滇东断陷盆地南洞岩溶地下水系统地下河水文动态特征与资源量评价

本文对滇东断陷盆地南洞岩溶地下水系统各地下河的水文动态特征进行了分析,推断了南洞岩溶地下水系统的结构特征.根据岩性构造、地下河发育以及补径排关系,将其划分为四个子系统.分别采用降雨入渗系数法和径流模数法对南洞岩溶地下水系统的天然资源量进行计算,计算结果分别为35610.7万m3/a和33460.2万m3/a.用枯季径流模数法对南洞岩溶地下水系统的可采资源量进行了计算,计算结果为23407.3万m3/a,其可开采资源量巨大.南洞地下河在没有天然补给量的情况下,120天消耗的调蓄量为4503.3万m3,南洞地下河日允许开采资源量为49.4万m3/d.二号暗河建库蓄水条件下库区上游的日允许开采量为75.9万m3/d,蓄水库容来源于工程设计,资源保证程度高.本次研究可为南洞岩溶地下水资源的开发利用和调配提供科学依据.     

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.     

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.     

Geochronological and geochemical evidence for a Late Ordovician to Silurian arc-back-arc system in the northern Great Xing'an Range,NE China

The early Paleozoic tectonic evolution of the Xing'an-Mongolian Orogenic Belt is dominated by two oceanic basins on the northwestern and southeastern sides of the Xing'an Block,i.e.,the Xinlin-Xiguitu Ocean and the Nenjiang Ocean.However,the early development of the Nenjiang Ocean remains unclear.Here,we present zircon U-Pb geochronology and whole-rock elemental and Sr-Nd isotopic data on the gabbros in the Xinglong area together with andesitic tuffs and basalts in the Duobaoshan area.LA-ICP-MS zircon U-Pb dating of gabbros and andesitic tuffs yielded crystallization ages of 443-436 Ma and 452-451 Ma,respectively.The Early Silurian Xinglong gabbros show calc-alkaline and E-MORB affinities but they are enriched in LILEs,and depleted in HFSEs,with relatively low U/Th ratios of 0.18-0.36 andεNd(t)values of-1.6 to+0.5.These geochemical features suggest that the gabbros might originate from a mantle wedge modified by pelagic sediment-derived melts,consistent with a back-arc basin setting.By contrast,the andesitic tuffs are characterized by high MgO(>5 wt.%),Cr(138-200 ppm),and Ni(65-110 ppm)contents,and can be termed as high-Mg andesites.Their low Sr/Y ratios of 15.98-17.15 and U/Th values of 0.24-0.25 and moderate(La/Sm)_n values of 3.07-3.26 are similar to those from the Setouchi Volcanic Belt(SW Japan),and are thought to be derived from partial melting of subducted sediments,and subsequent melt-mantle interaction.The Duobaoshan basalts have high Nb(8.44-10.30 ppm)and TiO2 contents(1.17-1.60 wt.%),typical of Nb-enriched basalts.They are slightly younger than regional adakitic rocks and have positiveεNd(t)values of+5.2 to+5.7 and are interpreted to be generated by partial melting of a depleted mantle source metasomatized by earlier adakitic melts.Synthesized with coeval arc-related igneous rocks from the southeastern Xing'an Block,we propose that the Duobaoshan high-Mg andesitic tuffs and Nbenriched basalts are parts of the Late Ordovician and Silurian Sonid Zuoqi-Duobaoshan arc belt,and they were formed by the northwestern subduction of the Nenjiang Ocean.Such a subduction beneath the integrated Xing'an-Erguna Block also gave rise to the East Ujimqin-Xinglong igneous belt in a continental back-arc basin setting.Our new data support an early Paleozoic arc-back-arc model in the northern Great Xing'an Range.     

全民所有自然资源资产管理考核评价机制与方法研究

本文采用对比分析与归纳分析法,在明确全民所有自然资源资产管理考核评价机制定位的基础上,充分借鉴和参考现有相关考核评价制度的设计思路,围绕“考核谁、谁来考、怎么考、考什么、结果怎么定、结果怎么用”等关键问题,从考核评价对象和实施主体、考核评价方式和实施、考核评价结果应用、考核评价内容和指标体系构建、考核评价结果评定方法等方面,提出构建全民所有自然资源资产管理考核评价机制和方法的思路,为推进生态文明建设和自然资源资产产权制度改革提供支撑。     

应用分布式存储技术优化省级CIMISS数据服务能力

随着气象数据量的不断增长,进一步提升CIMISS数据管理和服务能力的需求变得日益迫切。为解决存储系统动态扩展能力不足、并行计算与吞吐效率低下等限制CIMISS继续发展的问题,采用分布式文件系统和NAS技术替代GPFS建设共享文件系统,实现非结构化气象数据的存储功能;采用分布式数据库替代Oracle RAC建设关系数据库管理系统,实现结构化气象数据的存储功能和非结构化气象数据的索引功能。实践证明,该方案能够有效地改善CIMISS的数据存储能力、并发响应能力,适应未来气象业务对数据存储和应用的需求。     

BCC模式及其开展的CMIP6试验介绍

世界气候研究计划（WCRP）正在组织实施第六次国际耦合模式比较计划（CMIP6),国家气候中心作为参与单位之一,通过近几年的模式研发,推出3个最新模式版本参与该计划,包括含有气溶胶化学模块的地球系统模式BCC-ESM1.0、中等分辨率气候模式BCC-CSM2-MR和高分辨率气候模式BCC-CSM2-HR。除了CMIP6中的气候诊断、评估和描述试验（DECK）和历史气候模拟试验（Historical),这3个模式共将参与CMIP6中的10个模式比较子计划。文中主要介绍这3个模式的基本情况以及所开展的CMIP试验,并对BCC-CSM2-MR模式的Historical试验结果进行简要评估,为试验数据使用者提供参考。     

碳市场顶层设计路线图

中国正面临着低碳减排和保持经济增速的双重挑战。为利用碳排放权交易机制以最低的社会成本实现减排目标,我国自2013年起开始建设碳排放权交易试点,并于2017年12月起宣布正式启动全国碳市场。然而碳市场的顶层设计不可一蹴而就,需要在我国宏观经济改革的大背景下分阶段逐步推进。短期（2020年前）碳市场建设重在强化产权制度建设,完善市场交易基础。中期（2021—2030年）碳市场建设要形成活跃的市场氛围,充分降低我国的温室气体达峰成本。长期（2031—2050年）碳市场建设要形成稳定上升的碳价趋势,为我国的低碳转型提供长期动力。     

河南省人工防雹作业指挥系统研发及应用

利用河南省历史气象资料,结合先进的防雹理论与技术,系统分析和总结了河南省冰雹过程的天气尺度与中尺度概念模型,并根据三维冰雹云数值模式及雷达探测、闪电定位、卫星、自动站数据,研发出河南省人工防雹作业指挥系统。该系统包括天气形势分析子系统和作业决策指挥子系统。天气形势分析子系统可根据大尺度形势背景、中尺度系统特征及三维冰雹云数值模式和卫星、闪电、自动站资料,对可能降雹区进行预测。作业决策指挥子系统通过对雷达数据产品的二次开发,完成雷达资料处理、产品生成及风暴自动识别、分类、预警,并根据参数的变化和雹云的移动方向,对下游作业区进行预警及输出作业方案。整个系统基于VS2005开发平台,使用c++开发语言,利用图层分层管理将地理信息、雷达实时观测资料、雷达二次产品、高空资料、火箭和高炮作业点等信息分层显示。系统自动化程度高,操作简便,为河南省冰雹天气预报预警提供了可参考的技术指标体系。     

广西气象数据中心机房供电系统设计与保障

针对供配电系统容易发生的安全隐患,优化设计配电系统结构、采用一体化运维监控平台和采用高质量、高可靠性的设备,消除单点故障瓶颈,确保在停电、设备故障、维修维护等各种情况下提供不中断或快速恢复供电,避免停电对业务正常运行造成影响,确保机房供电安全。