Water Cycle Analysis of Social and Economic System in Tarim River Basin

Water cycle includes natural water circulation and social economic system water cycle. The concept of virtual water provides a new method and means for studying social water circulation. This paper is based on the theory of water circulation in social and economic system, using input-output analysis method quantitatively describes the Tarim River basin of social water cycle paths and analysis of water resources management in Tarim River basin sustainable development process of the key issues. The results show that the main sectors of virtual water export in the Tarim River Basin are agriculture, petroleum, natural gas and food industry. Agricultural water accounts for more than 98% of total water consumption, most of which is transferred to the food and textile industries, and the food industry export water from the agricultural sector. Shandong Province is the largest virtual water transport area in the Tarim River Basin. The main sector of virtual water input in the Tarim River Basin is the metallurgical industry. Finally, in view of the problems arising from the inter-industrial and inter-regional social water circulation in the Tarim River basin, the paper puts forward the ways and strategies of regulating agricultural and industrial water use in the Tarim River Basin.     

江西兴国均村-高兴地区氟水文地球化学特征研究

氟广泛分布于地下水且与人体健康相关,世界上许多国家和地区均存在高氟水。本文以江西省均村-高兴地区为例,结合区域水文地质调查成果开展地下水中氟水文地球化学特征研究,探讨研究区地下水中F-的分布特征与来源。对研究区4个地下水系统中的442个地下水样品的F-、Ca²⁺、HCO_3^-浓度及pH值、TDS等进行分析,研究认为各地下水系统地下水中的F-浓度与Ca²⁺浓度、HCO_3^-浓度、pH值、TDS正相关,含氟矿物的溶解是地下水中氟的主要来源,较强烈的地下水交替条件及弱酸性的地下水特征是导致地下水中氟浓度低的重要原因。     

IPCC AR6报告解读：气候系统对太阳辐射干预响应

IPCC第六次评估报告（AR6）第一工作组报告评估了太阳辐射干预（Solar radiation modification,SRM）对气候系统和碳循环的影响。在大幅度减排基础上,太阳辐射干预有潜力作为应对气候变化的备用措施。目前,对于太阳辐射干预气候影响的评估都是基于模式模拟结果。评估主要结论如下：太阳辐射干预可以在全球和区域尺度上抵消一部分温室气体增加造成的气候变化（高信度);但是太阳辐射干预无法在全球和区域尺度上完全抵消温室气体增加引起的气候变化（几乎确定);有可能通过适当的太阳辐射干预设计,同时实现多个温度变化减缓目标（中等信度);在高强度温室气体排放情景下,如果太阳辐射干预实施后突然终止,并且这种终止长时间持续,将会造成快速的气候变化（高信度);如果在减排和CO₂移除的情况下,太阳辐射干预的实施强度逐渐减小至零,将显著降低太阳辐射干预突然终止产生的快速气候变化风险（中等信度);太阳辐射干预会通过降温作用,促进陆地和海洋对大气CO₂的吸收（中等信度),但是太阳辐射干预无法缓解海洋酸化（高信度);太阳辐射干预对其他生物化学循环影响的不确定性大。由于对云-气溶胶-辐射过程的相互作用和微物理过程认知有限,目前对平流层气溶胶注入、海洋低云亮化、高层卷云变薄等太阳辐射干预方法的冷却潜力和气候效应的认知还有很大的不确定性。     

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

浅水三角洲沉积体系与储层岩石学特征

浅水三角洲已经成为当前沉积学研究和油气勘探的重点领域,浅水三角洲常规和非常规砂岩储层中发现了丰富的油气资源。鄂尔多斯盆地中—古生界发育大型浅水三角洲沉积,结合岩芯、测井、分析化验等资料,对盆地西部地区山1—盒8段浅水三角洲的母岩特征、沉积充填、砂体展布与储层岩石学特征进行研究,为研究区常规砂岩储层和致密砂岩油气勘探提供地质依据。分析表明,研究区南部和北部砂岩重矿物组合相似,以锆石和白钛矿为主。综合La/Yb-REE与Dickinson三角图解、稀土元素配分模式和碎屑锆石定年分析认为,北部物源主要来自盆地西北部阿拉善古陆太古界和元古界花岗岩、片麻岩、石英砂岩,向南影响到陇东地区北部;南部物源主要来自盆地南部北秦岭地区太古界、元古界花岗岩、片麻岩和片岩,向北影响陇东地区中南部。山1段发育曲流河三角洲,盒8段发育辫状河三角洲,孤立型与垂向叠置型水下分支河道砂体是主要的砂体类型。盒8段沉积时期,古湖泊可能萎缩;南北物源形成的三角洲在研究区中部环县东南一带交汇混合。砂岩类型主要为岩屑质石英砂岩、石英砂岩和岩屑砂岩,结构成熟度中等—较差。砂岩成岩改造强烈,水—岩反应复杂,压实作用是储层致密化的主因,多期胶结作用使砂岩的孔喉结构变得十分复杂。孔隙类型以微米—纳米级的岩屑溶蚀孔、剩余粒间孔和高岭石晶间孔为主,整体上属于非常规致密砂岩储层。砂体分布与“甜点”预测是研究区致密油气勘探的关键。     

辽河西部凹陷曙北地区沙四段薄砂层成因类型及分布规律

为了明确辽河西部凹陷曙北地区沙河街组四段薄砂层成因类型及分布规律,从岩心、测井响应和地震反射特征等方面总结了各类成因薄砂层的识别标志,并预测了各砂层组的砂体展布,探讨了砂体发育的控制因素,总结了沉积模式.研究结果表明,曙北地区沙四段为扇三角洲-湖泊的沉积体系,薄砂层发育水下分流河道、河口坝、低隆滩坝、沿岸浅滩4种成因类型,其中以水下分流河道和低隆滩坝为主.古地貌、古物源和古水深控制了各类砂体的展布.以曙光和兴隆台古潜山一线为界,南部为扇三角洲体系沉积区,主要发育前缘水下分流河道和河口坝;北部（包括低隆区）为无明显水流注入的半封闭湖湾区,主要发育低隆滩坝砂体和灰/云坪,在西侧沿岸局部地区还发育沿岸浅滩.储量区外大面积发育的低隆滩坝砂体,是下一步碎屑岩增储上产的潜在接替区域.     

渤海海域埕岛低凸起东部南区新生代断裂系统及油气分布的控制作用

埕岛低凸起东部南区新生代受控于伸展与走滑作用,断裂构造复杂,传统认为中深层北东向与近东西向断层属于同期同沉积断层。针对这一观点及引起的问题,利用钻井和地震资料,运用构造地质理论解析断裂系统。研究区主要发育正断层、走滑正断层两种类型,断开层位有基底—东营组、平原组—东营组、平原组—基底三种情况,现今断裂以东营组与馆陶组之间的区域不整合面为时限划分为两期断裂系统。早期断裂主要切开基底—东下段,属于同沉积断层;晚期断裂主要切开平原组—东营组,可断达基底,其发育受早期断裂制约。北东向与近东西向断层分别属于早晚两期断裂系统,对油气分布各起关键性控制作用:先期基底升降引起的伸展作用形成北东向断层,控制洼槽地貌与深水重力流沉积环境,发育了连片的层状砂质碎屑流;后期郯庐断裂右行走滑派生了近东西向雁列断层,断层面既充当储层上倾方向的遮挡条件,又在东西向挤压时封闭性变差而变成油气垂向运移通道,断层及断层作用控制了圈闭分布与油气聚集的有序性,自东向西,圈闭及油水界面依次升高且充满度变小,呈全充满、欠充满、半充满等状态。断裂系统研究将地质体置于一定的构造应力场中,分析断层组合的空间排列和交切关系以及断层的力学机制和位移特征等,探究时空演化对油气分布的控制作用。断裂系统研究方法在构造作用叠合区具有适宜性,对该区及类似地区的勘探开发具有现实意义。     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.