云南地区4级地震频度异常特征与强震关系研究

对云南地区18次MS≥6强震事件前中、小地震活动过程进行了分析,发现在这些地震发生前1—3年近场区2°×2°范围内4级地震频度基本上出现了显著增强现象,可以用4级地震年累计频度进行定量描述。通过全时空的扫描,确定年累计频度N≥4为异常阈值,该指标通过了置信度97.5%的R值内符检验。并用调整单元对强震附近4级地震活动增强现象给予了物理解释。     

Assessing the effects of land cover and future climate conditions on the provision of hydrological services in a medium‐sized watershed of Portugal

The separated and combined effects of land‐cover scenarios and future climate on the provision of hydrological services were evaluated in Vez watershed, northern Portugal. Soil and Water Assessment Tool was calibrated against daily discharge, sediments and nitrates, with good agreements between model predictions and field observations. Four hypothetical land‐cover scenarios were applied under current climate conditions (eucalyptus/pine, oak, agriculture/vine and low vegetation). A statistical downscaling of four General Circulation Models, bias‐corrected with ground observations, was carried out for 2021–2040 and 2041–2060, using representative concentration pathway 4.5 scenario. Also, the combined effects of future climate conditions were evaluated under eucalyptus/pine and agriculture/vine scenario. Results for land cover revealed that eucalyptus/pine scenario reduced by 7% the annual water quantity and up to 17% in the summer period. Although climate change has only a modest effect on the reduction of the total annual discharge (?7%), the effect on the water levels during summer was more pronounced, between ?15% and ?38%. This study shows that climate change can affect the provision of hydrological services by reducing dry season flows and by increasing flood risks during the wet months. Regarding the combined effects, future climate may reduce the low flows, which can be aggravated with eucalyptus/pine scenario. In turn, peak flows and soil erosion can be offset. Future climate may increase soil erosion and nitrate concentration, which can be aggravated with agriculture scenario. Results moreover emphasize the need to consider both climate and land‐cover impacts in adaptation and land management options at the watershed scale. Copyright © 2015 John Wiley & Sons, Ltd.     

Phase transition of the Pacific decadal oscillation and decadal variation of the East Asian summer monsoon in the 20th century

This paper focuses on the relationship between the phase transition of the Pacific decadal oscillation (PDO) and decadal variation of the East Asian summer monsoon (EASM) in the twentieth century. The first transition occurred in the 1940s, with an enhanced SST in the North Pacific and reduced SST in the tropical eastern Pacific and South Indian Ocean. In agreement with these SST changes, a higher SLP was found in most parts of the Pacific, while a lower SLP was found in the North Pacific and most parts of the Indian Ocean. In this case, the EASM was largely enhanced with a southerly anomaly in the lower troposphere along the east coast of China. Correspondingly, there was less rainfall in the Yangtze River valley and more rainfall in northern and southern China. An opposite change was found when the PDO reversed its phase in the late 1970s. In the tropical Indian Ocean and western Pacific, however, the SST was enhanced in both the 1940s and 1970s. As a result, the western Pacific subtropical high (WPSH) tended to extend westward with a larger magnitude in the 1970s. The major features were reasonably reproduced by an atmospheric general circulation model (IAP AGCM4.0) prescribed with observed SST and sea ice. On the other hand, the westward extension of the WPSH was exaggerated in the 1970s, while it was underestimated in the 1940s. Besides, the spatial pattern of the simulated summer rainfall in eastern China tended to shift southward compared with the observation.     

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

1958-2017年太湖蒸发量年际变化趋势及主控因子

湖泊蒸发对气候变化非常敏感,是水文循环响应气候变化的指示因子,因此研究湖泊蒸发的控制因素,对于理解区域水文循环有重要意义.本文利用太湖中尺度涡度通量网避风港站观测数据校正JRA-55再分析资料,驱动CLM4.0-LISSS模型,并利用2012-2017年涡度相关通量数据和湖表面温度数据检验模型模拟蒸发结果,验证了该模型在太湖的适用性;估算了1958-2017年间太湖的湖面蒸发量,并利用Manner-Kendall趋势检验分析了湖面蒸发的变化趋势,寻找太湖实际蒸发的年际变化的主控因子.结果如下:校正后的JRA-55再分析资料模拟的太湖蒸发与观测值之间存在季节偏差,但是季节偏差在年尺度上相互抵消,再分析资料可用于年际尺度太湖蒸发变化的模拟;1958-2017年间太湖蒸发量以1977年为界,先下降(-3.6 mm/a),后增加(2.3 mm/a);多元逐步回归结果表明,向下的短波辐射是太湖1958-2017年间太湖蒸发变化的主控因子,向下的长波辐射、气温、比湿也对湖泊蒸发年际变化有一定影响,但是风速对蒸发量的年际变化影响不大.     

2017年南丹Ms4.0地震前后重力变化

利用广西及邻区2014~2017年流动重力观测资料,系统分析区域重力场变化及其与2017-07-15广西南丹MS4.0地震的关系,并结合GPS观测数据与地震地质调查成果,探讨区域重力场变化的时空分布特征及机理。结果表明：1）南丹M_S4.0地震前后,震区附近重力异常变化与主干断裂关系密切,反映沿控震断裂在2014~2017年间发生了引起地表重力变化效应的地壳变形和构造活动;2）差分重力图像表明,南丹M_S4.0地震前重力变化为“局部重力异常→四象限重力异常→重力反向变化发震”的过程;3）重力变化与GPS 观测反映的水平运动表明,南丹M_S4.0地震位于重力四象限分布中心部位及面压缩峰值附近,证明重力场和形变场动态变化对中强地震地点预测具有指示意义;4）天峨-南丹-环江一带是重力变化最剧烈地区,亦是水平形变面压缩过渡带,同时位于莫霍面等深线强烈变化地段、M_L3.0地震围空区、沿主断裂存在的低b值异常区。结合地震活动图像、定点前兆观测异常综合分析认为,该地区仍存在发生中强地震的可能。     

时距平面剩余时差选择加权叠加压制多次波方法及效果

一个CDP道集经动校正后,多次波仍存在剩余时差δt,它随炮检距呈抛物线变化。由δt的变化即可求出多次波剩余波数△K的分布规律。据此,可设计一个理想的叠加剩余波数响应,用于动校正后的CDP道集的加权叠加。在t～x平面选择δt,即可改变叠加剩余波数响应,从而改变各道的加权系数,实现最佳压制多次波的效果。     

地质地球化学图解的计算机绘图系统

根据目前国内外发表的常用地质地球化学图解特征,研制了一套容纳１５０多幅常用地质地球化学图解的绘图系统。系统界面友好,操作方面,适用性极强,具有可扩充性。     

基于C4.5决策树算法的道路结冰预报模型构建及应用

道路结冰是气象上规定的主要灾害性天气之一,准确认识道路结冰发生规律并科学有效地预报是防灾减灾的关键问题。以影响道路结冰的日积雪深度、日最低气温、日降水量等气象要素为主要因子,将是否结冰抽象成二元分类问题,借助数据挖掘中C4.5决策树算法进行分类分析,得到便于预报员使用的预报道路结冰规则集。在实验部分,选取2004—2013年连云港和嘉定为例,用前8 a的连云港(嘉定)地区道路结冰数据样本进行分类规则的学习,从而得到适合连云港(嘉定)地区的4(3)条预报道路结冰规则集,然后用剩下2 a的数据进行检验,准确率高达96.82%(94.87%)。实验表明采用C4.5决策树算法构建的道路结冰预报模型不仅预报准确率高、易解释、方便预报员直接使用,而且预报规则与道路结冰现象的天气过程及理论一致。