基于Matlab的断裂带温泉水地球化学特征及地震活动性研究

基于Matlab开发出地下流体分析软件,对比分析了甘肃西秦岭北缘的武山、街子和清水温泉水化学组分特征;初步分析了温泉水水质类型、补给来源、水-岩平衡状态以及循环深度,并讨论了温泉水深循环对地震活动性的影响.研究表明温泉水均为大气降水成因,其水化特征受围岩的控制作用;清水温泉水的成熟度没有武山和街子温泉水高.地下水循环深度较浅的武山温泉和街子温泉水化类型属于Na-HCO3·SO4·Cl,所处断裂的地震活动频繁;地下水循环深度较深的清水温泉水化类型属于Na-SO4·Cl,所处断裂的地震活动性弱.     

The Coral Triangle Initiative and regional exchanges: Strengthening capacity through a regional learning network

Natural resource management and conservation programs that promote building capacity and social learning among participants often lead to the formation of learning networks: a type of social network where learning is both a goal and potential outcome of the network. Through forming relationships and sharing information, participants in a learning network build social capital that can help a network achieve social and environmental goals. In this study, we explored social capital in a learning network that emerged through a large-scale marine governance effort, the Coral Triangle Initiative on Coral Reefs, Fisheries, and Food Security. Through a mixture of social network analysis and key informant interviews, we examined the major patterns of information exchange among individuals who had participated in regional learning exchanges; evaluated whether the network's structure resulted in information sharing; and considered implications for strengthening network sustainability, capacity building, and learning. We found that the Regional Exchange network fostered information sharing among participants across national and organizational boundaries. While the network had individuals who were more central to information sharing, the network structure was generally decentralized, indicating potential resilience to changes in leadership and membership. Participants stressed the importance of the knowledge and connections they had acquired through the learning network; however, they expressed doubts regarding its sustainability and stressed the need for a strong coordinating entity. Our findings suggest that conservation learning networks have the ability to bridge cultural divides and promote social learning; however, a strong network coordinator and continuing efforts to support information sharing and learning are crucial to the network's strength and sustainability. The tangible learning and capacity development outcomes cultivated through Regional Exchange network underscore the value of and need to invest in conservation networks that support peer-to-peer learning.     

BIBLIOGRAPHIE

Abstract

Time series modelling approaches are useful tools for simulating and forecasting hydrological variables and their change through time. Although linear time series models are common in hydrology, the nonlinear time series model, the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, has rarely been used in hydrology and water resources engineering. The GARCH model considers the conditional variance remaining in the residuals of the linear time series models, such as an ARMA or an ARIMA model. In the present study, the advantages of a GARCH model against a linear ARIMA model are investigated using three classes of the GARCH approach, namely Power GARCH, Threshold GARCH and Exponential GARCH models. A daily streamflow time series of the Matapedia River, Quebec, Canada, is selected for this study. It is shown that the ARIMA (13,1,4) model is adequate for modelling streamflow time series of Matapedia River, but the Engle test shows the existence of heteroscedasticity in the residuals of the ARIMA model. Therefore, an ARIMA (13,1,4)-GARCH (3,1) error model is fitted to the data. The residuals of this model are examined for the existence of heteroscedasticity. The Engle test indicates that the GARCH model has considerably reduced the heteroscedasticity of the residuals. However, the Exponential GARCH model seems to completely remove the heteroscedasticity from the residuals. The multi-criteria evaluation for model performance also proves that the Exponential GARCH model is the best model among ARIMA and GARCH models. Therefore, the application of a GARCH model is strongly suggested for hydrological time series modelling as the conditional variance of the residuals of the linear models can be removed and the efficiency of the model will be improved.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Modarres, R. and Ouarda, T.B.M.J., 2013. Modelling heteroscedasticty of streamflow times series. Hydrological Sciences Journal, 58 (1), 1–11.     

搅拌桩复合地基平面模拟的简化方法探讨

水泥土搅拌桩(DMM)在高速公路工程中得到广泛应用,人们也希望能对该复合地基在路堤荷载下的地基的变形深入了解,其数值分析是一种重要的方法。但是,采用三维有限元进行数值模拟在高速公路工程中容易造成数组过大,计算时间并且收敛性比较差,因此把三维问题简化为二维问题是众望所归。在把三维问题简化二维平面问题简化计算时,最重要的是参数的折减。基于水泥土搅拌桩复合地基的特性,结合理论分析提出了一种参数折减的方法。并依据连盐高速公路实测的数据验证了该参数简化方法的可行性。     

甘肃“5·5"黑风暴小波分析

用小波变换理论对１９９３年春季甘肃省河西走廊地区一场特大黑风暴进行了分析。结果表明，小波分析能比较客观地将时间序列中不同时间尺度的振动分离开，使我们能清楚地看到黑风暴中的中尺度扰动。     

海水声速剖面基函数的重构性能分析

海水声速剖面通常使用经验正交函数（Empirical Orthogonal Function,EOF）进行稀疏表示,然而基函数会受到数据完备性和数据测量时间的制约,其代表性误差会导致声速剖面重构精度受限。为了提高声速剖面的重构精度,本文利用模糊C均值聚类对BOA_Argo历史数据集进行聚类分析,探讨不同聚类空间的训练集数据对实测声速剖面重构精度的影响。研究表明,声速剖面具有明显的时空聚集特性,聚类后的历史声速剖面集生成的基函数和平均声速剖面具有最优的重构性能。本文研究结果有助于为历史声速剖面训练集的选取提供实际指导意义,进而提高声速剖面重构精度乃至反演精度。     

非均质地基中平面应变隧道开挖面稳定上限分析

非均质是软黏土地基中比较普遍的现象,而目前隧道开挖面稳定研究中比较成熟的理论主要是针对均质土体。因此,从塑性极限分析上限法的基本原理出发,采用平面应变隧道刚体平动破坏模式(多块体上限法),考虑软黏土地基的非均质性,推导了平面应变隧道极限支护压力关于隧道埋深、土体重度及土体强度的上限公式。通过与其他方法的比较分析,证明了极限分析方法在隧道开挖面稳定性方面的可行性;利用该方法的计算结果详细探讨了隧道开挖面稳定的影响因素;而且由计算结果可知,地基土的非均质性在影响隧道开挖面极限支护压力的同时,也影响着隧道开挖破坏面的位置和形状,为工程实践提供重要的理论依据。     

泌阳断陷下第三系核三上段高频层序中米兰柯维奇天文旋回信息

古气候是影响陆相层序发育的一个重要因素,其周期性变化是源于天文旋回的驱动力（即米兰柯维奇假说）。米兰柯维奇天文旋回包括偏心率旋回、倾斜率旋回和岁差旋回,这几个轨道参数所驱动的古气候变迁,分别形成了周期为１０万年（或４０万年）、４万年及２万年的高频层序,即小层序组、小层序及小层单元,研究结果表明,泌阳断陷湖盆的高频层序是由地球轨道旋回所驱动的古气候周期性变迁所形成的。     

GNSS-MR技术用于雪深探测的初步研究

全球导航卫星系统干涉反射测量（global navigation satellite system-interferometric reflectometry,GNSS-IR）技术能探测浅层地表的土壤湿度。针对多系统组合的土壤湿度反演问题,基于轨迹聚类方法,从全球定位系统(global positioning system,GPS)、北斗卫星导航系统（BeiDou satellite navigation system,BDS）、格洛纳斯(GLONASS)、伽利略（Galileo）导航系统的信噪比观测数据中提取多径干涉相位,利用经验模型求解轨迹聚类后的土壤湿度估计值,以加权平均方式得到系统组合后的估计结果。结果表明,BDS、Galileo反演精度相当且优于GPS、GLONASS,基于轨迹聚类的多系统组合土壤湿度估计方法的均方根误差为0.041 4 cm³/cm³,相比于单系统的综合反演精度提升约16.3%,相比于单系统的最佳频段反演精度提升约5.2%,所提方法能有效监测土壤湿度的变化。