49口）和21口铀矿验证钻孔（其中工业矿（化）孔16口）的数据采集建库，在此基础上建立了专题成果图集及三维地质模型。该数据库主要由含铀岩系地层厚度等值线图、砂体厚度等值线图、顶底板埋深等值线图、含砂率等值线图、放射性异常等值线图等专题成果图集和三维地质结构模型组成，为铀矿勘探开发提供了有利支撑和服务作用。     

Climatological Characteristics of the East Asian Winter Monsoon Simulated by CWRF Regional Climate Model

Based on the ERA-Interim atmospheric reanalysis data from the European Medium-Term Weather Forecast Center from 1979 to 2016 and the ERSSTv4 sea surface temperature data from the US National Oceanic and Atmospheric Administration, the regional climate model CWRF was used to simulate the climate characteristics in East Asia. The results show that the CWRF model can well reproduce the average characteristics of the East Asian winter monsoon circulation, including the location and intensity of the low-level continental cold high pressure and variation characteristics of wind field in high and low levels. The occurrence area and frequency of the north wind in the simulation and the reanalysis data were further calculated and compared. It is shown that they are basically consistent. The distribution of air temperature and precipitation over China are well represented by the model. The water vapor transport is also in good agreement with the reanalysis data. The water vapor from the Bay of Bengal plays a vital role in the precipitation over South China. The simulation results of apparent heat source and apparent moisture sink show that the model can well simulate the thermal difference between the East Asian continent and the adjacent sea area. The analysis results indicate that CWRF model has the ability to simulate the main characteristics of the East Asian winter monsoon.     

Multi-stage metasomatism of lithospheric mantle by asthenosphere-derived melts: evidence from mantle xenoliths in daxizhuang at the eastern North China craton

Mineralogy and Petrology - A detailed study on petrology and mineral chemistry of 12 mantle xenoliths from Late Cretaceous basaltic lava flows at Daxizhuang has been conducted to constrain the...     

基于多变量LSTM神经网络的地下水水位预测

为解决以往模型未考虑地下水位相关影响因素的问题，探讨长短期记忆（LSTM）神经网络在地下水位预测中的应用，利用长短期记忆神经网络，采用多变量输入的方式，构建了基于多变量LSTM神经网络的地下水水位预测模型。以泰安市岱岳区J1号监测井为例，采用2001-2014年地下水水位动态监测资料与相关影响因素数据，利用多变量LSTM神经网络对2015-2016年地下水位进行预测，并与单变量LSTM神经网络和反向传播（BP）神经网络进行对比。研究结果表明：以相关影响变量为输入的BP神经网络无法考虑时序变化规律，预测均方根误差最大，为2.399 3；以地下水位为变量输入的单变量LSTM神经网络仅能根据时序变化作出相应预测，无法考虑相关变量影响，预测均方根误差为2.102 2；基于多变量输入的LSTM神经网络的预测精度显著高于单变量LSTM神经网络和BP神经网络，预测均方根误差最小，仅为1.919 1。总体上，多变量LSTM神经网络地下水位预测模型仅在某些峰值处误差较大，但总体预测效果较为理想。