THE CHUBB/BAUMAN METHOD FOR ESTIMATING THE RECREATION POTENTIAL OF RIVERS: A CRITICAL REVIEW1

ABSTRACT: The Chubb/Bauman (Ch/B) method for making quantitative estimates of recreation potential for rivers is based on the 1968/ 69 Leopold method for quantitative assessment of the scenic beauty of rivers. Both use classifications of environmental variables as the database. Unlike the Leopold method, the classifications used in the Ch/B method consistently reflect human preferences. The Ch/B method collects information on 67 variables, and uses a computer program to produce estimates of potential for 16 common recreation activities. This critique evaluates selected concepts and procedures of the Ch/B method partly by comparison with other available methods of recreation resource inventory. It considers the validity and utility of numerical weighting of variables, the use of numbers derived from place in a classification, and the transformation process. The quantitative techniques of the method exhibit serious flaws. Much of the data produced by the method appears to be quantitative but in fact is not, and it does not produce truly quantitative estimates of recreation potential. Classifications of generalized geographic or environmental variables are shown to have serious defects as a basis for evaluation of recreational potential.     

PAST AND FUTURE OF ANALYSIS OF WATER RESOURCES TIME SERIES1

ABSTRACT: water resources supply and demand time series consist of several or all of the four basic characteristics: tendency, intermittency, periodicity and stochasticity. Their importance changes from one type of variables to another. Historic developments of analysis of time series in hydrology have varied significantly over the past, from the stress on search for periodicities and persistence in annual series to the emphasis on the series stochastic properties. Supply and demand series are often highly interrelated, which fact is most often neglected in planning water resources systems in general, and water storage capacities in particular. The future of series analysis in water resources will likely be by a joint use of physically-based structural analysis and the use of advanced methods of treating data by stochastic processes, statistical estimation and inference techniques. The most intriguing challenge of the future of this analysis may be the treatment of nonnormal, nonlinear and in general nonstationary hydrologic and water use time series. The proper treatment of complex multivariate processes will also challenge the specialists, especially for the purposes of transfer of information between data on variables at given points, or between data at several points of a given variable, or both.     

A STOCHASTIC DYNAMIC PROGRAMMING BASED APPROACH TO THE OPERATION OF A MULTI-RESERVOIR SYSTEM1

ABSTRACT: An heuristic iterative technique based upon stochastic dynamic programming is presented for the analysis of the operation of a three reservoir ‘Y’ shaped hydroelectric system. The technique is initiated using historical inflow data for the downstream reservoir. At each iteration the optimal policies for the downstream hydroelectric generating unit are used to provide relative weightings or targets for operation of upstream reservoirs. New input inflows to the downstream reservoir are then obtained by running the historical streamflow record through the optimal policies for the upstream reservoirs. These flows are then used to develop a new operating policy for the downstream reservoir and hence new targets for the upstream reservoirs. The process is continued until the operating policies for each reservoir provide the same overall system benefit for two successive iterations. Results obtained from the procedure are compared to the results obtained by historical operation of the system. The procedure is shown to develop operating policies which give benefits which are as close to the historical benefits as can be expected given the choice of the number of storage state variables.     

A PROBABILISTIC BENEFIT-COST ANALYSIS OF A ZONING PROGRAM FOR FLOOD PLAINS1

ABSTRACT: Various techniques, one of which is zoning, are used to control the extent of flood damage. The benefit-cost analysis of zoning programs must take into account the random nature of flooding. This paper outlines a method for determining not only the expected value of the benefit-cost ratio, but also the probability of such a zoning program being profitable. It also presents an application of the method to the assessment of the Outaouais Regional Community zoning program.     

Application Of Artificial Neural Network Models To Analyse The Relationships Between Gammarus pulex L. (Crustacea, Amphipoda) And River Characteristics

This study aimed at analysing the relationship between river characteristics and abundance of Gammarus pulex. To this end, four methods which can identify the relative contribution and/or the contribution profile of the input variables in neural networks describing the habitat preferences of this species were compared: (i) the ‘PaD‘ (‘Partial Derivatives‘) method consists of a calculation of the partial derivatives of the output in relation to the input variables; (ii) the ‘Weights‘method is a computation using the connection weights of the backpropagation Artificial Neural Networks; (iii) the ‘Perturb‘method analyses the effect of a perturbation of the input variables on the output variable; (iv) the ‘Profile‘ method is a successive variation of one input variable while the others are kept constant at a fixed set of values. The dataset consisted of 179 samples, collected over a three-year period in the Zwalm river basin in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Gammarus pulex were used in this study. The different contribution methods gave similar results concerning the order of importance of the input variables. Moreover, the stability of the methods was confirmed by gradually removing variables. Only in a limited number of cases a shift in the relative importance of the remaining input variables could be observed. Nevertheless, differences in sensitivity and stability of the methods were detected, probably as a result of the different calculation procedures. In this respect, the ‘PaD‘method made a more severe discrimination between minor and major contributing environmental variables in comparison to the ‘Weights‘, ‘Profile‘ and ‘Perturb‘ methods. From an ecological point of view, the input variables ‘Ammonium‘ and to a smaller extent ‘COD‘, were selected by these methods as dominant river characteristics for the prediction of the abundance of Gammarus pulex in this study area.     

不确定条件下矿产资源的最优开采

通过一个连续时间的随机动态规划模型,探讨了市场需求、资源存量的不确定性以及勘探活动对矿产资源价格和开采速度的影响,并给出了随机条件下Hotelling法则的表达形式.模型结果显示:不确定性对资源价格变化速度的影响主要取决于开采成本,如果相对于资源存量来说开采成本是不变的或者开采的规模成本是不变的,则不确定性对资源价格的变化速度没有影响.反之,如果开采的规模成本是递增的,则不确定性会加速资源价格的变化.此外,不确定性的存在将加快资源的开采速度.至于勘探活动,它一方面降低了地质条件的不确定性,另一方面增加了资源的存量,所以勘探活动降低了资源价格和开采速度的变化率,减少了不确定性对资源开采的影响.     

洪水多站峰量同时模拟的随机模型

洪水过程是一复杂的随机动力系统，随机模拟技术至今仍是研究洪水过程时空统计特性的有力工具。该文以同时模拟上游站、下游站及其区间的最大洪峰流量、最大五日洪量和最大十二日洪量为例，建立了一种简便而适用的随机模型。实例结果表明，该随机模型是可行而有效的，在水资源系统工程的理论与实践中具有重要价值。     

SOLUTE TRANSPORT IN THREE‐DIMENSIONAL SATURATED POROUS MEDIA HAVING SELF‐SIMILAR HYDRAULIC CONDUCTIVITY DISTRIBUTION1

ABSTRACT: Customarily, it has been assumed that hydraulic conductivity is a stationary, homogeneous stochastic process with a finite variance for stochastic analysis of solute transport in the subsurface. That the distribution of hydraulic conductivity may have a fractal behavior with long range correlations was suggested from field data analyses. This motivates us to further investigate how the fractal behavior of permeability distribution impacts solute transport in porous media. This study provides longitudinal and transverse macrodispersivity coefficients and the variance of the solute concentration. Longitudinal and transverse macrodispersivity coefficients are found to depend strongly on the fractal dimension (D) of logarithmic hydraulic conductivity (logK). The longitudinal and transverse macrodispersivity coefficients are the highest when D = 1, and the values decrease monotonically to zero at D = 2. Both coefficients correspond to the characteristic length scale of the logK distribution, thus are scale dependent parameters. The ratio of the transverse to the longitudinal macrodispersivity coefficient is on the order of 10^‐1 to 10^‐4. Concentration variance also decreases with the fractal dimension of logK. There is no spatial spreading of solute for D = 2, and the concentration variance reaches zero for this case.     

基于竞争失效的导弹机电产品可靠性评估

目的 解决导弹机电产品退化-突发竞争失效模式下的可靠性评估问题。方法 对导弹典型机电产品电机进行贮存失效分析,同时考虑双参数退化失效和突发失效对电机贮存可靠性的影响。首先,以具有随机效应的非线性Wiener过程描述电机贮存退化失效过程中的非线性、随机性和样本差异性。然后,采用Weibull分布描述突发失效过程规律,并考虑退化程度对突发失效的影响。最后,利用Copula函数刻画退化性能参数之间的相互作用关系,建立双参数退化-突发竞争失效模型,并给出基于两步极大似然估计的参数估计方法。结果 以仿真导弹电机退化突发失效数据为例进行分析,实现了基于双参数退化-突发竞争失效模型的系统可靠性评估,得到电机贮存5 a时的可靠度估计值为0.465。结论 所构建的双参数随机退化与突发失效相关的竞争失效模型有效,为导弹机电产品可靠性验证评估及寿命预测提供了相应的理论依据。     

Evaluation of the effect of meteorological data resolution on Lagrangian particle dispersion simulations using the ETEX experiment

This paper presents results from a series of numerical experiments designed to evaluate operational long-range dispersion model simulations, and to investigate the effect of different temporal and spatial resolution of meteorological data from numerical weather prediction models on these simulations. Results of Lagrangian particle dispersion simulations of the first tracer release of the European Tracer Experiment (ETEX) are presented and compared with measured tracer concentrations. The use of analyzed data of higher resolution from the European Center for Medium-Range Weather Forecasts (ECMWF) model produced significantly better agreement between the concentrations predicted with the dispersion model and the ETEX measurements than the use of lower resolution Navy Operational Global Atmospheric Prediction System (NOGAPS) forecast data. Numerical experiments were performed in which the ECMWF model data with lower vertical resolution (4 instead of 7 levels below 500 mb), lower temporal resolution (12 h instead of 6 h intervals), and lower horizontal resolution (2.5° instead of 0.5°) were used. Degrading the horizontal or temporal resolution of the ECMWF data resulted in decreased accuracy of the dispersion simulations. These results indicate that flow features resolved by the numerical weather prediction model data at approximately 45 km horizontal grid spacing and 6 h time intervals, but not resolved at 225 km spacing and 12 h intervals, made an important contribution to the long-range dispersion.