四川省盐源县盐泉的特征与形成

研究天然盐泉的形成有助于揭示陆地水文循环过程中的物质迁移。采用水文地球化学的方法,分析四川省盐源县的9个泉水和卤水水样的水化学特征和同位素特征,探讨盐泉的溶质来源,总结盐泉的成因模式。水样可以分为TDS为311.69 g/L的Cl-Na型卤水、TDS为55.77~89.43 g/L的Cl-Na型盐泉、TDS为1.17 g/L的Cl-Na型微咸泉和TDS为0.26~0.56 g/L的以HCO₃-Ca、HCO₃·SO₄-Ca·Mg型为主的淡水泉。泉水和卤水的氢氧同位素显示其来源于大气降水;水样的特征系数显示盐泉和卤水都属于溶滤型,且指示研究区基本不具有找钾前景。泉水的盐分主要来源于石盐、方解石、石膏和白云石等矿物的溶滤。盐泉的形成模式可以概括为:在山区获得大气降水入渗补给后,地下水经历较浅和较深的地下径流并且溶滤含盐地层或者盐矿,使其矿化度升高,在地形较低处汇集出露地表成泉。     

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。     

西昌盆地上三叠统白果湾组富有机质泥页岩沉积岩相古地理与孔隙特征

海陆过渡相富有机质泥页岩是页岩气勘查开发的重要领域。本文以西昌盆地上三叠统白果湾组富有机质泥页岩为研究对象，对研究区内富有机质泥页岩的沉积岩相古地理特征、微观孔隙类型、孔隙结构特征进行研究。白果湾组富有机质泥页岩段沉积相主要为湖泊相、三角洲相、河流相。发育不同类型的微孔隙，孔隙主要以小孔为主，微孔次之，平均孔径分布在5.56~56.89nm之间，比表面积平均为9.44m²/g，总孔体积平均为0.0187cm³/g。页岩气主要形成于滨浅湖亚相及半深湖亚相中，并主要吸附于富有机质泥页岩的小孔、微孔内；西昌盆地白果湾组富有机质泥页岩储集空间较好，具有良好的勘探潜力。     

Walking Access Distance of Metro Passengers and Relationship with Demographic Characteristics: A Case Study of Nanjing Metro

In the metropolises of China, the metro plays an increasingly important role in commuting because of its efficiency, affordability, and cleanliness. This paper attempts to explore the relationship between walking access distance to metro stations and the demographic characteristics of passengers, such as age, monthly income, travel frequency, gender, and travel purpose, as well as the influence of the urban context. Nanjing Metro Line 2 is selected as the case study. By using different methods such as a questionnaire survey, spatial decay function, analysis of covariance (ANOVA), network analysis of routes, and K-means cluster analysis, it is suggested that demographic characteristics have a significant impact on the pedestrian walking distance, with the exception of gender. Furthermore, the paper finds a spatial decay effect in walking access distance, the decay rate of which, however, varies across stations. Terminal stations have a larger pedestrian catchment area than in regular and exchange stations. Moreover, the passengers of Nanjing Metro Line 2 can be classified into six groups according to their demographic characteristics, among which education and occupation are vital indicators in determining their willingness to walk to the stations. Middle-class passengers have a higher dependence on the metro and tend to walk longer than other groups do. This study provides an important reference for planners and transport sectors to optimize land-use and transport infrastructures.     

Regional Characteristics and Causes of Haze Events in Northeast China

Northeast China experiences severe atmospheric pollution, with an increasing occurrence of heavy haze episodes. However, the underlying forces driving haze formation during different seasons are poorly understood. In this study, we explored the spatio-temporal characteristics and causes of haze events in Northeast China by combining a range of data sources(i.e., ground monitoring, satellite-based products, and meteorological products). It was found that the ‘Shenyang-Changchun-Harbin(SCH)'city belt was the most polluted area in the region on an annual scale. The spatial distribution of air quality index(AQI) values had a clear seasonality, with the worst pollution occurring in winter, an approximately oval-shaped polluted area around western Jilin Province in spring, and the best air quality occurring in summer and most of the autumn. The three periods that typically experienced intense haze events were Period I from mid-October to mid-November(i.e., late autumn and early winter), Period II from late-December to February(i.e., the coldest time in winter), and Period III from April to mid-May(i.e., spring). During Period I, strong PM_(2.5) emissions from seasonal crop residue burning and coal burning for winter heating were the dominant reasons for the occurrence of extreme haze events(AQI 300). Period II had frequent heavy haze events(200 AQI 300) in the coldest months of January and February, which were due to high PM_(2.5) emissions from coal burning and vehicle fuel consumption, a lower atmospheric boundary layer, and stagnant atmospheric conditions. Haze events in Period III, with high PM_(10) concentrations, were primarily caused by the regional transportation of windblown dust from degraded grassland in central Inner Mongolia and bare soil in western Jilin Province. Local agricultural tilling could also release PM_(10) and enhance the levels of windblown dust from tilled soil. Better control of coal burning, fuel consumption, and crop residue burning in winter and autumn is urgently needed to address the haze problem in Northeast China.     

On the electron density diagnostics of silicon <Emphasis Type="SmallCaps">viii</Emphasis> ion in solar transition region

The conditions for accurate electron density diagnostics in the solar transition region are discussed, and result shows that lines from Si?viii can provide an excellent tool for electron density diagnostics of the emitting plasma. For the Si?viii 1440.50 Å and 1445.75 Å lines, the principle of the electron density diagnostics is discussed for any intensity ratio. By the observed intensity ratio, the diagnostic results of the electron density for the quiet sun and the active region are calculated, and results indicate that in the quiet sun, the averaged electron density is \(\log (N_{e}) = 8.63\); while in the active region, the averaged density gets the maximum \(\log (N_{e}) = 8.86\) in the active region (B), and gets the minimum \(\log (N_{e}) = 8.38\) in the active region (E), where the electron density is in the unit of cm^?3. Finally, the relationship of intensity ratio and electron density is discussed, in the case of lower and higher electron density limits. This discussion is significant in the electron density diagnostics, which will be important for study on coronal heating and acceleration of solar wind.     

Environmental hazard analysis of a gypsum karst depression area with geophysical methods: a case study in Sivas (Turkey)

Because the mixture of seawater and freshwater in the Gyeongin-Ara Waterway in South Korea can lead to the intrusion of saline water into surrounding aquifers, systematic management through the establishment of a groundwater protection area is required. The analytic hierarchy process (AHP) model is used to delineate this protection area based on two primary factors and five secondary factors related to saline water intrusion. The study area is divided into 987 gridded cells with a unit size of 100 × 100 m, and the final evaluation score for each cell is calculated using the AHP model. Consequently, several artificial neural network models based on a multilayer perceptron are developed using the AHP’s secondary criteria and the evaluation score. Comparing the evaluation scores of ANN and AHP, more than 180 samples are required in the ANN model to insure high R2 between the original and estimated values. The ANN model is more consistent than the AHP model when determining groundwater protection area, because it can be re-constructed due to the changes in some secondary criteria and also changed due to a standardization process. The final evaluation score by the ANN model based on 300 samples, with the highest R2, is calculated and the regions with a score higher than 2.0 are selected as the groundwater protection area, accounting for 15% of the total cells. This area is similar to the range within approximately 200 m of the GA Waterway and also includes some changing sites in hydrogeochemistry and electric conductivity, which is produced by saline water intrusion. If the land-use type, groundwater levels, and some other criteria change at any cell, the ANN model can be re-executed to verify whether the cell belongs to a groundwater protection area. Considering that salinity of groundwater near the waterway can be affected by various factors including well depth, pumping conditions, and groundwater levels, the ANN model, which is a non-linear model, can be more effective for prediction than the AHP model.     

自然和自然贡献情景模型研究综述

本文回顾了自然和自然贡献情景模型发展的背景、历史和内容,概括总结了自然和自然贡献情景模型的发展进程以及联合国生物多样性与生态系统服务政府间科学—政策平台(IPBES)情景模型的概念框架,讨论了自然和自然贡献情景模型存在的问题和发展方向。为了在全球层面解决现有综合集成模型存在的问题,根据地球表层建模基本定理和生态环境曲面建模基本定理,提出了具有中国原创特点的自然与自然贡献情景模型概念框架。     

广西土壤有机质空间变异特征及其影响因素研究

基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明：广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。