渤海主要渔业资源结构的演变分析

通过对现有资料的系统分析,简化了渤海生态系统食物网,并剖析了近50年来渤海主要渔业资源结构的变化特征,这对进一步阐明渤海生态系统动力学的变化特征以及研究渔业资源衰退的原因有重要的科学意义。研究表明,渤海主要鱼类可聚为4类:游泳动物食性鱼类、底栖动物食性鱼类、浮游动物食性鱼类和腐屑食性鱼类,在此基础上渤海生态系统食物网可简化为3条食物链:浮游植物→浮游动物→浮游动物食性鱼类→游泳动物食性鱼类(第一条食物链);浮游植物和碎屑→底栖动物→底栖动物食性鱼类和头足类→游泳动物食性鱼类(第二条食物链);碎屑→腐屑食性鱼类(第三条食物链)。20世纪50年代末以来,第一条食物链渔业资源已取代第二条食物链渔业资源成为最主要的渔业资源,第三条食物链渔业资源生物量百分比呈上升趋势,近年来已成为继第一条食物链渔业资源的第二大类渔业资源。渔业捕捞、渤海次级生产力结构的变化以及各渔业资源生物自身生长和繁殖特点的不同是导致渤海主要渔业资源结构变化的重要因素。     

关于非齐次马氏链的强极限定理

主要研究了非齐次马氏链的强极限定理.首先应用鞅差序列收敛定理给出了关于非齐次马氏链的任意k元函数一类平均值的极限定理.最后得到一系列相关状态序偶出现频率的推论.     

马尔可夫链模型在地下水水位预测中的应用

作者将鲁南地区一水文观测孔的９２次地下水水位月平均监测数据,划分了１０种状态范围,运用马尔可夫链模型,对未来地下水水位进行状态范围预测。在与实际监测资料进行对比的基础上,验证了马尔可夫链理论在地下水水位预测中的可行性及可靠性,并对运用中的具体问题进行了探讨。     

苏皖北部地区晚元古代地层的马尔柯夫链分析

本文运用数学地质理论中的马尔柯夫链分析方法,对苏皖北部地区及鲁西南地区晚元古代地层进行了初步研究。文中选择6条比较典型的剖面,分别对它们进行了转移概率、极限概率、差值阵、置换分析和熵分析等方面的计算,并对所得结果做了相应的地质解释。分析结果,从定量方面揭示出了晚元古代时期苏皖海盆基底的“波动”史及其上覆地层的主要沉积韵律类型,以及盆地内不同部位、不同时代岩性变化的主要趋势及其阶段性;并认为,在晚元古代早期苏皖海盆中很可能同时存在有南、北两个沉积中心,而并非像以往所认为的那样,只有一个沉积中心。     

基于灰色马尔科夫链预测系统的设计与实现

通过对灰色GM[1,1]模型的算法改进,将改进后的灰色模型与马尔科夫链结合,既可以发挥灰色系统预测精确的特点,又可以利用马尔科夫链对准确预测波动性数据的优势。在灰色马尔科夫链模型的算法基础上,采用Visual Studio 2005开发环境,进行灰色马尔科夫链预测系统的设计。最后利用南方某地区十年来土地利用数据进行系统验证,结果表明,灰色马尔科夫链模型能很大地提高预测的精度和效果,符合实际要求。     

重大地震灾害链的时空有序性及其预测研究

重大地震与地震灾害链预测是当今世界地学前缘课题.本文通过国内外具体实例,重点介绍了重大地震灾害链的时空有序性、地震灾害链网络结构及其预测方法.     

河南区域经济增长俱乐部趋同研究

1990~2004年,河南区域经济增长形成了高收入、中高收入、中低收入和低收入 4个趋同俱乐部。高收入和低收入趋同俱乐部的稳定性最大且连片扩张,区域经济增长水平和空间结构的两极分化日趋增强。总体上,一个区域的"邻居区域环境"对其经济增长及其向何种趋同俱乐部转移有规律性的影响。低收入区域的经济增长及其向中低收入趋同俱乐部转移的概率与其邻居区域的经济增长水平正相关。中低收入区域更倾向于向低收入趋同俱乐部转移。对于中高收入区域,与经济增长水平越高的区域为邻,其向高收入趋同俱乐部转移的概率越大;反之,与经济增长水平越低的区域为邻,其向中低收入趋同俱乐部转移概率也越大。高收入区域的经济增长及稳定性受邻居区域的影响比较小。     

Pulse generation models for daily intermittent streamflows / Modèles de génération d’impulsions pour des débits journaliers intermittents

Abstract

Abstract Generating pulses and then converting them into flow are two main steps of daily streamflow generation. Three pulse generation models have been proposed on the basis of Markov chains for the purpose of generating daily intermittent streamflow time series in this study. The first one is based on two two-state Markov chains, whereas the second uses a three-state Markov chain. The third model uses harmonic analysis and fits Fourier series to the three-state Markov chain. Results for a daily intermittent streamflow data series show a good performance of the proposed models.     

Assessing uncertainties in a conceptual water balance model using Bayesian methodology / Estimation bayésienne des incertitudes au sein d’une modélisation conceptuelle de bilan hydrologique

Abstract

Abstract The aim of this study was to estimate the uncertainties in the streamflow simulated by a rainfall–runoff model. Two sources of uncertainties in hydrological modelling were considered: the uncertainties in model parameters and those in model structure. The uncertainties were calculated by Bayesian statistics, and the Metropolis-Hastings algorithm was used to simulate the posterior parameter distribution. The parameter uncertainty calculated by the Metropolis-Hastings algorithm was compared to maximum likelihood estimates which assume that both the parameters and model residuals are normally distributed. The study was performed using the model WASMOD on 25 basins in central Sweden. Confidence intervals in the simulated discharge due to the parameter uncertainty and the total uncertainty were calculated. The results indicate that (a) the Metropolis-Hastings algorithm and the maximum likelihood method give almost identical estimates concerning the parameter uncertainty, and (b) the uncertainties in the simulated streamflow due to the parameter uncertainty are less important than uncertainties originating from other sources for this simple model with fewer parameters.     

Daily rainfall projections from general circulation models with a downscaling nonhomogeneous hidden Markov model (NHMM) for south‐eastern Australia

An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd.