珠江口盆地阳江东凹古近系构造特征与勘探潜力

阳江东凹是近年来珠江口盆地(东部)的热点探区,过去四十余年受限于钻井数量与地震资料品质和覆盖范围,缺少对古近系的研究.随着勘探程度的提高,走向深层古近系是珠江口盆地油气勘探的必然趋势.本文在覆盖全区的高品质三维地震资料基础上,结合新近钻井和测井资料,系统解剖阳江东凹的构造特征及其对沉积充填的控制,并探讨古近系的勘探潜力...     

东江流域雨水集中期气候特征及2006年降水成因分析

利用湘东南东江流域1959～2006年共48年的历史资料,采用统计分析方法,对东江流域历年雨水集中期的气候规律以及2006年雨水集中期的特征及成因进行了分析。分析结果表明:东江流域历年的雨水集中期多出现在6月和8月;东江流域雨水集中期的出现,受台风的影响较大。2006年由于04号台风"碧利斯"的影响导致了本年的雨水集中期出现在7月中旬,其特征是降水强度强、强降水范围广、过程降雨量大,而大尺度引导气流、南海季风对"碧利斯"的西行路径及降水强度影响较大。     

Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area,China

China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China’s hotspot regions, the Guangdong-Hong KongMacao Greater Bay Area(GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to2017 were used to derive forest, and landscape metrics and geographic information system(GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in1987–2017;meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60%(1034.42 km2) was converted to urban land;2) the percentages of forest loss to urban land in Dongguan(19.14%), Guangzhou(18.35%) and Shenzhen(15.81%) were higher than those in other cities;3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from2007 to 2017);4) the landscape responses to forest changes varied with the scale;and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong.Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation.     

贵州强降雨天气过程决策服务模式

【目的】为深入总结贵州气象防灾减灾工作中面向党政领导和相关部门的灾害性天气决策气象服务模式。【方法】在服务需求分析的基础上,结合典型案例,对近年来强降水等灾害性天气过程中的预报服务机制进行总结凝炼。【结果】提出灾害性天气“过程前、过程中、过程后”关键时间点的跟进式气象服务“4+3”模式和强降雨临灾服务的“24-6-2-2”递进式预报服务模式。【结论】 经近年来实践检验,相关服务模式能有效应对强降水等灾害性天气过程,有力支撑党政领导和部门决策应对灾害性天气,有效助力防灾减灾救灾工作。     

贵州省习水县暴雨特征及成因分析

【目的】在极端天气频发的气候背景下,有必要进一步分析习水县暴雨天气时空分布特征。【方法】利用1959—2022年贵州省习水国家基本气象站逐日降水资料、2010—2022年24个乡镇区域站日降水资料,运用统计学及空间插值等方法,对习水县的暴雨时空分布特征及成因进行分析。【结果】习水县暴雨多发生在习水河谷和赤水河谷的迎风坡及东部喇叭口地形区域,空间分布特征为北多南少;年区域性暴雨日数呈增长趋势;区域性暴雨月变化呈“单峰”型分布特征,主要出现在5—9月,占比94%;区域性大暴雨日数月分布呈“双峰”型分布,峰值在6月、8月。习水县暴雨具有明显日变化特征,夜雨特征明显,大暴雨夜雨占比81.1%;区域性暴雨天气过程主要降水时段集中在19时—次日06时,占比76.9%。习水从春季至秋季都有暴雨出现,暴雨日数频次大值区自西向东移动,夏季暴雨出现最多,占比69%。将造成区域性暴雨天气的影响系统分为低涡切变型、冷锋低槽型、梅雨锋型、台风外围型等4种类型。低涡切变型产生暴雨最多,占比77.3%。【结论】习水县暴雨空间分布呈北多南少,区域性暴雨主要出现在5—9月,夜雨特征明显,该研究成果可为更好地开展习水县暴雨灾害性天气预报及气象服务工作提供参考。     

WIN 2000的入侵检测系统实例分析

入侵检测系统能发觉入侵行为并且采取相应的措施。它通过对计算机网络或计算机系统中的若干关键点收集信息并对其进行分析,从中发现网络或系统中是否有违反安全策略的行为和被攻击的迹象。该文通过对WIN2000下的入侵检测的一个实例进行分析,总结了几点应对入侵的具体措施,旨在为网络管理员提供借鉴。     

藏南拉康温泉地质特征及雄曲河谷两岸地热分布不均成因分析

西藏山南地区洛扎县雄曲河拉康段在600 m距离内出露温泉4处,仅1处位于河谷右岸;平硐勘查显示两岸岩性、产状、构造一致,地热异常却仅在左岸平硐内部显著,右岸平硐地热异常不明显.本次研究以此异常为出发点,通过片麻状花岗岩不同切面导热实验、片麻状花岗岩与板岩相同切面导热实验,温泉水δ2H,δ18O同位素测试分析等方法,探究...     

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.     

CINRAD RPG累积降水算法在文山州的应用

把降水实况和相应时段内C INRAD RPG 1h累积降水量进行对比分析,检验C INRAD RPG 1h累积降水量在文山地区的可靠性。经过对比分析可知,C INRAD RPG1h累积降水量虽然存在严重偏差,不能根据其对降水作定量估计,但它对区域降水仍然具有较好的指示性,可以根据相关数值估计降水量级。     

南海中沙天然气水合物资源远景区海底沉积物的物理力学性质研究

根据南海中沙天然气水合物远景区沉积物样品的分析资料,从物理力学特征各方面对本区海底沉积物进行了综合工程地质特征研究。结果表明,本区海底沉积物类型全部为淤泥,工程地质性质相近,以高含水率、高孔隙比、低密度及高塑性为主要特征,抗剪强度很小,压缩系数均大于0.5。土体沉积环境为水动力强度较弱的深海半深海环境。