The mean and turbulence structure simulation of the monsoon trough boundary layer using a one-dimensional model withe-l ande-ε closures

An attempt has been made here to study the sensitivity of the mean and the turbulence structure of the monsoon trough boundary layer to the choice of the constants in the dissipation equation for two stations Delhi and Calcutta, using one-dimensional atmospheric boundary layer model withe-ε turbulence closure. An analytical discussion of the problems associated with the constants of the dissipation equation is presented. It is shown here that the choice of the constants in the dissipation equation is quite crucial and the turbulence structure is very sensitive to these constants. The modification of the dissipation equation adopted by earlier studies, that is, approximating the Tke generation (due to shear and buoyancy production) in theε-equation by max (shear production, shear + buoyancy production), can be avoided by a suitable choice of the constants suggested here. The observed turbulence structure is better simulated with these constants. The turbulence structure simulation with the constants recommended by Aupoixet al (1989) (which are interactive in time) for the monsoon region is shown to be qualitatively similar to the simulation obtained with the constants suggested here, thus implying that no universal constants exist to regulate dissipation rate. Simulations of the mean structure show little sensitivity to the type of the closure parameterization betweene-l ande-ε closures. However the turbulence structure simulation withe-ε. closure is far better compared to thee-l model simulations. The model simulations of temperature profiles compare quite well with the observations whenever the boundary layer is well mixed (neutral) or unstable. However the models are not able to simulate the nocturnal boundary layer (stable) temperature profiles. Moisture profiles are simulated reasonably better. With one-dimensional models, capturing observed wind variations is not up to the mark.     

氧化亚铁硫杆菌水文地球化学作用实验初步研究

在某些地球化学环境中，微生物对水─岩相互作用有重要影响。本文通过氧化亚铁硫杆菌与硫化物相互作用试验，初步研究了氧化亚铁硫杆菌作用引起水─岩介质变化特征，分析了氧化亚铁硫杆菌水文地球化学作用的一些规律。     

Application of an optimum design technique for determining the coefficient of consolidation by using piezocone test data

For normally consolidated clay, several researchers have developed a number of theoretical time factors to determine the coefficient of consolidation from piezocone test results. However, depending on assumptions and analytical techniques, it could vary considerably, even for a specific degree of consolidation. In this paper a method is proposed to determine a consistent coefficient of consolidation by applying the concept of an optimum design technique over all ranges of the degree of consolidation. Initial excess pore pressure distribution is assumed to be capable of being obtained by the successive spherical cavity expansion theory. The dissipation of pore pressure is simulated by means of a two-dimensional linear-uncoupled axi-symmetric consolidation analysis. The minimization of differences between measured and predicted excess pore pressure was carried out by the BFGS unconstrained optimum design algorithm with a one-dimensional golden section search technique. By analyzing numerical examples and in-situ test results, it was found that the adopted optimum design technique gives consistent and convergent results.     

导水裂隙带高度预测途径探讨

导水裂隙带高度是设计防水煤（岩）柱尺寸的主要技术参数，是煤矿防治水工作的重要内容。详细论述了其研究现状及发展趋势，并提出了履岩体地质环境，履岩体力学环境和数值模拟技术三位一体的综合预测评价方法。     

Effects of geology and human activity on the dynamics of salt-water intrusion in three coastal aquifers in southern Spain

 Mathematical modelling of salt-water intrusion processes in three aquifers on the southern coast of Spain (Río Verde, Río Vélez and Castell de Ferro) reveals that, although all three systems are subject to the same climate and seasonal over-exploitation, geological and human factors have very different effects on the dynamics of contamination. In the Río Verde aquifer, the most important influence is the high volume of extractions occurring during the dry season; in Río Vélez, the intrusion is strongly controlled by infiltration of water from the river to the aquifer, and, in the Castell de Ferro system, an intensely karstified carbonate massif lying in contact with both the sea water and the detrital aquifer represents the main entrance point for influx of sea water and subsequent washing of the aquifer. We have undertaken a mathematical simulation of various possible measures to counteract intrusion, according to the specific characteristics of the process in each aquifer. These measures include artificial recharge, use of natural recharge from the river as a hydraulic barrier, and the construction of a low-permeability barrier. Received: 5 December 1995 · Accepted: 12 April 1996     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

Conceptually-based shot noise modeling of streamflows at short time interval

A conceptual-stochastic approach to short time runoff data modelling is proposed, according to the aim of reproducing the hydrological aspects of the streamflow process and of preserving as much as possible the dynamics of the process itself. This latter task implies preservation of streamflow characteristics at higher scales of aggregation and, within a conceptual framework, involves compatibility with models proposed for the runoff process at those scales. At a daily time scale the watershed response to the effective rainfall is considered as deriving from the response of three linear reservoirs, respectively representing contributions to streamflows of large deep aquifers, with over-year response lag, of aquifers which run dry by the end of the dry season and of subsurface runoff. The surface runoff component is regarded as an uncorrelated point process. Considering the occurrences of effective rainfall events as generated by an independent Poisson process, the output of the linear system represents a conceptually-based multiple shot noise process. Model identification and parameter estimation are supported by information related to the aggregated runoff process, in agreement to the conceptual framework proposed, and this allows parameter parsimony, efficient estimation and effectiveness of the streamflow reproduction. Good performances emerged from the model application and testing made with reference to some daily runoff series from Italian basins.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.