关于水文地质水井钻探工程中新型自动解垢过滤器的分析研究

水文地质钻探、水井钻探是探矿工程的重要组成部分。随着水资源需求量的增加和生态环境保护要求的提高,水文地质和水井钻探工程显得更为重要。在其成井过程中,常见过滤器腐蚀结垢,直接影响井眼进水量和抽水效果,甚至导致过滤器和井眼报废。俄罗斯南方国立技术大学Третьяк А.Я.教授等人发明了自动解垢过滤器,解决了过滤器腐蚀结垢问题。     

中国地区集合预报产品自适应递减平均偏差订正法的改进研究

基于中国地区T213集合预报产品2 m温度预报数据,采用卡尔曼滤波类型的自适应递减平均法进行偏差订正处理,原方案在剧烈降温天气订正效果表现不理想。通过对递减平均参数w的重新构建得到改进的订正方案w(i,p)(i为站点信息,p为天气过程信息),在此基础上进一步优化对历史信息的有效提取,得到改进的方案w(i,p)相似法和w(i,p)统计法,并进行效果检验。结果表明:改进为包含空间和天气过程信息的函数w(i,p)后方案的订正效果得到不同程度的提高,其中24 h剧烈降温预报各成员预报均方根误差平均减小了0. 15℃;而进一步改进的w(i,p)统计法在当前几种剧烈降温预报中订正效果最优,其集合平均偏差与w(i,p)方案相比减小2. 54℃。     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

The Mathematic Models of the Kalman Filtering for Across-Fault Measurement

This paper makes a probe into the application of the Kalman filtering method to the data processing of across-fault measurements.On the basis of statistical regression,the mathematic and stochastic models of filtration are established by combining the regression method with Kalman filtering.In the filtering computation,not only the randomness of fault movements but also the time-dependent variation of environmental effects have been taken into consideration.By use of the adaptive filtering method,an estimation of the dynamic noise variance matrix is obtained through iteration.Models for one measuring line(leveling line or baseline),two measuring lines(both leveling lines or both baselines)and four measuring lines(two leveling lines and two baselines)are derived and established systematically.By means of these models,the data of across-fault measurements can be processed dynamically in real-time to provide the filtered values of height difference between benchmarks or baseline length at different time in     

Cost-effective network design for groundwater flow monitoring

The extensive use of groundwater resources has increased the need for developing cost-effective monitoring networks to provide an indication of the degree to which the subsurface environment has been affected by human activities. This study presents a cost-effective approach to the design of groundwater flow monitoring networks. The groundwater network design is formulated with two problem formats: maximizing the statistical monitoring power for specified budget constraint and minimizing monitoring cost for statistical power requirement. The statistical monitoring power constraint is introduced with an information reliability threshold value. A branch and bound technique is employed to select the optimal solution from a discrete set of possible network alternatives. The method is tested to the design of groundwater flow monitoring problem in the Pomona County, California.     

利用LAU效应测定干涉滤光片的中心透过率波长值

本文提出一种利用LAU效应测定干涉滤光片中心透过率波长值的理论和实验方法,这一方法不但具有精度高、装置简单、方法简便等优点,而且由该方法所获得的实验结果,可以作为当前有关平面周期物体LAU 效应新理论的一种实践检验。     

快速序贯算法

本文讨论了序贯算法的基本原理，与ｋａｌｍａｎ滤波的关系，和序贯算法的渐近性态，得到无先验信息的序贯算法不受初值的影响。实例分析表明，此序贯算法可适于方程系数阵的求逆、求解和病态方程的快速解算。     

Exploratory spectral analysis of hydrological times series

Current methods of estimation of the univariate spectral density are reviewed and some improvements are made. It is suggested that spectral analysis may perhaps be best thought of as another exploratory data analysis (EDA) tool which complements, rather than competes with, the popular ARMA model building approach. A new diagnostic check for ARMA model adequacy based on the nonparametric spectral density is introduced. Additionally, two new algorithms for fast computation of the autoregressive spectral density function are presented. For improving interpretation of results, a new style of plotting the spectral density function is suggested. Exploratory spectral analyses of a number of hydrological time series are performed and some interesting periodicities are suggested for further investigation. The application of spectral analysis to determine the possible existence of long memory in natural time series is discussed with respect to long riverflow, treering and mud varve series. Moreover, a comparison of the estimated spectral densities suggests the ARMA models fitted previously to these datasets adequately describe the low frequency component. Finally, the software and data used in this paper are available by anonymous ftp from fisher.stats.uwo.ca.     

基于误差准则和循环迭代的时移地震匹配滤波方法

分析了用于时移地震互均衡处理中的传统匹配滤波算法适用范围，结果表明该方法在滤波算子的反算子为最小相位时效果最好.对该方法难以解决的混合相位问题，推导出通用公式，并提出基于最小平方误差准则和循环迭代的求解方法.理论和实际数据都验证了该方法较已有方法的优越性.