新疆地震序列参数初探

整理和分析了1990年以来发生在新疆地区的30次ML≥5.4级地震序列(伽师强震群除外),得出了新疆地震序列类型划分的一般规则并将这些地震序列分为孤立型、主震—余震型和双震或多震型3种。这些地震序列主要分布于新疆4个地震构造带,以主余型为主,每个地震带内地震序列类型有所不同。通过对地震序列参数b、h、k和p的计算和分析,认为k值对该区地震序列类型的判断有一定参考价值。     

震后趋势判断中尾波振幅衰减特征k值的研究

利用唐山、浑源、岫岩和浙江省的鄞县、珊溪水库地震等不同地震类型的数字地震波资料，经过筛选和整理，对每一个地震序列求出几个台站的尾波振幅衰减特征，k值随时间序列的变化特征。结果表明，虽然k值的变化趋势比较复杂，但还是发现不同震型的k值的变化特征有所不同。从趋势上来说，在主震前后，主震一余震型地震的k值显示先低后高的趋势，震群型地震显示先高后低的趋势。我们可以根据这个特征来判断所发生地震的震型，用于震后地震趋势快速判断。     

新疆中强地震序列类型及其早期判断

地震发生后,首先是尽早地判断震型,以判断未来大震发生的可能性及地震活动的发展趋势。本文对1970—1987年新疆大部分中强地震的序列进行了震型判断和震型的早期判断,以求找出新疆地震序列类型的判断指标,为快速判定震型,预报震后序列发展趋势提供依据,并通过震型判断的分析研究找出新疆地震序列类型的基本特征。     

伽师-巴楚强震群序列趋势的早期判断

使用喀什地震台记录的伽师—巴楚震群序列目录,采用Em／∑E、△M方法对序列早期震型进行判定。在震型判定的基础上,采用h、b、u、F值等参数对震后序列趋势进行分析。得到以下主要结论：(1)伽师一巴楚强震群序列特征复杂,在震群活动的不同阶段,它们既有共性也有个性;在震群活动的各个阶段,不同强度的地震序列特征在震后早期便可显现;(2)首发强震后,区域历史强震类型将有助于定性判断震后趋势,震区余震地震波形可能是早期判断地震类型的关键环节;(3)使用Em／∑E、△M方法并结合主震后第1天内的小震频次能够对震型作出较为准确的判定。在震型判定的基础上再使用h、b、u、F值参数对各级序列进行逐级分层的趋势分析;(3)使用6级地震序列的h值和含主震计算的6值对未来强震震级进行估算,采用5级地震序列的h值和不含主震计算的6值对未来强余震震级进行推算;(5)跟踪子序列的震型、预测震级及参数异常的动态变化,判断后续序列中是否会发生强(余)震,但分析时必须注意各级序列之间的隶属关系和活动背景;(6)在强震成组活动后,若h值出现高→低→高的变化过程,则预示着震群活动可能进入后期。震群中最高震级地震发生后的h值大于1也是序列发展进入晚期的重要标志。     

我国九次强震序列分类

十年来,我国地震工作者根据前震、主震和余震的震级差,主震的能量占全序列能量的百分比(能量比),余震活动水平以及地震序列的某些统计特征(b值等),把地震序列分为三种基本类型:主震余震型、震群型和弧立型。实践证明,这三种类型基本上反映了各地震序列之间的差别,对于正确地判断地震趋势和预报强余震起了积极作用。     

青海及邻区中强地震序列特征分析

对1980年以来青海及邻区(31°～40°N, 88°～104°E)中强震序列类型判定标准及序列参数特征进行了分析和研究。根据青海及邻区中强地震序列的特征,将地震序列划分为孤立型、主震—余震型和多震型。参数研究结果表明,ρ值基本上对中强以上地震序列类型判别无贡献;b值和h值的共同特点是:孤立型主震—余震型多震型;孤立型地震序列的U值、F值和k值结果为0或者趋近于0,且这3个参数的均值都具孤立型主震—余震型多震型的特征;k值对地震类型判别有较好的区分度,孤立型地震序列k值近似于零,主震—余震型地震序列k值≤0.2,而多震型地震序列k值0.2。这些可作为划分地震序列类型的判别指标。     

云南地区余震序列的能量衰减

利川判断地震序列能蕈释放衰减是否异常的Ec—k量板,汁算了云南及附近地区39次巾强地震序列的能量衰减系数k值。结果显示：①当判别指标k〉1时,地震序列能量衰减处于正常状态;当k≤1时,判断地震序列能量衰减出现异常,其后发生更大地震或强余震的町能什较大。②对云南地区中强地震序列的榆验表明,有74％的地震序列符合上述判别指标。③用相同的地震进行了地震序列频度衰减系数^值的计算,发现符合h值判别指标的地震序列占统计际本的锄％。④对日常地震跟踪临视中遇到的二次典型地震序列详细分析,发现用k值力。法无论对中小地震序列还是巨震序列,预测效果均较好。     

震群型序列活动特征

在较大地震发生后,余震即开始活动,地震序列显示出不同特征。按照地震能量的释放规律和序列活动的特点,可以分为三个基本类型,震群型是其中一种类型。本文系从能量、频次、地质条件以研究震群型活动的特点,发现余震活动总体积与序列释放总能量成正比。震前小震群的展布面积与未来续发性强震震级有关。多组构造交接复合的三角地块或菱形断块则是震群型序列活动的有利场所;介质条件不均一的破碎地带则是震群型序列活动的主要条件。     

1980 年以来青海地区震群活动与前震序列特征分析

采用青海地震台网资料,系统整理分析了青海地区的震群活动及前震序列,总结了震群活动与中强以上地震的时空关系,检验了前兆震群类型的判断指标。研究认为,青海地区ML≥2 震群活动增强对区内6. 5 级以上地震有一定的中长期时间预测意义,对7 级以上地震有一定的时空预测意义。利用MAPSIS 软件6 项震群参数,以满足4 项前兆指标的全组合模式判断前兆震群,对研究区总频次大于40 的34 个震群进行参数计算,判断出前兆震群24 个,占总数的71% 。100% 前兆震群后发生相应的中强震,部分非前兆震群后也发生相应的中强震;震群对应的中强震80% 发生在本地震构造带,对中强震孕育区域有一定的指示意义。青海地区有前震序列的震例较少,仅有的3 例,参数计算均不符合前震序列判断指标,对强震无预测意义。     

PP聚类在震群分析中的应用研究

以1972——1992年新疆98个震群为样本，用U，K，最大地震序列的能量比等8个参数作为测量震群形态的特征量，应用PP聚类方法对它们进行了数值聚类分析．结果表明:这98个震群大体可分为A，B，C，D四类．A类震群有24个，其中18个震群发生后，未来12个月内，震群周围有强震发生；而在共计61个C，D类震群中，只有7个在震群发生后，未来12个月内，震群后周围有强震发生；B类震群后的强震发生率仅为3/11，可见，采用PP聚类方法，能有效地识别出前兆震群(A类)，正确地判断震群周围地区的中短期地震趋势． PP聚类方法是一种有效的新兴分类法，能广泛地应用于地震序列的类型判别等多项分类中．      

SCIENCE CHINA Earth Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Distribution of throughfall and stemflow in multi‐strata agroforestry,perennial monoculture,fallow and primary forest in central Amazonia,Brazil

The partitioning of rain water into throughfall, stemflow and interception loss when passing through plant canopies depends on properties of the respective plant species, such as leaf area and branch angles. In heterogeneous vegetation, such as tropical forest or polycultural systems, the presence of different plant species may consequently result in a mosaic of situations with respect to quantity and quality of water inputs into the soil. As these processes influence not only the water availability for the plants, but also water infiltration and nutrient leaching, the understanding of plant effects on the repartitioning of rain water may help in the optimization of land use systems and management practices. We measured throughfall and stemflow in a perennial polyculture (multi‐strata agroforestry), monocultures of peach palm (Bactris gasipaes) for fruit and for palmito, a monoculture of cupuaçu (Theobroma grandiflorum), spontaneous fallow and primary forest during one year in central Amazonia, Brazil. The effect on rain water partitioning was measured separately for four useful tree species in the polyculture and for two tree species in the primary forest. Throughfall at two stem distances, and stemflow, differed significantly between tree species, resulting in pronounced spatial patterns of water input into the soil in the polyculture system. For two tree species, peach palm for fruit (Bactris gasipaes) and Brazil nut trees (Bertholletia excelsa), the water input into the soil near the stem was significantly higher than the open‐area rainfall. This could lead to increased nutrient leaching when fertilizer is applied close to the stem of these trees. In the primary forest, such spatial patterns could also be detected, with significantly higher water input near a palm (Oenocarpus bacaba) than near a dicotyledonous tree species (Eschweilera sp.). Interception losses were 6·4% in the polyculture, 13·9 and 12·3% in the peach palm monocultures for fruit and for palmito, respectively, 0·5% in the cupuaçu monoculture and 3·1% in the fallow. With more than 20% of the open‐area rainfall, the highest stemflow contributions to the water input into the soil were measured in the palm monocultures and in the fallow. Copyright © 1999 John Wiley & Sons, Ltd.     

A Monte Carlo study of rainfall forecasting with a stochastic model

A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities.     

Anthropogenic Eutrophication and Red Tide Outbreak in Lacustrine Systems of the Kashmir Himalaya

Red tide, a recurrent phenomenon has become conspicuous in several Kashmir lake ecosystems since 1991. The responsible organism (Euglena pedunculata), a rare flagellate rediscovered in the Kashmir Himalaya (Khan 1993) caused first and unprecedented red tide outbreak, constituting a maximum of 96% of resident numerical phytoplankton density in Dal Lake. At present, conflicting hypotheses exist on the generation of causal assemblage(s) imparting redness to waters: Jeeji Bai (1991) linked its origin to acid precipitation – a fallout of burning oil‐fields during the Gulf War – whilst Khan (1993) holds local factor(s) responsible. Field/experimental studies support the latter contention that the influx of untreated sewage, in unison with warm temperatures, high levels of PhAR, iron and interruption to hydrological flow‐pattern together with absence/or reduction in grazing activity created conducive environmental milieu for red tide outbreak. Dal Lake “red tide” drifted the bloom‐inoculum to other waters, including Lake Wular, where additional ecological niches were carved out, threatening the aesthetic value and biological diversity of Kashmir lakes. Ecological monitoring indicates frequent seasonal red tide occurrence in Dal Lake (including summer‐autumn event of 1998) which testifies its unabated eutrophication status. Further studies are needed on ecological adaptability and biogeographic distribution of this rare and unique red tide‐causing flagellate.