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  • Articles  (4,541)
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Stochastic environmental research and risk assessment 10 (1996), S. 1-15 
    ISSN: 1436-3259
    Keywords: Spacings ; quantiles ; generalized Pareto distribution ; log-logistic distribution
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The maximum product of spacings (MPS) method is discussed from the standpoint of information theory. MPS parameter and quantile estimates for the generalized Pareto distribution and the two parameter log-logistic distribution are compared with the maximum likelihood(ML) and probability weighted moment (PWM) estimates.
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  • 2
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    Stochastic environmental research and risk assessment 10 (1996), S. 17-37 
    ISSN: 1436-3259
    Keywords: Diffusion ; network ; reservoir ; power law
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A diffusion approximation for a network of continuous time reservoirs with power law release rules is examined. Under a mild assumption on the inflow processes, we show that for physically reasonable values of the power law constants, the system of processes converges to a multi-dimensional Gaussian diffusion process. We also illustrate how the limiting Gaussian process may be used to compute approximations to the original system of reservoirs. In addition, we study the quality of our approximations by comparing them to results obtained by simulations of the original watershed model. The simulations offer support for the use of the approximation developed here.
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  • 3
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    Stochastic environmental research and risk assessment 10 (1996), S. 39-63 
    ISSN: 1436-3259
    Keywords: Saturated flow ; rainfall ; groundwater monitoring
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A numerical experiment of flow in variably saturated porous media was performed in order to evaluate the spatial and temporal distribution of the groundwater recharge at the phreatic surface for a shallow aquifer as a function of the input rainfall process and soil heterogeneity. The study focused on the groundwater recharge which resulted from the percolation of the excess rainfall for a 90-days period of an actual precipitation record. Groundwater recharge was defined as the water flux across the moving phreatic surface. The observed spatial non-uniformity of the groundwater recharge was caused by soil heterogeneity and is particularly pronounced during the stage of recharge peak (substantial percolation stage). During that stage the recharge is associated with preferential flow paths defined as soil zones of locally higher hydraulic conductivity. For the periods of low percolation intensity the groundwater recharge was exhibiting more uniform spatial characteristics. The temporal distribution of the recharge was found to be a function of the frequency and intensity of the rainfall events. Application of sampling design demonstrates the joint influence of the spatial and temporal recharge variability on the cost-effective monitoring of groundwater potentiometric surfaces.
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  • 4
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    Stochastic environmental research and risk assessment 10 (1996), S. 65-85 
    ISSN: 1436-3259
    Keywords: Streamflow ; drought ; tree-ring data ; renewal model ; geometric variables
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract It is shown that runs of low-flow annual streamflow in a coastal semiarid basin of Central California can be adequately modelled by renewal theory. For example, runs of below-median annual streamflows are shown to follow a geometric distribution. The elapsed time between runs of below-median streamflow are geometrically distributed also. The sum of these two independently distributed geometric time variables defines the renewal time elapsing between the initiation of a low-flow run and the next one. The probability distribution of the renewal time is then derived from first principles, ultimately leading to the distribution of the number of low-flow runs in a specified time period, the expected number of low-flow runs, the risk of drought, and other important probabilistic indicators of low-flow. The authors argue that if one identifies drought threat with the occurrence of multiyear low-flow runs, as it is done by water supply managers in the study area, then our renewal model provides a number of interesting results concerning drought threat in areas historically subject to inclement, dry, climate. A 430-year long annual streamflow time series reconstructed by tree-ring analysis serves as the basis for testing our renewal model of low-flow sequences.
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  • 5
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    Stochastic environmental research and risk assessment 10 (1996), S. 87-106 
    ISSN: 1436-3259
    Keywords: Climate change ; daily precipitation modelling ; generalized linear models ; iteratively reweighted least squares ; spline functions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The precipitation amounts on wet days at De Bilt (the Netherlands) are linked to temperature and surface air pressure through advanced regression techniques. Temperature is chosen as a covariate to use the model for generating synthetic time series of daily precipitation in a CO2 induced warmer climate. The precipitation-temperature dependence can partly be ascribed to the phenomenon that warmer air can contain more moisture. Spline functions are introduced to reproduce the non-monotonous change of the mean daily precipitation amount with temperature. Because the model is non-linear and the variance of the errors depends on the expected response, an iteratively reweighted least-squares technique is needed to estimate the regression coefficients. A representative rainfall sequence for the situation of a systematic temperature rise is obtained by multiplying the precipitation amounts in the observed record with a temperature dependent factor based on a fitted regression model. For a temperature change of 3°C (reasonable guess for a doubled CO2 climate according to the present-day general circulation models) this results in an increase in the annual average amount of 9% (20% in winter and 4% in summer). An extended model with both temperature and surface air pressure is presented which makes it possible to study the additional effects of a potential systematic change in surface air pressure on precipitation.
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  • 6
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    Stochastic environmental research and risk assessment 10 (1996), S. 107-126 
    ISSN: 1436-3259
    Keywords: Gaussian process ; spatial correlation ; anisotropy ; Fourier transform ; Gauss-Newton ; ECM ; measurement error ; signal extraction ; irregular data
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This paper is concerned with developing computational methods and approximations for maximum likelihood estimation and minimum mean square error smoothing of irregularly observed two-dimensional stationary spatial processes. The approximations are based on various Fourier expansions of the covariance function of the spatial process, expressed in terms of the inverse discrete Fourier transform of the spectral density function of the underlying spatial process. We assume that the underlying spatial process is governed by elliptic stochastic partial differential equations (SPDE's) driven by a Gaussian white noise process. SPDE's have often been used to model the underlying physical phenomenon and the elliptic SPDE's are generally associated with steady-state problems. A central problem in estimation of underlying model parameters is to identify the covariance function of the process. The cumbersome exact analytical calculation of the covariance function by inverting the spectral density function of the process, has commonly been used in the literature. The present work develops various Fourier approximations for the covariance function of the underlying process which are in easily computable form and allow easy application of Newton-type algorithms for maximum likelihood estimation of the model parameters. This work also develops an iterative search algorithm which combines the Gauss-Newton algorithm and a type of generalized expectation-maximization (EM) algorithm, namely expectation-conditional maximization (ECM) algorithm, for maximum likelihood estimation of the parameters. We analyze the accuracy of the covariance function approximations for the spatial autoregressive-moving average (ARMA) models analyzed in Vecchia (1988) and illustrate the performance of our iterative search algorithm in obtaining the maximum likelihood estimation of the model parameters on simulated and actual data.
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  • 7
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    Stochastic environmental research and risk assessment 10 (1996), S. 127-150 
    ISSN: 1436-3259
    Keywords: Rainfall estimation ; indicator cokriging ; rain gage measurements
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Indicator cokriging (Journel 1983) is examined as a tool for real-time estimation of rainfall from rain gage measurements. The approach proposed in this work obviates real-time estimation of real-time statistics of rainfall by using ensemble or climatological statistics exclusively, and reduces computational requirements attendant to indicator cokriging by employing only a few auxiliary cutoffs in estimation of conditional probabilities. Due to unavailability of suitable rain gage measurements, hourly radar rain fall data were used for both indicator covariance estimation and a comparative evaluation. Preliminary results suggest that the indicator cokriging approach is clearly superior to its ordinary kriging counterpart, whereas the indicator kriging approach is not. The improvement is most significant in estimation of light rainfall, but drops off significantly for heavy rainfall. The lack of predictability in spatial estimation of heavy rainfall is borne out in the integral scale of indicator correlation: peaking to its maximum for cutoffs near the median, indicator correlation scale becomes increasingly smaller for larger cutoffs of rainfall depth. A derived-distribution analysis, based on the assumption that radar rainfall is a linear sum of ground-truth and a random error, suggests that, at low cutoffs, indicator correlation scale of ground-truth can significantly differ from that of radar rainfall, and points toward inclusion of rainfall intermittency, for example, within the framework proposed in this work.
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  • 8
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    Stochastic environmental research and risk assessment 10 (1996), S. 151-161 
    ISSN: 1436-3259
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 9
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    Stochastic environmental research and risk assessment 10 (1996), S. 163-166 
    ISSN: 1436-3259
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 10
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    Stochastic environmental research and risk assessment 10 (1996), S. 187-207 
    ISSN: 1436-3259
    Keywords: log-Gumbel distribution ; flood frequency analysis ; quantile estimation ; confidence intervals
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The log-Gumbel distribution is one of the extreme value distributions which has been widely used in flood frequency analysis. This distribution has been examined in this paper regarding quantile estimation and confidence intervals of quantiles. Specific estimation algorithms based on the methods of moments (MOM), probability weighted moments (PWM) and maximum likelihood (ML) are presented. The applicability of the estimation procedures and comparison among the methods have been illustrated based on an application example considering the flood data of the St. Mary's River.
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  • 11
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    Stochastic environmental research and risk assessment 10 (1996), S. 167-186 
    ISSN: 1436-3259
    Keywords: Reservoir stochastic theory ; reliability ; mean ; variance ; indicator function ; storage bounds ; nonlinear programming ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A new formulation is presented for the analysis of reservoir systems synthesizing concepts from the traditional stochastic theory of reservoir storage, moments analysis and reliability programming. The analysis is based on the development of the first and second moments for the stochastic storage state variable. These expressions include terms for the failure probabilities (probabilities of spill or deficit) and consider the storage bounds explicitly. Using this analysis, expected values of the storage state, variances of storage, optimal release policies and failure probabilities — useful information in the context of reservoir operations and design, can be obtained from a nonlinear programming solution. The solutions developed from studies of single reservoir operations on both an annual and monthly basis, compare favorably with those obtained from simulation. The presentation herein is directed to both traditional reservoir storage theorists who are interested in the design of a reservoir and modern reservoir analysts who are interested in the long term operation of reservoirs.
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  • 12
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    Stochastic environmental research and risk assessment 10 (1996), S. 209-229 
    ISSN: 1436-3259
    Keywords: Infiltration-advance equation ; water spreading ; cellular automata ; irrigation ; surface hydrology ; hydrodynamics ; stochastic processes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A technique has been developed for predicting the irregular advance pattern often observed as water spreads on the surface of the ground. The technique is a combination of stochastic sketching, potential theory, probability theory, and a mass balance equation in the form of an advance equation. The technique can be used on flat as well as sloping terrain and addresses any form of obstructions or constraints to the flow of the water. The stochastic sketching portion of the technique uses cellular automata with transition probability movement rules to sketch the dynamics of small volume water elements in the defined environment. Randomly selected small volume flow path segments are computed and plotted. The envelope of these segments defines the wetted area and the advance front. Several examples are presented showing the patterns produced for various situations.
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  • 13
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    Stochastic environmental research and risk assessment 10 (1996), S. 231-251 
    ISSN: 1436-3259
    Keywords: Stochastic ; multiphase ; three phase ; heterogeneity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The first paper (Chang et al., 1995b) of this two-part series described the stochastic analysis using spectral/perturbation approach to analyze steady state two-phase (water and oil) flow in a, liquid-unsaturated, three fluid-phase porous medium. In this paper, the results between the numerical simulations and closed-form expressions obtained using the perturbation approach are compared. We present the solution to the one-dimensional, steady-state oil and water flow equations. The stochastic input processes are the spatially correlated logk where k is the intrinsic permeability and the soil retention parameter, α. These solutions are subsequently used in the numerical simulations to estimate the statistical properties of the key output processes. The comparison between the results of the perturbation analysis and numerical simulations showed a good agreement between the two methods over a wide range of logk variability with three different combinations of input stochastic processes of logk and soil parameter α. The results clearly demonstrated the importance of considering the spatial variability of key subsurface properties under a variety of physical scenarios. The variability of both capillary pressure and saturation is affected by the type of input stochastic process used to represent the spatial variability. The results also demonstrated the applicability of perturbation theory in predicting the system variability and defining effective fluid properties through the ergodic assumption.
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  • 14
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    Stochastic environmental research and risk assessment 10 (1996), S. 295-317 
    ISSN: 1436-3259
    Keywords: Bayesion methods ; time series ; hydrology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A review of literature reveals the inadequacy of Intervention analysis and spectrum based methods to adequately quantify changes in hydrologic times series. A Bayesian method is used to investigate the statistical significance of observed changes in hydrologic times series and the results are reported herein. The Bayesian method is superior to the previous methods.
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  • 15
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    Stochastic environmental research and risk assessment 10 (1996), S. 253-278 
    ISSN: 1436-3259
    Keywords: Random fields ; stochastic processes ; fractals
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This paper describes a new method for generating spatially-correlated random fields. Such fields are often encountered in hydrology and hydrogeology and in the earth sciences. The method is based on two observations: (i) spatially distributed attributes usually display a stationary correlation structure, and (ii) the screening effect of measurements leads to the sufficiency of a small search neighborhood when it comes to projecting measurements and data in space. The algorithm which was developed based on these principles is called HYDRO_GEN, and its features and properties are discussed in depth. HYDRO_GEN is found to be accurate and extremely fast. It is also versatile: it can simulate fields of different nature, starting from weakly stationary fields with a prescribed covariance and ending with fractal fields. The simulated fields can display statistical isotropy or anisotropy.
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  • 16
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    Stochastic environmental research and risk assessment 10 (1996), S. 279-294 
    ISSN: 1436-3259
    Keywords: Linear estimation ; interpolation ; kriging ; splines ; conditional
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This work presents analytical expressions for the best estimate, conditional covariance function, and conditional realizations of a function from sparse observations. In contrast to the prevalent approach in kriging where the best estimates at every point are determined from the solution of a system of linear equations, the best-estimate function can be represented analytically in terms of basis functions, whose number depends on the observations. This approach is computationally superior when graphing a function estimate and is also valuable in understanding what the solution should look like. For example, one can immediately see that all “singularities” in the best-estimate function are at observation points.
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  • 17
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    Stochastic environmental research and risk assessment 10 (1996), S. 319-329 
    ISSN: 1436-3259
    Keywords: Particle tracking ; numerical methods ; random walks ; advection-dispersion equation ; stochastic processes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A formal statistical discussion of the origins of the random walk and its relation to the classic advection-dispersion equation is given. At issue is the common use of Gaussian distributed steps in producing the desired dispersive effects. Shown are alternative solutions to the basic Langevin equation describing mass displacements based on non-Gaussian, white increments. In particular, the results reveal that uniform or symmetric-triangular steps can be employed without loss of generality in accuracy of the solution (over all Peclet numbers) and may yield significant savings in the computational generation of the random deviates required in the Monte Carlo procedures of the random walk method.
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  • 18
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    Stochastic environmental research and risk assessment 10 (1996), S. 330-330 
    ISSN: 1436-3259
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 19
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    Stochastic environmental research and risk assessment 11 (1997), S. 17-31 
    ISSN: 1436-3259
    Keywords: Bivariate density ; meta-Gaussian density ; normal quantile transform ; likelihood ratio dependence ; correlation coefficient
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Convenient bivariate densities found in the literature are often unsuitable for modeling hydrologic variates. They either constrain the range of association between variates, or fix the form of the marginal distributions. The bivariate meta-Gaussian density is constructed by embedding the normal quantile transform of each variate into the Gaussian law. The density can represent a full range of association between variates and admits arbitrarily specified marginal distributions. Modeling and estimation can be decomposed into i) independent analyses of the marginal distributions, and ii) investigation of the dependence structure. Both statistical and judgmental estimation procedures are possible. Some comparisons to recent applications of bivariate densities in the hydrologic literature motivate and illustrate the model.
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  • 20
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    Stochastic environmental research and risk assessment 11 (1997), S. 33-50 
    ISSN: 1436-3259
    Keywords: Unit hydrograph ; uncertainty analysis ; linearly constrained Monte-Carlo simulation ; reliability analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Unit hydrographs (UHs), along with design rainfalls, are frequently used to determine the discharge hydrograph for design and evaluation of hydraulic structures. Due to the presence of various uncertainties in its derivation, the resulting UH is inevitably subject to uncertainty. Consequently, the performance of hydraulic structures under the design storm condition is uncertain. This paper integrates the linearly constrained Monte-Carlo simulation with the UH theory and routing techniques to evaluate the reliability of hydraulic structures. The linear constraint is considered because the water volume of each generated design direct runoff hydrograph should be equal to that of the design effective rainfall hyetograph or the water volume of each generated UH must be equal to one inch (or cm) over the watershed. For illustration, the proposed methodology is applied to evaluate the overtopping risk of a hypothetical flood detention reservoir downstream of Tong-Tou watershed in Taiwan.
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  • 21
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    Stochastic environmental research and risk assessment 11 (1997), S. 1-16 
    ISSN: 1436-3259
    Keywords: Nash cascade reservoir model ; rainfall-runoff ; EM algorithm ; filtering ; maximum likelihood estimation ; martingale estimating function
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Abstract: Linear continuous time stochastic Nash cascade conceptual models for runoff are developed. The runoff is modeled as a simple system of linear stochastic differential equations driven by white Gaussian and marked point process noises. In the case of d reservoirs, the outputs of these reservoirs form a d dimensional vector Markov process, of which only the dth coordinate process is observed, usually at a discrete sample of time points. The dth coordinate process is not Markovian. Thus runoff is a partially observed Markov process if it is modeled using the stochastic Nash cascade model. We consider how to estimate the parameters in such models. In principle, maximum likelihood estimation for the complete process parameters can be carried out directly or through some form of the EM (estimation and maximization) algorithm or variation thereof, applied to the observed process data. In this research we consider a direct approximate likelihood approach and a filtering approach to an algorithm of EM type, as developed in Thompson and Kaseke (1994). These two methods are applied to some real life runoff data from a catchment in Wales, England. We also consider a special case of the martingale estimating function approach on the runoff model in the presence of rainfall. Finally, some simulations of the runoff process are given based on the estimated parameters.
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  • 22
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    Stochastic environmental research and risk assessment 11 (1997), S. 173-192 
    ISSN: 1436-3259
    Keywords: Uncertainty analysis ; unit hydrograph ; regression analysis ; probabilistic point estimation methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated with the two parameters, N and K, in Nash's IUH model from different regional regression equations. The uncertainty features associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate that uncertainty of N and K from the regional regression equations are too significant to be ignored.
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  • 23
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    Stochastic environmental research and risk assessment 11 (1997), S. 145-171 
    ISSN: 1436-3259
    Keywords: Hydrologic regionalization ; unit hydrograph ; regression analysis ; multivariate regression ; seemingly unrelated regression ; validation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.
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  • 24
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    Stochastic environmental research and risk assessment 11 (1997), S. 193-210 
    ISSN: 1436-3259
    Keywords: Turbulence ; sediment ; fluvial ; river ; bursting process ; statistics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Entrainment of sediment particles from channel beds into the channel flow is influenced by the characteristics of the flow turbulence which produces stochastic shear stress fluctuations at the bed. Recent studies of the structure of turbulent flow has recognized the importance of bursting processes as important mechanisms for the transfer of momentum into the laminar boundary layer. Of these processes, the sweep event has been recognized as the most important bursting event for entrainment of sediment particles as it imposes forces in the direction of the flow resulting in movement of particles by rolling, sliding and occasionally saltating. Similarly, the ejection event has been recognized as important for sediment transport since these events maintain the sediment particles in suspension. In this study, the characteristics of bursting processes and, in particular, the sweep event were investigated in a flume with a rough bed. The instantaneous velocity fluctuations of the flow were measured in two-dimensions using a small electromagnetic velocity meter and the turbulent shear stresses were determined from these velocity fluctuations. It was found that the shear stress applied to the sediment particles on the bed resulting from sweep events depends on the magnitude of the turbulent shear stress and its probability distribution. A statistical analysis of the experimental data was undertaken and it was found necessary to apply a Box-Cox transformation to transform the data into a normally distributed sample. This enabled determination of the mean shear stress, angle of action and standard error of estimate for sweep and ejection events. These instantaneous shear stresses were found to be greater than the mean flow shear stress and for the sweep event to be approximately 40 percent greater near the channel bed. Results from this analysis suggest that the critical shear stress determined from Shield's diagram is not sufficient to predict the initiation of motion due to its use of the temporal mean shear stress. It is suggested that initiation of particle motion, but not continuous motion, can occur earlier than suggested by Shield's diagram due to the higher shear stresses imposed on the particles by the stochastic shear stresses resulting from turbulence within the flow.
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  • 25
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    Stochastic environmental research and risk assessment 11 (1997), S. 211-227 
    ISSN: 1436-3259
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The principle of maximum entropy (POME) was employed to derive a new method of parameter estimation for the 2-parameter generalized Pareto (GP2) distribution. Monte Carlo simulated data were used to evaluate this method and compare it with the methods of moments (MOM), probability weighted moments (PWM), and maximum likelihood estimation (MLE). The parameter estimates yielded by POME were comparable or better within certain ranges of sample size and coefficient of variation.
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  • 26
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    Stochastic environmental research and risk assessment 11 (1997), S. 523-547 
    ISSN: 1436-3259
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Kernel density estimators are useful building blocks for empirical statistical modeling of precipitation and other hydroclimatic variables. Data driven estimates of the marginal probability density function of these variables (which may have discrete or continuous arguments) provide a useful basis for Monte Carlo resampling and are also useful for posing and testing hypotheses (e.g bimodality) as to the frequency distributions of the variable. In this paper, some issues related to the selection and design of univariate kernel density estimators are reviewed. Some strategies for bandwidth and kernel selection are discussed in an applied context and recommendations for parameter selection are offered. This paper complements the nonparametric wet/dry spell resampling methodology presented in Lall et al. (1996).
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  • 27
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    Stochastic environmental research and risk assessment 11 (1997), S. 459-482 
    ISSN: 1436-3259
    Keywords: Karhunen-Loéve expansion ; Empirical Orthogonal Functions ; stochastic simulation ; gaussian fields ; analytical covariance functions ; eigenfunctions ; kriging
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract 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.
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    Stochastic environmental research and risk assessment 12 (1998), S. 1-14 
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    Keywords: Key words: Exceedance probability ; trend ; stochastic variables ; non-stationarity
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    Notes: Abstract Studying the hypothetical case of a trend superimposed on a random stationary variable, we highlight the strong influence of possible non-stationarities on exceedance probability. After a general outline, the subject is analytically developed using the Gumbel distribution, emphasizing the quick increase of the exceedance probability over time in the presence of weak rising trends, and its sensitive underestimation where the non-stationarity goes unnoticed or is considered negligible. Finally the work is applied to hydrological series of rainfall and river flow.
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    Stochastic environmental research and risk assessment 12 (1998), S. 53-64 
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    Keywords: Key words: Risk ; clustering ; point process ; Poisson ; flood.
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    Notes: Abstract: Since the introduction into flood risk analysis, the partial duration series method has gained increasing acceptance as an appealing alternative to the annual maximum series method. However, when the base flow is low, there is clustering in the flood peak or flow volume point process. In this case, the general stochastic point process model is not suitable to risk analysis. Therefore, two types of models for flood risk analysis are derived on the basis of clustering stochastic point process theory in this paper. The most remarkable characteristic of these models is that the flood risk is considered directly within the time domain. The acceptability of different models are also discussed with the combination of the flood peak counted process in twenty years at Yichang station on the Yangtze river. The result shows that the two kinds of models are suitable ones for flood risk analysis, which are more flexible compared with the traditional flood risk models derived on the basis of annual maximum series method or the general stochastic point process theory.
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    Stochastic environmental research and risk assessment 12 (1998), S. 33-52 
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    Keywords: Keywords: Streamflow ; simulation ; nonparametric
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    Notes: Abstract A new approach for streamflow simulation using nonparametric methods was described in a recent publication (Sharma et al. 1997). Use of nonparametric methods has the advantage that they avoid the issue of selecting a probability distribution and can represent nonlinear features, such as asymmetry and bimodality that hitherto were difficult to represent, in the probability structure of hydrologic variables such as streamflow and precipitation. The nonparametric method used was kernel density estimation, which requires the selection of bandwidth (smoothing) parameters. This study documents some of the tests that were conduced to evaluate the performance of bandwidth estimation methods for kernel density estimation. Issues related to selection of optimal smoothing parameters for kernel density estimation with small samples (200 or fewer data points) are examined. Both reference to a Gaussian density and data based specifications are applied to estimate bandwidths for samples from bivariate normal mixture densities. The three data based methods studied are Maximum Likelihood Cross Validation (MLCV), Least Square Cross Validation (LSCV) and Biased Cross Validation (BCV2). Modifications for estimating optimal local bandwidths using MLCV and LSCV are also examined. We found that the use of local bandwidths does not necessarily improve the density estimate with small samples. Of the global bandwidth estimators compared, we found that MLCV and LSCV are better because they show lower variability and higher accuracy while Biased Cross Validation suffers from multiple optimal bandwidths for samples from strongly bimodal densities. These results, of particular interest in stochastic hydrology where small samples are common, may have importance in other applications of nonparametric density estimation methods with similar sample sizes and distribution shapes.
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    Stochastic environmental research and risk assessment 12 (1998), S. 15-32 
    ISSN: 1436-3259
    Keywords: Key words: Kalman filtering ; groundwater modelling ; inverse methods ; uncertainty analysis ; state prediction ; parameter estimation
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    Notes: Abstract The popularity of applying filtering theory in the environmental and hydrological sciences passed its first climax in the 1970s. Like so many other new mathematical methods it was simply the fashion at the time. The study of groundwater systems was not immune to this fashion, but neither was it by any means a prominent area of application. The spatial-temporal characteristics of groundwater flow are customarily described by analytical or, more frequently, numerical, physics-based models. Consequently, the state-space representations associated with filtering must be of a high order, with an immediately apparent computational over-burden. And therein lies part of the reason for the but modest interest there has been in applying Kalman filtering to groundwater systems, as reviewed critically in this paper. Filtering theory may be used to address a variety of problems, such as: state estimation and reconstruction, parameter estimation (including the study of uncertainty and its propagation), combined state-parameter estimation, input estimation, estimation of the variance-covariance properties of stochastic disturbances, the design of observation networks, and the analysis of parameter identifiability. A large proportion of previous studies has dealt with the problem of parameter estimation in one form or another. This may well not remain the focus of attention in the future. Instead, filtering theory may find wider application in the context of data assimilation, that is, in reconstructing fields of flow and the migration of sub-surface contaminant plumes from relatively sparse observations.
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    Stochastic environmental research and risk assessment 12 (1998), S. 65-82 
    ISSN: 1436-3259
    Keywords: Key words: Flood flow ; threshold ; generalized Pareto ; Poisson
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This study uses the method of peaks over threshold (P.O.T.) to estimate the flood flow quantiles for a number of hydrometric stations in the province of New Brunswick, Canada. The peak values exceeding the base level (threshold), or `exceedances', are fitted by a generalized Pareto distribution. It is known that under the assumption of Poisson process arrival for flood exceedances, the P.O.T. model leads to a generalized extreme value distribution (GEV) for yearly maximum discharge values. The P.O.T. model can then be applied to calculate the quantiles X T corresponding to different return periods T, in years. A regionalization of floods in New Brunswick, which consists of dividing the province into `homogeneous regions', is performed using the method of the `region of influence'. The 100-year flood is subsequently estimated using a regionally estimated value of the shape parameter of the generalized Pareto distribution and a regression of the 100-year flood on the drainage area. The jackknife sampling method is then used to contrast the regional results with the values estimated at site. The variability of these results is presented in box-plot form.
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    Stochastic environmental research and risk assessment 12 (1998), S. 97-116 
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    Notes: Abstract : The knowledge of the volume and duration of low-flow events in river channels is essential for water management and the design of hydraulics structures. In this study, both preceding characteristics, X 1 and X 2, are considered simultaneously via two types of bivariate distributions whose marginals are exponential. One of these bivariate distributions has been presented by Nagao and Kadoya (1971) and the other has been used by Singh and Singh (1991) to the study of rainfall intensity and rainfall depth. The results are applied to the low-flow series (“peaks-below-threshold”) of Lepreau River (station 01AQ001) in New Brunswick, Canada. These results show that the model that was successfully employed by Singh and Singh (1991) to study rainfall, presents certain difficulties when a very strong correlation, ρ, between the two random variables X 1 and X 2, exists. The model by Nagao and Kadoya (1971) seems to be more satisfactory for such situations, although this model seems also to be quite sensitive to variations in ρ.
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    Stochastic environmental research and risk assessment 12 (1998), S. 83-96 
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    Notes: Abstract Many natural porous geological rock formations, as well as engineered porous structures, have fractal properties, i.e., they are self-similar over several length scales. While there have been many experimental and theoretical studies on how to quantify a fractal porous medium and on how to determine its fractal dimension, the numerical generation of a fractal pore structure with predefined statistical and scaling properties is somewhat scarcer. In the present paper a new numerical method for generating a three-dimensional porous medium with any desired probability density function (PDF) and autocorrelation function (ACF) is presented. The well-known Turning Bands Method (TBM) is modified to generate three-dimensional synthetic isotropic and anisotropic porous media with a Gaussian PDF and exponential-decay ACF. Porous media with other PDF's and ACF's are constructed with a nonlinear, iterative PDF and ACF transformation, whereby the arbitrary PDF is converted to an equivalent Gaussian PDF which is then simulated with the classical TBM. Employing a new method for the estimation of the surface area for a given porosity, the fractal dimensions of the surface area of the synthetic porous media generated in this way are then measured by classical fractal perimeter/area relationships. Different 3D porous media are simulated by varying the porosity and the correlation structure of the random field. The performance of the simulations is evaluated by checking the ensemble statistics, the mean, variance and ACF of the simulated random field. For a porous medium with Gaussian PDF, an average fractal dimension of approximately 2.76 is obtained which is in the range of values of actually measured fractal dimensions of molecular surfaces. For a porous medium with a non-Gaussian quadratic PDF the calculated fractal dimension appears to be consistently higher and averages 2.82. The results also show that the fractal dimension is neither strongly dependent of the porosity nor of the degree of anisotropy assumed.
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    Stochastic environmental research and risk assessment 12 (1998), S. 117-140 
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    Notes: Abstract Transport of non-ergodic solute plumes by steady-state groundwater flow with a uniform mean velocity, μ, were simulated with Monte Carlo approach in a two-dimensional heterogeneous and statistically isotropic aquifer whose transmissivity, T, is log-normally distributed with an exponential covariance. The ensemble averages of the second spatial moments of the plume about its center of mass, 〈S i i (t)〉, and the plume centroid covariance, R i i (t) (i=1,2), were simulated for the variance of Y=log T, σ Y 2=0.1, 0.5 and 1.0 and line sources normal or parallel to μ of three dimensionless lengths, 1, 5, and 10. For σ Y 2=0.1, all simulated 〈S i i (t)〉−S i i (0) and R i i (t) agree well with the first-order theoretical values, where S i i (0) are the initial values of S i i (t). For σ Y 2=0.5 and 1.0 and the line sources normal to μ, the simulated longitudinal moments, 〈S 11(t)〉−S 11(0) and R 11(t), agree well with the first-order theoretical results but the simulated transverse moments 〈S 22(t)〉−S 22(0) and R 22(t) are significantly larger than the first-order values. For the same two larger values of σ Y 2 but the line sources parallel to μ, the simulated 〈S 11(t)〉−S 11(0) are larger than but the simulated R 11 are smaller than the first-order values, and both simulated 〈S 22(t)〉−S 22(0) and R 22(t) stay larger than the first-order values. For a fixed value of σ Y 2, the summations of 〈S i i (t)〉−S i i (0) and R i i , i.e., X i i (i=1,2), remain almost the same no matter what kind of source simulated. The simulated X 11 are in good agreement with the first-order theory but the simulated X 22 are significantly larger than the first-order values. The simulated X 22, however, are in excellent agreement with a previous modeling result and both of them are very close to the values derived using Corrsin's conjecture. It is found that the transverse moments may be significantly underestimated if less accurate hydraulic head solutions are used and that the decreasing of 〈S 22(t)〉−S 22(0) with time or a negative effective dispersivity, defined as , may happen in the case of a line source parallel to μ where σ Y 2 is small.
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    Stochastic environmental research and risk assessment 12 (1998), S. 141-154 
    ISSN: 1436-3259
    Keywords: Key words: Ground truth ; geostatistical techniques ; areal reduction factor ; Rainfall process ; linear relationship.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Geostatistical techniques are used to quantify the reference mean areal rainfall (ground truth) from sparse raingaugenetworks. Based on the EPSAT-Niger event cumulative rainfall, a linear relationship between the ground truth considered as the mean area rainfall estimated from the densely available raingauge network and the area rainfall estimated from sparse network are derived. Also, a linear relationship between the ground truth and point rainfall is established. As it was reported experimentally by some authors, the slope of these relationships is less than one. Based on the geostatistical framework, the slope and the ordinate at the origin can be estimated as a function of the spatial structure of the rainfall process. It is shown that the slope is smaller than one. For the special case of one gauge inside a fixed area or a Field Of View (FOV), an areal reduction factor is derived. It has a limit value which depends only on the size of the area and the spatial structure of the rainfall process. The relative variance error of estimating the FOV cumulative rainfall from point rainfall is also given.
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    Stochastic environmental research and risk assessment 12 (1998), S. 223-245 
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    Keywords: Key words: Stochastic differential equation ; spatial data ; irregularly sampled data ; parameter estimation.
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    Notes: Abstract: A second order stochastic differential equation is used for modeling of water-table elevation. The data were sampled at the Borden Aquifer as a part of a tracer experiment. The purpose of the water-table data collection was to determine presence of a water flow. We argue that the water-table surface is a simple plane oscillating up and down in time according to an equation for a stochastic oscillator. We derive the model, estimate its parameters and provide arguments for goodness-of-fit of the model.
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    Stochastic environmental research and risk assessment 12 (1998), S. 267-283 
    ISSN: 1436-3259
    Keywords: Key words: Flood frequency analysis ; TCEV ; non-systematic information ; regional ; statistical gain.
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    Notes: Abstract: Due to the social and economic implications, flood frequency analysis must be done with the highest precision. For this reason, the most suitable statistical model must be selected, and the maximum amount of information must be used. Floods in Mediterranean rivers can be produced by two different mechanisms, which forces the use of a non-traditional distribution like the TCEV. The information can be increased by using additional non-systematic data, or with a regional analysis, or both. Through the statistical gain concept, it has been shown that in most cases the use of additional non-systematic information can decrease the quantile estimation error in about 50%. In a regional analysis, the␣benefit of additional information in one station, is propagated to the rest of␣the␣stations with only a small decrease with respect to the at-site equivalent analysis.
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    Stochastic environmental research and risk assessment 12 (1998), S. 285-298 
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    Notes: Abstract We present a geostatistically based inverse model for characterizing heterogeneity in parameters of unsaturated hydraulic conductivity for three-dimensional flow. Pressure and moisture content are related to perturbations in hydraulic parameters through cross-covariances, which are calculated to first-order. Sensitivities needed for covariance calculations are derived using the adjoint state sensitivity method. Approximations of the conditional mean parameter fields are then obtained from the cokriging estimator. Correlation between parameters and pressure – moisture content perturbations is seen to be strongly dependent on mean pressure or moisture content. High correlation between parameters and pressure data was obtained under saturated or near saturated flow conditions, providing accurate estimation of saturated hydraulic conductivity, while moisture content measurements provided accurate estimation of the pore size distribution parameter under unsaturated flow conditions.
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    Stochastic environmental research and risk assessment 12 (1998), S. 247-266 
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    Keywords: Key words: Stochastic control ; dynamic programming ; reservoir systems ; hydrologic forecasting ; hydropower ; feedback control ; autoregressive models.
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    Notes: Abstract : As with all dynamic programming formulations, differential dynamic programming (DDP) successfully exploits the sequential decision structure of multi-reservoir optimization problems, overcomes difficulties with the nonconvexity of energy production functions for hydropower systems, and provides optimal feedback release policies. DDP is particularly well suited to optimizing large-scale multi-reservoir systems due to its relative insensitivity to state-space dimensionality. This advantage of DDP encourages expansion of the state vector to include additional multi-lag hydrologic information and/or future inflow forecasts in developing optimal reservoir release policies. Unfortunately, attempts at extending DDP to the stochastic case have not been entirely successful. A modified stochastic DDP algorithm is presented which overcomes difficulties in previous formulations. Application of the algorithm to a four-reservoir hydropower system demonstrates its capabilities as an efficient approach to solving stochastic multi-reservoir optimization problems. The algorithm is also applied to a single reservoir problem with inclusion of multi-lag hydrologic information in the state vector. Results provide evidence of significant benefits in direct inclusion of expanded hydrologic state information in optimal feedback release policies.
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    Stochastic environmental research and risk assessment 12 (1998), S. 299-316 
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    Notes: Abstract This paper presents a geostatistical approach to multi-directional aquifer stimulation in order to better identify the transmissivity field. Hydraulic head measurements, taken at a few locations but under a number of different steady-state flow conditions, are used to estimate the transmissivity. Well installation is generally the most costly aspect of obtaining hydraulic head measurements. Therefore, it is advantageous to obtain as many informative measurements from each sampling location as possible. This can be achieved by hydraulically stimulating the aquifer through pumping, in order to set-up a variety of flow conditions. We illustrate the method by applying it to a synthetic aquifer. The simulations provide evidence that a few sampling locations may provide enough information to estimate the transmissivity field. Furthermore, the innovation of, or new information provided by, each measurement can be examined by looking at the corresponding spline and sensitivity matrix. Estimates from multi-directional stimulation are found to be clearly superior to estimates using data taken under one flow condition. We describe the geostatistical methodology for using data from multi-directional simulations and address computational issues.
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    Stochastic environmental research and risk assessment 9 (1995), S. 33-47 
    ISSN: 1436-3259
    Keywords: Hidden markov models ; maximum likelihood estimation ; EM algorithm ; martingale estimating function ; forward-backward algorithm ; Monte Carlo ; filtering ; Nash cascade model ; rainfall runoff modeling
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n ≥ 0) or (Xt, t ≥ 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n ≥ 0) or (Yt, t ≥ 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.
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    Stochastic environmental research and risk assessment 9 (1995), S. 117-132 
    ISSN: 1436-3259
    Keywords: River Quality ; network ; computer model ; Thermodynamics
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    Notes: Abstract In this paper, concepts of network thermodynamics are applied to a river water quality model, which is based on Streeter-Phelps equations, to identify the corresponding physical components and their topology. Then, the randomness in the parameters, input coefficients and initial conditions are modeled by Gaussian white noises. From the stochastic components of the physical system description of problem and concepts of physical system theory, a set of stochastic differential equations can be automatically generated in a computer and the recent developments on the automatic formulation of the moment equations based on Ito calculus can be used. This procedure is illustrated through the solution of an example of stochastic river water quality problem and it is also shown how other related problems with different configurations can be automatically solved in a computer using just one software.
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    Stochastic environmental research and risk assessment 9 (1995), S. 171-205 
    ISSN: 1436-3259
    Keywords: AR-AIC-Bayes filter ; autoregressive spectral density estimation ; diagnostic checks for ARMA models ; exploratory data analysis ; fast Fourier transform ; Hurst coefficient ; long-memory times series ; periodogram smoothing ; riverflow time series ; spectral density plots
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract 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.
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    Stochastic environmental research and risk assessment 9 (1995), S. 215-237 
    ISSN: 1436-3259
    Keywords: Computation ; discretization ; entropy ; networks ; time averaging ; water quality
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The computational aspects of using a new, entropy-based, theory to predict water quality values at discontinued water quality monitoring stations are discussed. The main computational issues addressed are the level of discretization used in converting the continuous probability distribution of water quality values to the discrete levels required for the entropy function, and the choice of the interval of time for which to assign the value of the water quality (period of time averaging) through the entropy function. Unlike most cases of entropy applications involving discretization of continuous functions the results of using entropy theory to predict water quality values at discontinued monitoring stations in this application appear to be insensitive to the choice of the level of discretization even down to the very coarse level discretization associated with only eight intervals. However, depending on the length of record available the choice of the time interval for which the water quality values are assigned (period for time averaging) appear to have a significant impact on the accuracy of the results.
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    Stochastic environmental research and risk assessment 9 (1995), S. 13-32 
    ISSN: 1436-3259
    Keywords: Distributed parameter filter ; shallow water equations ; distributed dynamical systems ; data assimilation ; white Gaussian noise
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Distributed parameter filtering theory is employed for estimating the state variables and associated error covariances of a dynamical distributed system under highly random tidal and meteorological influences. The stochastic-deterministic mathematical model of the physical system under study consists of the shallow water equations described by the momentum and continuity equations in which the external forces such as Coriolis force, wind friction, and atmospheric pressure are considered. White Gaussian noises in the system and measurement equations are used to account for the inherent stochasticity of the system. By using an optimal distributed parameter filter, the information provided by the stochastic dynamical model and the noisy measurements taken from the actual system are combined to obtain an optimal estimate of the state of the system, which in turn is used as the initial condition for the prediction procedure. The approach followed here has numerical approximation carried out at the end, which means that the numerical discretization is performed in the filtering equations, and not in the equations modelling the system. Therefore, the continuous distributed nature of the original system is maintained as long as possible and the propagation of modelling errors in the problem is minimized. The appropriateness of the distributed parameter filter is demonstrated in an application involving the prediction of storm surges in the North Sea. The results confirm excellent filter performance with considerable improvement with respect to the deterministic prediction.
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    Stochastic environmental research and risk assessment 9 (1995), S. 77-88 
    ISSN: 1436-3259
    Keywords: Extreme rainfalls ; partial duration series ; regional estimation ; Bayes' theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Based on the Partial Duration Series model a regional Bayesian approach is introduced in the modelling of extreme rainfalls from a country-wide system of recording raingauges in Denmark. The application of the Bayesian principles is derived in case of both exponential and generalized Pareto-distributed exceedances. The method is applied to, respectively, the total precipitation depth and the maximum 10 minutes rain intensity of individual storms from 41 stations. By means of the regional analysis prior distributions of the parameters in the Partial Duration Series model are estimated. It is shown that the regional approach significantly reduces the uncertainty of the T-year event estimator compared to estimation based solely on at-site data. In addition, the regional approach provides quantile estimates at non-monitored sites.
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    Journal of geographical systems 1 (1999), S. 277-303 
    ISSN: 1435-5949
    Keywords: Key words: Higher education ; geodemographics ; participation rates ; JEL classification: C80 ; I21 ; I28 ; J11
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. Higher education in England has expanded rapidly in the last ten years with the result that currently more than 30% of young people go on to university. Expansion is likely to continue following the recommendations of a national committee of inquiry (the Dearing Committee). The participation rate is known to vary substantially among social groups and between geographical areas. In this paper the participation rate is calculated using a new measure, the Young Entrants Index (YEI), and the extent of variation by region, gender and residential neighbourhood type established. The Super Profiles geodemographic system is used to facilitate the latter. This is shown to be a powerful discriminator and to offer great potential as an alternative analytical approach to the conventional social class categories, based on parental occupation, that have formed the basis of most participation studies to date.
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    Journal of geographical systems 1 (1999), S. 305-321 
    ISSN: 1435-5949
    Keywords: Key words: GIS, urban systems model, land use – transportation model, traffic analysis zone ; JEL classification: R11, R14, R41
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. The main purpose of this paper is to explore a possible integration for the entire transportation modeling procedure – from data inventory to future demand forecasting – by implementing integrated land use and transportation models with a geographic information system (GIS). In order to make an integrated, procedural modeling system possible, Land Use and Transportation modeling system with GIS (LUTGIS) has been developed and presented in this paper.  There are four sub-systems in LUTGIS: (1) a data inventory system, (2) a traffic analysis zone generation system, (3) an integrated land use and transportation modeling system, and (4) a graphic user interface (GUI) system. Since the main target of this paper is to explore a possible way to create a viable system, LUTGIS integrates currently available and user-friendly computing technologies. For both transportation planners and administrative decision-makers, such an operable system is very desirable for sharing information so they may arrive at a consensus through the use of LUTGIS, an integrated land use and transportation modeling system.
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    Topics: Geography , Economics
    Notes: Abstract In this paper, we investigate the role of input-output data sources in regional econometric input-output models. While there has been a great deal of experimentation focused on the accuracy of alternative methods for estimating regional inputoutput coefficients, little attention has been directed to the role of accuracy when the input-output system is nested within a broader accounting framework. The issues of accuracy were considered in two contexts, forecasting and impact analysis focusing on a model developed for the Chicago region. We experimented with three input-output data sources: observed regional data, national input-output, and randomly generated inputoutput coefficients. The effects of different sources of input-output data on regional econometric input-output models revealed that there are significant differences in results obtained in both forecast and impact analyses. The adjustment processes inherent in the econometric input-output system did not mask the differences imbedded in input-output tables derived from different data sources. Since applications of these types of models involve both impact and forecasting exercises, there should be strong motivation for basing the syste on the most accurate set of input-output accounts.
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    Papers in regional science 75 (1996), S. 177-199 
    ISSN: 1435-5957
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    Topics: Geography , Economics
    Notes: Abstract Japan National Railways went private in 1987, the first of many national railways to do so, and the Japanese experience could provide lessons to other nations. This paper evaluates the effects of Japan National Railways' Privatization on labor productivity and employment in the passenger sectors. The main data was obtained from the Annual Rail Statistics of both the Ministry of Transport and Japan National Railways. Quantitative methods such as labor productivity models were used to evaluate the effects of privatization. Large private railways, which are considered the most efficient railways in Japan, are often compared to privatized Japan Railways. Major findings are as follows: First, Japan Railways still have 20% more employees than large private railways. Second, current productivity differences between Japan Railways and large private railways appear in station and maintenance activities. Third, reduction in employment during the transitional periods of privatization greatly contributed to increases in the productivity of Japan Railways. Fourth, it is not clear whether or not productivity differences among regional Japan Railways have been decreasing since privatization. Finally, the effect of privatization on productivity growth was about 29%. Moreover, even if productivity increases, safety is not compromised, with serious accidents clearly being unrelated to productivity growth.
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    Papers in regional science 75 (1996), S. 433-440 
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    Topics: Geography , Economics
    Notes: Abstract This paper explicitly incorporates monopsony market structure into the Weber-Moses's one-output, two-input triangular location model and reexamines the location invariance principle. It will be shown that this principle need not hold if the imperfection of input markets prevails. This is contrary to the conventional wisdom.
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    Papers in regional science 75 (1996), S. 135-153 
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    Topics: Geography , Economics
    Notes: Abstract The relationship between urbanization and level of income has been the subject of considerable theoretical debate and empirical study for many years. However, little recent work has been done to determine whether or not previous findings still hold, and there has been even less multi-country analysis to explore the degree of generality. Analysis of data for metropolitan areas in the United States from 1970 to 1990 indicates per capita income increases directly with population size. For states of the United States and 113 countries for 1960 and 1980 a strong positive relationship exists and holds temporally between level of per capita Gross Domestic Product and percent of the population that is urban.
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    Papers in regional science 75 (1996), S. 201-235 
    ISSN: 1435-5957
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    Topics: Geography , Economics
    Notes: Abstract Foreign direct investment in the United States is an integral part of the competition among global industrial core regions. Most foreign investment in the U.S. originates in Europe, Canada, and Japan. Acquisition rather than new plant establishment is the favored mode of investment and the interregional supply of potential acquisition candidates constrains foreign investors' locational choices. This paper provides an analysis of the location of foreign employment in 15 disaggregated sectors across U.S. states in 1990. The results show that foreign firms concentrate employment in existing regions of production. Foreign investments in most raw materials processing sectors particularly favor these places. Some decentralization has occurred in several sectors, especially food, paper, chemicals and petroleum, rubber and plastics, stone, clay and glass products, and primary metals. Other significant determinants of location include labor force characteristics and certain regional preferences. No evidence was found in our analysis of disaggregate sectors that foreign investors avoid strong unions more than their domestic counterparts.
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    Papers in regional science 75 (1996), S. 265-291 
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    Topics: Geography , Economics
    Notes: Abstract Drawing from flexible production literature on industrial networks, this research pays particular attention to the socially embedded nature of firm linkages in a distribution sector. The empirical study of Chinese-owned computer wholesale firms within Los Angeles County shows that the presence of ethnic identity plays a significant role in the internal operation and external transactions of Chinese firms. Ethnic relations facilitate interactions within the ethnic group, producing a closely knit ethnic network within the industry. The heavy reliance on ethnic networks also has led Chinese firms to a notable geographical separation from the remaining firms in the same sector.
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    Papers in regional science 75 (1996), S. 351-374 
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    Topics: Geography , Economics
    Notes: Abstract Producer services employment has grown rapidly within advanced economies in recent years. The bases of demand related to this growth are not well understood by regional scientists. A common view is that this growth is largely attributable to cost-driven factors and vertical disintegration processes on the part of producer service users. This paper demonstrates that cost-driven externalization is not the most important force underlying growth in demand for producer services. The need for specialized knowledge is by far the most important factor behind producer services demand, combined with a variety of other cost, quasi-cost, and non-cost-driven forces.
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    Papers in regional science 75 (1996), S. 463-481 
    ISSN: 1435-5957
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    Topics: Geography , Economics
    Notes: Abstract This paper focuses on the dynamic relations between Spain's principal regional labor markets. An economic base mechanism, some of whose assumptions are redefined, is postulated as the essential behavior hypothesis. The bifurcation hypothesis is resolved having regard to the necessary condition of cointegration between the basic sector and the regional aggregate, using series with quarterly periodicity in this case. The identified bases, which need not coincide in each region, allow a dynamic inter-regional model to be built using vector autoregression with an error correction mechanism. The results are a step towards the spatial disaggregation of Spain's labor market and reveal singular dynamic relationships.
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    Papers in regional science 75 (1996), S. 501-524 
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    Topics: Geography , Economics
    Notes: Abstract This paper aims at positioning spatial development at the crossroads of the conflicting needs for spatial mobility and spatial sustainability. Such tensions have explicitly been recognized in recent local, national and international policy documents. A reconciliation of such antagonistic driving forces in our modern network economy requires a solid theoretical framework in which the relevant force fields are depicted and in which the uncertainties inherent in any attempt at steering human behavior in space are explicitly recognized. This requires an analytical framework in which relevant scenarios are systematically projected on a model structure describing the above mentioned force field. This paper will try to offer an operational methodology for coping with the above mentioned conflicting issues in planning for sustainable spatial development. Particular attention will be given to the spatial scale of analyzing sustainable development. The methodology will be illustrated by presenting empirical results from a case study undertaken in the western part of the Netherlands, the so called Randstad.
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    Papers in regional science 78 (1999), S. 21-45 
    ISSN: 1435-5957
    Keywords: JEL classification: C52, R10, R12, R14, R39 ; Key words:New economic geography, spatial statistics, spatial modeling, methodology
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    Topics: Geography , Economics
    Notes: Abstract. Krugman states that “Regional science is not a unified subject. It is best described as a collection of tools.” Unfortunately such a perspective fails to fully acknowledge theoretical dimensions of the accompanying refocusing on geographic expressions of economic linkages, such as those highlighted in spatial externalities specifications. Such promulgated aspects of the spatial economic landscape relate to map pattern, and certainly the spatial statistics and spatial econometrics theory that accompanies it, as well as the underlying substantive theory garnered from a variety of sources. The principal implication is other than “loose- jointed, do-the-best-you-can theorizing”.
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    Papers in regional science 78 (1999), S. 111-116 
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    Papers in regional science 78 (1999), S. 117-118 
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    Papers in regional science 78 (1999), S. 157-177 
    ISSN: 1435-5957
    Keywords: JEL classification: R1, R12 ; Key words:Central place theory, choice rules, generalised Voronoi diagrams, market areas
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    Topics: Geography , Economics
    Notes: Abstract. Although a variety of modifications of classical central place theory has been proposed, one area that remains unexplored is the effect of relaxing the nearest centre assumption for the purchase of a specified basket of goods within a given hierarchical level. This article examines the effect of such a relaxation on central place market areas by using higher-order Voronoi diagrams. When used to model market areas, higher-order Voronoi diagrams can be interpreted as overlapping and probabilistic regions. These diagrams construct market areas based on the assumption that consumers choose from a set of $k (k = 1, 2, \ldots, n)$ nearest centres of the same hierarchical level. If consumers are assumed to be indifferent between the k centres, the appropriate market areas are given by the order-k Voronoi diagram. In this case, it is shown that sales potentials are consistent with those that result when the nearest centre assumption is in effect. If consumers are assumed to have a preference for nearer centres, market areas are defined by the ordered, order-k Voronoi diagram. This situation generates sales potentials which can vary between centres.
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    Stochastic environmental research and risk assessment 11 (1997), S. 51-63 
    ISSN: 1436-3259
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A basic problem in hydrology is computing confidence levels for the value of the T-year flood when it is obtained from a Log Pearson III distribution in terms of estimated mean, estimated standard deviation, and estimated skew. In an important paper Chowdhury and Stedinger [1991] suggest a possible formula for approximate confidence levels, involving two functions previously used by Stedinger [1983] and a third function, λ, for which asymptotic estimates are given. This formula is tested [Chowdhury and Stedinger, 1991] by means of simulations, but these simulations assume a distribution for the sample skew which is not, for a single site, the distribution which the sample skew is forced to have by the basic hypothesis which underlies all of the analysis, namely that the maximum discharges have a Log Pearson III distribution. Here we test these approximate formulas for the case of data from a single site by means of simulations in which the sample skew has the distribution which arises when sampling from a Log Pearson III distribution. The formulas are found to be accurate for zero skew but increasingly inaccurate for larger common values of skew. Work in progress indicates that a better choice of λ can improve the accuracy of the formula.
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    Stochastic environmental research and risk assessment 11 (1997), S. 94-94 
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    Stochastic environmental research and risk assessment 11 (1997), S. 95-114 
    ISSN: 1436-3259
    Keywords: Soil moisture ; time scale ; non-Gaussian ; colored-noise
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Large-scale fields of soil moisture are forced by atmospheric precipitation and radiative forcing. When these forcing factors are themselves influenced by surface and soil moisture processes, the result is a nonlinear land-atmosphere system with inherent feedback mechanisms that may strongly modulate variability in climate. Given such feedbacks, simple randomness in the forcing factors may be manifested as a complex statistical signature in the surface hydrology. In this paper, we investigate the impacts of non-Gaussian and colored-noise on the probability distribution of soil moisture resulting from the statistical-dynamical land-atmosphere interaction model of Rodriguez-Iturbe et al. (1991). Persistence of hydroclimatologic anomalies as characterized by the correlation time scale of soil moisture is discussed.
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    Stochastic environmental research and risk assessment 11 (1997), S. 115-127 
    ISSN: 1436-3259
    Keywords: Rainfall-runoff modeling ; transfer response ; dynamic non-linear models ; normal and gamma observational distribution ; predictive performance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The rainfall-runoff modeling is very useful for forecasting purposes. A good methodology for forecasting the future stream flow is a key requirement for designers and operators of water resources systems. A compromise between conceptual and classical time series modeling is applied to model the relationship between rainfall and runoff. The dynamic nonlinear model is composed of a probability distribution describing the observation, a link function relating its mean to the so called state parameters and a system of equations defining the evolution of these parameters. Its Bayesian nature permits to take into account subjective information, making forward intervention, defining monitoring schemes and introducing smoothing facilities. An application using the data of Fartura river's basin is reported. The assessment of the prior distribution is discussed and the predictive performance of the linear and the non-linear models is reported.
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    Stochastic environmental research and risk assessment 11 (1997), S. 129-143 
    ISSN: 1436-3259
    Keywords: Stochastic analysis ; perturbation methods ; unsaturated transport ; heterogeneous porous media
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    Notes: Abstract Within the framework of stochastic theory and the spectral perturbation techniques, three-dimensional dispersion in partially saturated soils with a finite correlation scale of log-hydraulic conductivity is analyzed. The effects of spatial variability of the moisture distribution parameter on the asymptotic spreading behavior of a unsaturated solute plume are assessed. This is accomplished by comparing two asymptotic macrodispersivities and two variance of solute concentration, obtained for a constant moisture content and spatially varied moisture, respectively.
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    Stochastic environmental research and risk assessment 11 (1997), S. 65-93 
    ISSN: 1436-3259
    Keywords: Nonparametric ; Monte Carlo ; precipitation ; weather
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    Notes: Abstract A nonparametric resampling technique for generating daily weather variables at a site is presented. The method samples the original data with replacement while smoothing the empirical conditional distribution function. The technique can be thought of as a smoothed conditional Bootstrap and is equivalent to simulation from a kernel density estimate of the multivariate conditional probability density function. This improves on the classical Bootstrap technique by generating values that have not occurred exactly in the original sample and by alleviating the reproduction of fine spurious details in the data. Precipitation is generated from the nonparametric wet/dry spell model as described in Lall et al. [1995]. A vector of other variables (solar radiation, maximum temperature, minimum temperature, average dew point temperature, and average wind speed) is then simulated by conditioning on the vector of these variables on the preceding day and the precipitation amount on the day of interest. An application of the resampling scheme with 30 years of daily weather data at Salt Lake City, Utah, USA, is provided.
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    Stochastic environmental research and risk assessment 11 (1997), S. 255-266 
    ISSN: 1436-3259
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract It has been observed that the field biodegradation rates for soluble hydrocarbon plumes are significantly smaller than the aerobic rates observed in the laboratory. It is believed that this difference is related to the fact that in the field oxygen and hydrocarbon must be mixed before the biodegradation reaction can occur, and that the effective degradation rate is controlled by the actual, not mean, concentrations of oxygen and hydrocarbon. In this work, we present a conceptual model of oxygen-mixing limited biodegradation, which indicates that the effective degradation rate should depend on the cross correlation between the oxygen and hydrocarbon concentration fluctuations. This is followed by a development of a rigorous, field-scale model.
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    Stochastic environmental research and risk assessment 11 (1997), S. 229-254 
    ISSN: 1436-3259
    Keywords: Model validation ; analysis of uncertainty ; model verification ; quality assurance ; system identification ; model calibration
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The development and use of models for predicting exposures are increasingly common and are essential for many risk assessments of the United States Environmental Protection Agency (EPA). Exposure assessments conducted by the EPA to assist regulatory or policy decisions are often challenged to demonstrate their “scientific validity”. Model validation has thus inevitably become a major concern of both EPA officials and the regulated community, sufficiently so that the EPA's Risk Assessment Forum is considering guidance for model validation. The present paper seeks to codify the issues and extensive foregoing discussion of validation with special reference to the development and use of models for predicting the impact of novel chemicals on the environment. Its preparation has been part of the process in formulating a White Paper for the EPA's Risk Assessment Forum. Its subject matter has been drawn from a variety of fields, including ecosystem analysis, surface water quality management, the contamination of groundwaters from high-level nuclear waste, and the control of air quality. The philosophical and conceptual bases of model validation are reviewed, from which it is apparent that validation should be understood as a task of product (or tool) design, for which some form of protocol for quality assurance will ultimately be needed. The commonly used procedures and methods of model validation are also reviewed, including the analysis of uncertainty. Following a survey of past attempts at resolving the issue of model validation, we close by introducing the notion of a model having maximum relevance to the performance of a specific task, such as, for example, a predictive exposure assessment.
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    Stochastic environmental research and risk assessment 11 (1997), S. 303-321 
    ISSN: 1436-3259
    Keywords: Simulation ; hydrograph rise and recession ; rainfall process ; probability distribution
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A model is developed for annual low flow hydrographs. Its two primary components reflect the fact that hydrologic processes during streamflow rise (function of water input) and recession (function of basin storage) are different. Durations of periods of rise (wet intervals) and recession (dry intervals) are modelled by discrete probability distributions — negative binomial for dry intervals and negative binomial or modified logarithmic series for wet intervals depending on goodness of fit. During wet intervals, the total inflow is modelled by the lognormal distribution and daily amounts are allocated according to a pattern-averaged model. During dry intervals, the flow recedes according to a deterministic-stochastic recession model. The model was applied to three Canadian basins with drainage area ranging from 2210 to 22000 km2 to generate 50 realizations of low flow hydrographs. The resulting two standard-error confidence band for the simulated probability distribution of annual minimum 7-day flows enclosed the probability distribution estimated from the observed record. A sensitivity analysis for the three basins revealed that in addition to the recession submodel, the most important submodel is that describing seasonality. The state of the basin at the beginning of the low flow period is of marginal importance and the daily distribution of input is unimportant.
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    Stochastic environmental research and risk assessment 11 (1997), S. 267-295 
    ISSN: 1436-3259
    Keywords: Space/time processes ; stochastic analysis ; regression model ; solute contents
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract A regression model is used to study spatiotemporal distributions of solute content ion concentration data (calcium, chloride and nitrate), which provide important water contamination indicators. The model consists of three random and one deterministic components. The random space/time component is assumed to be homogeneous/stationary and to have a separable covariance. The purely spatial and the purely temporal random components are assumed to have homogenous and stationary increments, respectively. The deterministic component represents the space/time mean function. Inferences of the random components involve maximum likelihood and semi-parametric methods under some restrictions on the data configuration. Computational advantages and modelling limitations of the assumptions underlying the regression model are discussed. The regression model leads to simplifications in the space/time kriging and cokriging systems used to obtain space/time estimates at unobservable locations/instants. The application of the regression model in the study of the solute content ions was done at a global scale that covers the entire region of interest. The variability analysis focuses on the calculation of the spatial direct and cross-variograms and the evaluation of correlations between the three solute content ions. The space/time kriging system is developed in terms of the space direct and cross-variograms, and allows the separate estimation of the regression model components. Maps of these components are then obtained for each one of the three ions. Using the estimates of the purely spatial component, spatial dependencies between the ions are studied. Physical causes and consequences of the space/time variability are discussed, and comparisons are made with previous analyses of the solute content dataset.
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    Stochastic environmental research and risk assessment 11 (1997), S. 323-330 
    ISSN: 1436-3259
    Keywords: Kolmogorov-Smirnov test ; identification of periodic component ; goodness-of-fit test for white noise ; periodogram ; residuals
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    Notes: Abstract A modified version of the widely used Kolmogorov-Smirnov (K-S) test of null hypothesis is constructed, that a given time series is Gaussian white noise, against the alternative hypothesis that the time series contains an added or multiplicative deterministic-periodic component of unspecified frequency. The usual KS test is treated as a special case. The proposed test is more powerful than the ordinary K-S test in detecting extreme (low or high) hidden periodicities. Computational procedure necessary for implementation are also given.
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    Stochastic environmental research and risk assessment 11 (1997), S. 297-302 
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    Keywords: Perturbation ; conservative chemical ; velocity variance ; eulerian
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    Notes: Abstract A recursive perturbation solution to the eulerian transport problem for a conservative solute in a random conductivity field is reported. The stochastic concentration is given to arbitrary order inσ ν, the variance of fluctuating velocity. The result gives the stochastic concentration as a perturbation to the deterministic concentration for constant mean flow. The closed form solution is easy to implement numerically via FFT.
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    Stochastic environmental research and risk assessment 11 (1997), S. 331-348 
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    Notes: Abstract Under the assumption that local solute dispersion is negligible, a new general formula (in the form of a convolution integral) is found for the arbitrary k-point ensemble moment of the local concentration of a solute convected in arbitrary m spatial dimensions with general sure initial conditions. From this general formula new closed-form solutions in m=2 spatial dimensions are derived for 2-point ensemble moments of the local solute concentration for the impulse (Dirac delta) and Gaussian initial conditions. When integrated over an averaging window, these solutions lead to new closed-form expressions for the first two ensemble moments of thevolume-averaged solute concentration and to the corresponding concentration coefficients of variation (CV). Also, for the impulse (Dirac delta) solute concentration initial condition, the second ensemble moment of thesolute point concentration in two spatial dimensions and the corresponding CV are demonstrated to be unbound. For impulse initial conditions the CVs for volume-averaged concentrations axe compared with each other for a tracer from the Borden aquifer experiment. The point-concentration CV is unacceptably large in the whole domain, implying that the ensemble mean concentration is inappropriate for predicting the actual concentration values. The volume-averaged concentration CV decreases significantly with an increasing averaging volume. Since local dispersion is neglected, the new solutions should be interpreted as upper limits for the yet to be derived solutions that account for local dispersion; and so should the presented CVs for Borden tracers. The new analytical solutions may be used to test the accuracy of Monte Carlo simulations or other numerical algorithms that deal with the stochastic solute transport. They may also be used to determine the size of the averaging volume needed to make a quasi-sure statement about the solute mass contained in it.
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    Stochastic environmental research and risk assessment 11 (1997), S. 349-368 
    ISSN: 1436-3259
    Keywords: Data assimilation ; Kalman filter ; Square root filter
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The Kalman filter algorithm can be used for many data assimilation problems. For large systems, that arise from discretizing partial differential equations, the standard algorithm has huge computational and storage requirements. This makes direct use infeasible for many applications. In addition numerical difficulties may arise if due to finite precision computations or approximations of the error covariance the requirement that the error covariance should be positive semi-definite is violated. In this paper an approximation to the Kalman filter algorithm is suggested that solves these problems for many applications. The algorithm is based on a reduced rank approximation of the error covariance using a square root factorization. The use of the factorization ensures that the error covariance matrix remains positive semi-definite at all times, while the smaller rank reduces the number of computations and storage requirements. The number of computations and storage required depend on the problem at hand, but will typically be orders of magnitude smaller than for the full Kalman filter without significant loss of accuracy. The algorithm is applied to a model based on a linearized version of the two-dimensional shallow water equations for the prediction of tides and storm surges. For non-linear models the reduced rank square root algorithm can be extended in a similar way as the extended Kalman filter approach. Moreover, by introducing a finite difference approximation to the Reduced Rank Square Root algorithm it is possible to prevent the use of a tangent linear model for the propagation of the error covariance, which poses a large implementational effort in case an extended kalman filter is used.
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    Stochastic environmental research and risk assessment 11 (1997), S. 369-395 
    ISSN: 1436-3259
    Keywords: Random fields ; diagrams ; perturbation ; non-local ; effective conductivity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This work presents a stochastic diagrammatic theory for the calculation of the effective hydraulic conductivity of heterogeneous media. The theory is based on the mean-flux series expansion of a log-normal hydraulic conductivity medium in terms of diagrammatic representations and leads to certain general results for the effective hydraulic conductivity of three-dimensional media. A selective summation technique is used to improve low-order perturbation analysis by evaluating an infinite set of diagrammatic terms with a specific topological structure that dominates the perturbation series. For stochastically isotropic media the selective summation yeilds the anticipated exponential expression for the effective hydraulic conductivity. This expression is extended to stochastically anisotropic media. It is also shown that in the case of non homogeneous media the uniform effective hydraulic conductivity is replaced by a non-local tensor kernel, for which general diagrammatic expressions are obtained. The non-local kernel leads to the standard exponential behavior for the effective hydraulic conductivity at the homogeneous limit.
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  • 78
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    Stochastic environmental research and risk assessment 11 (1997), S. 483-510 
    ISSN: 1436-3259
    Keywords: Conceptual-stochastic models ; shot noise ; streamflow simulation ; time aggregation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract 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.
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    Stochastic environmental research and risk assessment 11 (1997), S. 511-521 
    ISSN: 1436-3259
    Keywords: Runoff events ; arrival times ; partial duration series ; arid areas ; Israel ; probabilistic modeling ; Pearson III distribution
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Present descriptions of arrival times of runoff events are based upon modeling of interarrival intervals. Maintaining the traditional assumption that arrival times are independent random variables, these times can be directly described through a continuous distribution fitted to recorded data. A case study for the arid Negev region in Israel indicates that the Pearson type III distribution satisfactorily achieves this goal. The direct description can apply nonuniform functions, respond to multi-modal distributions, and be extended to regional modeling.
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  • 80
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    Stochastic environmental research and risk assessment 12 (1998), S. 155-170 
    ISSN: 1436-3259
    Keywords: Keywords: Stochastic inverse model ; conditioning ; transient groundwater flow.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract We investigated the effect of conditioning transient, two-dimensional groundwater flow simulations, where the transmissivity was a spatial random field, on time dependent head data. The random fields, representing perturbations in log transmissivity, were generated using a known covariance function and then conditioned to match head data by iteratively cokriging and solving the flow model numerically. A new approximation to the cross-covariance of log transmissivity perturbations with time dependent head data and head data at different times, that greatly increased the computational efficiency, was introduced. The most noticeable effect of head data on the estimation of head and log transmissivity perturbations occurred from conditioning only on spatially distributed head measurements during steady flow. The additional improvement in the estimation of the log transmissivity and head perturbations obtained by conditioning on time dependent head data was fairly small. On the other hand, conditioning on temporal head data had a significant effect on particle tracks and reduced the lateral spreading around the center of the paths.
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    Stochastic environmental research and risk assessment 12 (1998), S. 191-204 
    ISSN: 1436-3259
    Keywords: Keywords: groundwater flow ; inverse problems ; stability ; geostatistical interpolation ; kriging.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract The Differential System Method (DSM) permits identification of the physical parameters of finite-difference groundwater flow models in a confined aquifer when piezometric head and source terms are known at each point of the finite-difference lattice for at least two independent flow situations for which the hydraulic gradients are not parallel. Since piezometric head data are usually few and sparse, interpolation of the measured data onto a regular grid can be performed with geostatistical techniques. We apply kriging to the sparse data of a synthetic aquifer to evaluate the stability of the DSM with respect to uncorrelated measurement errors and interpolation errors. The numerical results show that the DSM is stable.
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  • 82
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    Stochastic environmental research and risk assessment 12 (1998), S. 171-190 
    ISSN: 1436-3259
    Keywords: Keywords: Self-Calibrated method ; Stochastic hydrology ; Conditional simulation ; Stochastic inversion.
    Source: Springer Online Journal Archives 1860-2000
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    Notes: Abstract: A common approach for the performance assessment of radionuclide migration from a nuclear waste repository is by means of Monte-Carlo techniques. Multiple realizations of the parameters controlling radionuclide transport are generated and each one of these realizations is used in a numerical model to provide a transport prediction. The statistical analysis of all transport predictions is then used in performance assessment. In order to reduce the uncertainty on the predictions is necessary to incorporate as much information as possible in the generation of the parameter fields. In this regard, this paper focuses in the impact that conditioning the transmissivity fields to geophysical data and/or piezometric head data has on convective transport predictions in a two-dimensional heterogeneous formation. The Walker Lake data based is used to produce a heterogeneous log-transmissivity field with distinct non-Gaussian characteristics and a secondary variable that represents some geophysical attribute. In addition, the piezometric head field resulting from the steady-state solution of the groundwater flow equation is computed. These three reference fields are sampled to mimic a sampling campaign. Then, a series of Monte-Carlo exercises using different combinations of sampled data shows the relative worth of secondary data with respect to piezometric head data for transport predictions. The analysis shows that secondary data allows to reproduce the main spatial patterns of the reference transmissivity field and improves the mass transport predictions with respect to the case in which only transmissivity data is used. However, a few piezometric head measurements could be equally effective for the characterization of transport predictions.
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  • 83
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    Stochastic environmental research and risk assessment 12 (1998), S. 205-222 
    ISSN: 1436-3259
    Keywords: Key words: Hale cycle ; luni-solar tidal constituent ; maximum entropy spectrum ; multi-taper method ; harmonic analysis.
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    Notes: Abstract: Cohen and Sweeter (1975) found the 20 to 22-year Hale (double sunspot) cycle signal in the maximum entropy spectra of sunspot and Atlantic tropical cyclone data. Currie (1996) corroborated and extended their analysis, but he argued that this signal is the 18.6-year luni-solar tidal constituent. Currie maintains that Cohen and Sweeter mistakenly conjectured that this long term periodicity was induced by the 20 to 22-year Hale cycle signal. However, no further investigation of periodicity in the extracted wave forms corresponding to the 18.6-year luni-solar signal was conducted. In this study, we follow Currie's signal processing procedures to extract the wave forms corresponding to the 18.6-year luni-solar signal. In order to investigate the periodicity in the extracted wave forms, multi-taper method (MTM) is used for harmonic analysis. Band pass filters are then designed to extract the wave forms corresponding to the individual components identified in the MTM harmonic analysis. The investigation results of the monthly precipitation and Palmer's drought severity index (PDSI) data in three of the midwestern states – Illinois, Indiana and Ohio – show that two periodic components, the 20 to 22-year Hale cycle signal and the other component with periods between 16.9 and 13.5 years, are identified. The bistability phenomenon, which Currie found in these wave forms, is more likely to result from the superposition of these two periodic components, rather than from a nonlinear mechanism. Besides, a periodic component with an approximate period of 33 years is detected.
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    Stochastic environmental research and risk assessment 9 (1995), S. 49-75 
    ISSN: 1436-3259
    Keywords: Flood frequency analysis ; index flood estimators ; L-moments ; GEV distribution ; regionalization ; probability weighted moments
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Our results illustrate the performance of at-site and regional GEV/PWM flood quantile estimators in regions with different coefficients of variation, degrees of regional heterogeneity, record lengths, and number of sites. Analytic approximations of bias and variance are employed. For realistic GEV distributions and short records, the index-flood quantile estimator performs better than a 2-parameter GEV/PWM quantile estimator with a regional shape parameter, or a 3-parameter at-site GEV/PWM quantile estimator, in both humid and especially in arid regions, as long as the degree of regional heterogeneity is moderate. As regional heterogeneity or record lengths increases, 2-parameter estimators quickly dominate. Flood frequency models that assign probabilities larger than 2% to negative flows are unrealistic; experiments employing such distributions provide questionable results. This appraisal generally demonstrates the value of regionalizing estimators of the shape of a flood distribution, and sometimes the coefficient of variation.
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  • 85
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    Stochastic environmental research and risk assessment 9 (1995), S. 105-116 
    ISSN: 1436-3259
    Keywords: Nonlocal ; transport ; dispersion ; heterogeneity ; integro-differential
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    Notes: Abstract Analysis from a number of different perspectives has shown diffusion and dispersion in natural porous formations to generally be nonlocal in character, i.e., the mass balance involves integro-partial differential equations. Only in certain asymptotic limits do these laws localize to classical partial differential equations. Compiled within is a resume of nonlocal laws that our group has developed over the last few years for systems with physical, chemical and biological heterogeneity. Analytical tools used to obtain these laws are nonequilibrium and equilibrium statistical mechanics, and first-order spectral-perturbation methods. This paper is an expansion of the material presented at the Waterloo conference held in the memory of Dr. Unny.
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    Stochastic environmental research and risk assessment 9 (1995), S. 133-149 
    ISSN: 1436-3259
    Keywords: moment-equations ; state-space ; numerical integration
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    Notes: Abstract The generation of the second and higher order moment equations for a set of stochastic differential equations based on Ito's differential lemma is difficult, even for small system of equations. From the knowledge of the statistical properties of the Gaussian white noises associated with the parameters and input coefficients of a set of stochastic differential equations of typeA.Ż+B.Z=C(t), a way to automatically generate the second order moment equations in a computer is presented in this paper. The resulting set of first and second order moment equations is also presented in the same state-space form of the original set of stochastic differential equations through a vectorization of the correlation matrix, which takes advantage of its symmetry. The procedure involved here avoids the inversion of matrixA to apply Ito's differential lemma. Therefore, the presented numerical implementation reduces the computational effort required in the formulation and solution of the moment equations. Moreover, other robust and efficient numerical deterministic integration schemes can be equally applied to the solution of the moment equations.
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    Stochastic environmental research and risk assessment 9 (1995), S. 238-238 
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    Stochastic environmental research and risk assessment 9 (1995), S. 269-296 
    ISSN: 1436-3259
    Keywords: Stochastic analysis ; diagrams ; groundwater flow
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract We present a diagrammatic method for solving stochastic 1-D and 2-D steady-state flow equations in bounded domains. The diagrammatic method results in explicit solutions for the moments of the hydraulic head. This avoids certain numerical constraints encountered in realization-based methods. The diagrammatic technique also allows for the consideration of finite domains or large fluctuations, and is not restricted by distributional assumptions. The results of the method for 1-D and 2-D finite domains are compared with those obtained through a realization-based approach. Mean and variance of head are well reproduced for all log-conductivity variances inputted, including those larger than one. The diagrammatic results also compare favorably to hydraulic head moments derived by standard analytic methods requiring a linearized form of the flow equation.
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    Stochastic environmental research and risk assessment 13 (1999), S. 1-26 
    ISSN: 1436-3259
    Keywords: Key words: Spatiotemporal ; stochastic ; mapping ; Bayes ; entropy ; computational approach ; physical knowledge bases ; epistemology.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract This paper is concerned with a computational formulation of the Bayesian maximum entropy (BME) mapping method, which can handle rigorously and efficiently spatiotemporal applications of considerable practical importance. BME is a method of modern geostatistics that can integrate and process physical knowledge that belongs to two major bases: general knowledge (i.e., obtained from general principles and laws, summary statistics and background information), and specificatory knowledge (i.e., obtained through experience with the specific situation). BME allows considerable flexibility regarding the choice of an appropriate spatiotemporal map, offers a complete assessment of the mapping uncertainty and contributes to the scientific understanding of the underlying natural phenomenon. Valuable insight is gained by studying a spatiotemporal data set representing water-level elevations at the Equus Beds aquifer (Kansas). Numerical results show that, as was expected in theory, classical geostatistics analysis is obtained as a special case of the considerably more general BME approach. Moreover, modern geostatistical analysis in terms of BME offers more accurate and informative results in practice, by incorporating various sources of physical knowledge that cannot be processed by the classical methods.
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    Stochastic environmental research and risk assessment 13 (1999), S. 27-47 
    ISSN: 1436-3259
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract Stochastic environmental risk assessment considers the effects of numerous biological, chemical, physical, behavioral and physiological processes that involve elements of uncertainty and variability. A methodology for predicting health risks to individuals from contaminated groundwater is presented that incorporates the elements of uncertainty and variability in geological heterogeneity, physiological exposure parameters, and in cancer potency. An idealized groundwater basin is used to perform a parametric sensitivity study to assess the relative impact of (a) geologic uncertainty, (b) behavioral and physiological variability in human exposure and (c) uncertainty in cancer potency on the prediction of increased cancer risk to individuals in a population exposed to contaminants in household water supplied from groundwater. A two-dimensional distribution (or surface) of human health risk was generated as a result of the simulations. Cuts in this surface (fractiles of variability and percentiles of uncertainty) are then used as a measure of relative importance of various model components on total uncertainty and variability. A case study for perchloroethylene or PCE, shows that uncertainty and variability in hydraulic conductivity play an important role in predicting human health risk that is on the same order of influence as uncertainty of cancer potency.
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    Stochastic environmental research and risk assessment 13 (1999), S. 66-84 
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    Notes: Abstract Velocity variability at scales smaller than the size of a solute plume enhances the rate of spreading of the plume around its center of mass. Macroscopically, the rate of spreading can be quantified through macrodispersion coefficients, the determination of which has been the subject of stochastic theories. This work compares the results of a volume-averaging approach with those of the advection dominated large-time small-perturbation theory of Dagan [1982] and Gelhar and Axness [1983]. Consider transport of an ideal tracer in a porous medium with deterministic periodic velocity. Using the Taylor-Aris-Brenner method of moments, it has been previously demonstrated [Kitanidis, 1992] that when the plume spreads over an area much larger than the period, the volume-averaged concentration satisfies the advection-dispersion equation with constant coefficients that can be computed. Here, the volume-averaging analysis is extended to the case of stationary random velocities. Additionally, a perturbation method is applied to obtain explicit solutions for small-fluctuation cases, and the results are compared with those of the stochastic macrodispersion theory. It is shown that the method of moments, which uses spatial averaging, for sufficiently large volumes of averaging yields the same result as the stochastic theory, which is based on ensemble averaging. The result is of theoretical but also practical significance because the volume-averaging approach provides a potentially efficient way to compute macrodispersion coefficients. The method is applied to a simplified representation of the Borden aquifer.
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    Stochastic environmental research and risk assessment 13 (1999), S. 85-99 
    ISSN: 1436-3259
    Keywords: Key words: Hydraulic diffusivity ; groundwater ; spectral analysis ; stochastic boundaries.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract: This study uses the cyclical frequency to develop the mathematical relationship between hydraulic diffusivity and spectral density functions calculated from groundwater level variation. Such relationship can be applied to (1) unsteady state, one-dimensional confined aquifer with time-dependent water level on both end boundaries, and (2) linearized unconfined aquifer with or without vertical recharge. The spectral density functions of groundwater fluctuations are largely affected by the spectral density functions obtained from time-dependent end boundaries and their cross-spectral density functions. Hydraulic diffusivity of an aquifer can be solved by type-curve matching technique at a specified frequency band under the conditions of (1) confined aquifer having equal time-dependent boundaries on both ends, (2) unconfined aquifer having equal time-dependent boundaries on both ends with surface recharge, and (3) unconfined aquifer subjected to surface recharge but neglecting the water table fluctuations on both end boundaries.
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    Stochastic environmental research and risk assessment 13 (1999), S. 113-130 
    ISSN: 1436-3259
    Keywords: Key words: Climatology ; meso-scale convective systems ; classification ; anisotropy ; intermittency ; ergodicity ; upscaling ; level sets.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract: The meta-Gaussian model is fitted to a set of 258 sahelian rainfields. The hypotheses underlying this model are discussed with a special emphasis on its ergodic properties, the scale of the phenomenon and the scale of observation. Then the ability of this model to reproduce some observed features, in particular upscaling properties, is checked from a distributional point of view. Finally, some simple properties of the thresholds which are linked to the area threshold method are described.
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    Stochastic environmental research and risk assessment 13 (1999), S. 100-112 
    ISSN: 1436-3259
    Keywords: Key words: Geostatistic ; Gaussian random functions ; anamorphosis ; intermittency ; discontinuous c.d.f ; valid covariance ; internal consistency.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract: For the purpose of numerically studying sahelian storm rainfields, a family of random functions is described with a characterization of its finite dimensional law. Some problems appearing when fitting its functional parameters are put forward and two solutions to bypass those problems are provided, according to the regularity properties of the marginal cumulative distribution function. An illustration of this method is implemented on a set of sahelian rainfields of event accumulation displaying a strong spatial intermittency.
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    Stochastic environmental research and risk assessment 13 (1999), S. 365-379 
    ISSN: 1436-3259
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    Notes: Abstract. Conceptual model selection is a key issue in risk assessment studies. We analyze the effect of a number of conceptual aspects related to solute transport in two-dimensional heterogeneous media. The main issues addressed are non-ergodicity, anisotropy in the correlation structure of the transmissivity field, and dispersion at the local scale. In particular, we study the development of a solute plume when mean flow is oriented at an angle with respect to the principal directions of anisotropy. The study is carried out in a Lagrangian framework using Monte Carlo analysis. Of special interest is the evolution of individual plumes. A number of aspects are analyzed, namely the location of the center of mass for each plume and the different ways to compute the angles that the main axes of the plume develop with respect to the direction of the mean flow. Stochastic theories based upon ergodicity conclude that the plume gets oriented in the mean flow direction. In our non-ergodic simulations, the mean of the offset angles, for each individual plume in each particular realization, is offset from the mean flow direction towards the direction of maximum anisotropy. If, instead, the analysis is performed on the ensemble plume (superposition of all different simulations), it is then found oriented closer to the direction of the mean flow than the average offset angle for the different plumes considered separately. This last result adds an extra word of caution to the use of ensemble averaged values in solute transport studies. Serious implications for risk assessment follow from the conceptual model adopted. First, in any single realization there will a large uncertainty in locating the plume at any given time; second, real dilution would be less than what would be expected if the macrodispersion values obtained for ergodic conditions were applied; third, the volume that is affected by a non-zero concentration is smaller than that predicted from macrodispersion concepts; fourth, the orientation of the plume does not correspond to that of the mean flow; and fifth, accounting for local dispersion helps reducing uncertainty.
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    Stochastic environmental research and risk assessment 13 (1999), S. 396-415 
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    Notes: Abstract. We analyze the movement of a solute cloud in a saturated aquifer, resulting from a point-like instantaneous solute injection. Physical heterogeneities of the medium due to spatial variations of the hydraulic conductivity, as well as the chemical heterogeneities due to variations in the linear adsorption coefficient and the degradation rate, are modeled as spatial stochastic processes with exponential autocorrelation functions. Furthermore, cross-correlations between the chemical properties and the conductivity are taken into account. For large transport times, the movement of the solute cloud is characterized by its center-of-mass velocity, by the macroscopic dispersion constant, and the macroscopic degradation rate. These quantities are evaluated using perturbation theory and two different averaging procedures. The first procedure derives the large-scale properties from the central moments of the concentration distribution in a given aquifer realization, and averages over the ensemble afterwards. The second method which is mathematically less demanding obtains large scale transport coefficients from the central moments of the ensemble-averaged concentration distribution. Under the assumption that both prescriptions lead to the same macro-scale quantities, the second approach is usually preferred in literature. The present paper is an extension of the work of Metzger et al. (1996). We show that the two averaging procedures lead to different results in one-dimensional systems, whereas the difference vanishes for higher dimensions. Taking into account the influence of small scale dispersion, we give explicit results for the macroscopic parameters characterizing the solute plume. We analyze the various contributions to these parameters and show how the physical origin of these contributions can be traced back uniquely to fluctuations in the retardation factor, in the flow field, and in the degradation rate, and to the cross-correlations between these inhomogeneities, respectively.
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    Stochastic environmental research and risk assessment 13 (1999), S. 416-435 
    ISSN: 1436-3259
    Keywords: Key words: Sequential linear estimator, successive linear estimator, conditional covariance, interpolation with large data sets.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract. A sequential linear estimator is developed in this study to progressively incorporate new or different spatial data sets into the estimation. It begins with a classical linear estimator (i.e., kriging or cokriging) to estimate means conditioned to a given observed data set. When an additional data set becomes available, the sequential estimator improves the previous estimate by using linearly weighted sums of differences between the new data set and previous estimates at sample locations. Like the classical linear estimator, the weights used in the sequential linear estimator are derived from a system of equations that contains covariances and cross-covariances between sample locations and the location where the estimate is to be made. However, the covariances and cross-covariances are conditioned upon the previous data sets. The sequential estimator is shown to produce the best, unbiased linear estimate, and to provide the same estimates and variances as classic simple kriging or cokriging with the simultaneous use of the entire data set. However, by using data sets sequentially, this new algorithm alleviates numerical difficulties associated with the classical kriging or cokriging techniques when a large amount of data are used. It also provides a new way to incorporate additional information into a previous estimation.
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    Meteorology and atmospheric physics 1 (1948), S. 39-61 
    ISSN: 1436-5065
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Physics
    Description / Table of Contents: Summary After an introduction on the most essential qualities of internal tidal waves a series of special cases of such waves (Strait of Gibraltar at Neaptide, “Meteor”-anchor-station 254 in the equatorial Atlantic, “Meteor”-stations 369 and 366 on Cap Verde continental-shelf off NW Africa, Strait of Gibraltar at Spring tide, Strait of Messina) have been thoroughly discussed. Particular attention has been paid to the phenomenon of the progressive change of the wave profile which was pursued to the total degeneration of the wave. This degeneration seems to be tied to the appearance of unstabl conditions and may increase to internal breakers of the tidal wave (internal bore). The decline of depth of the water layer on the continental-shelf with the progression of the internal wave according toFjeldstad's theory on the one hand, on the other hand the appearance of dynamic instability at a certain stream structure in the ocean were recognised as cause of this progressive change of shape of the wave profile. In particular the last mentioned circumstance appears to be decisive for the formation of an asymmetrical wave profile of internal tidal waves up to internal breakers. It was particularly referred to the oceanographic importance of this phenomenon for the mixing processes on the continental-shelf.
    Abstract: Résumé Après une introduction sur les qualités les plus essentielles des marées internes, une série de cas de telles ondes (détroit de Gibraltar à marée basse, station d'ancrage “Météor” 254 dans l'Atlantique équatorial, stations d'ancrage “Météor” 369 et 366 sur la plate-forme continentale du Cap-Vert au NW de l'Afrique, détroit de Gibraltar à haute marée, détroit de Messine) est discutée à fond. Une attention particulière a été attribuée au phénomène de changement progressif du profil d'onde et elle est poursuivie jusqu'à la dégénération de l'onde qui apparaît d'être liée à l'entrée de conditions instables et qui peut s'accroître jusqu'au ressac interne de la marée (Bore interne). D'une part selon la théorie deFjeldstad la diminution de hauteur de la couche d'eau avec la progression de la marée interne existant sur la plateforme continentale, d'autre part l'apparition d'instabilité dynamique au cas d'une certaine structure des courants dans l'océan ont été reconnus d'être la cause de ce changement de forme du profil d'onde. Surtout cette dernière circonstance apparaît d'être décisive pour la formation d'un profil d'onde asymétrique des marées internes jusqu'au ressac interne. En particulier l'importance océanographique de cette apparition pour les procédés de mélange sur la plate-forme continentale a été indiquée.
    Notes: Zusammenfassung Nach einer Einleitung über die wesentlichsten Eigenschaften interner Gezeitenwellen wurde eine Reihe von speziellen Fällen solcher Wellen (Straße von Gibraltar bei Nipptide, “Meteor”-Ankerstation 254 im äquatorialen Atlantischen Ozean, “Meteor”-Stationen 369 und 366 auf dem Kap-Verde-Schelf vor NW-Afrika, Straße von Gibraltar bei Springtide, Straße von Messina) eingehend diskutiert. Dabei wurde besondere Aufmerksamkeit der Erscheinung der fortschreitenden Änderung des Wellenprofils geschenkt und diese bis zur völligen Degeneration der Welle verfolgt. Diese Degeneration, die an den Eintritt unstabiler Verhältnisse geknüpft erscheint, kann sich bis zur internen Brandung der Gezeitenwelle (interne Bore) steigern. Als Ursache dieser fortschreitenden Formveränderung des Wellenprofils wurde einerseits entsprechend der Fjeldstadschen Theorie die mit Fortschreiten der internen Gezeitenwelle auf dem Schelf vorhandene Tiefenabnahme der Wasserschicht, anderseits das Auftreten von dynamischer Instabilität bei bestimmtem Stromaufbau im Ozean erkannt. Namentlich letzterer Umstand scheint für die Ausbildung einer Asymmetrie des Wellenprofils interner Gezeitenwellen bis zur inneren Brandung ausschlaggebend zu sein. Auf die ozeanographische Bedeutung dieser Erscheinung für die Mischungsvorgänge auf dem Schelf wurde besonders hingewiesen.
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  • 99
    Electronic Resource
    Electronic Resource
    Springer
    Meteorology and atmospheric physics 1 (1948), S. 100-107 
    ISSN: 1436-5065
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Physics
    Description / Table of Contents: Zusammenfassung Von der Anzahl der gleichzeitigen Niederschlagstage an zwei Beobachtungsstationen und von der Abweichung ihrer Wahrscheinlichkeit ausgehend, wird eine Methode zum Vergleiche der Niederschlagstypen im synoptischen Sinne entwickelt. Der sogenannte Ähnlichkeitsindex, der zwischen −1 und +1 variieren kann, wird mathematisch definiert. Je nach dem Wert desselben ist die zeitliche Verteilung der Niederschlagstage an zwei Orten gleich (+1), indifferent (0) oder entgegengesetzt (−1). Bei der Anwendung der Methode tritt eine gesetzmäßige Abnahme des Index mit der Entfernung auf. Ein entgegengesetztes Verhalten des Ähnlichkeitsindex beiderseits der Alpen veranschaulicht die Rolle, welche die Alpen bekanntlich als Wetterscheide spielen.
    Abstract: Summary A method of obtaining a synoptic view of the distribution of precipitation (rain- and snowfall) is developed. It is based on the number of days on which precipitation occurs at both of two places more or less distant from each other. A mathematical definition is given of an index of similarity, which latter varies between −1 and +1. These, limiting, figures signify in the case of −1 that precipitation is least likely to occur on any one day at both of two different places, in the case of +1 that it is most likely to occur, and that when the index of similarity is 0 no relation at all can be established for the likelihood of precipitation at both places on the same day. The index shows a sharp decline as the distance between places increases. In general it shows less relationship in regard to the simultaneous occurrence of rain-and snowfall between places lying on opposite sides of the Alps than between places on the same side, showing once more how the Alps act as a weather partition. The results, based on observations at 9 places in Switzerland and 8 in other European countries, are valid for the Temperate Zone; for other climatic regions they may be different.
    Notes: Résumé On développe une méthode basée sur le dénombrement des jours de pluite communs à deux stations données et sur l'écart avec leur probabilité. Une formule simple définit l'indice de similitude de deux régimes pluviaux, indice qui peut varier de −1 à +1 et qui caractérise la plus ou moins grande similitude des distributions chronologiques de la pluie en deux endroits quelconques. L'application de la méthode conduit à établir une loi de décroissance de l'indice avec la distance séparant les stations comparées. Dans la région alpine cette loi présente une anomalie résultant de l'effet orographique.
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  • 100
    Electronic Resource
    Electronic Resource
    Springer
    Meteorology and atmospheric physics 1 (1948), S. 127-140 
    ISSN: 1436-5065
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Physics
    Description / Table of Contents: Summary Without entering into details first of all the fundamental principles of magnetic topography and its main task are thoroughly discussed. Each magnetic surveying is to-day of double importance: on the one hand it contributes to the knowledge of the whole terrestrial magnetic field, on the other hand it lays the foundations for a further exploration of the uppermost layers of the earth according to the methods of applied geophysics. Single observations may therefore be of different importance. Great value was attached to formulating and describing as clear as possible certain fundamental principles such as spacial reach and representativity of a measuring point, validity range of data of an observatory, both spacial and temporal, and to giving all essential measures by which such topographies become mutually comparable.
    Abstract: Résumé Sans donner des détails on discute à fond tout d'abord les principes fondamentaux de la levée magnétique et sa tâche principale. Chaque levée magnétique a aujourd'hui une double importance, premièrement de contribuer à la connaissance du champ magnétique terrestre total, deuxièmement de livrer les bases pour une exploration plus vaste des couches terrestres supérieures d'après les méthodes de la géophysique appliquée. C'est pourquoi les observations individuelles peuvent avoir une importance différente. Une grande valeur a été attachée à formuler et décrire le plus clairement possible certains principes fondamentaux, comme la portée spatiale et la représentativité d'un point de mesure, le domaine de validité des données d'un observatoire dans l'espace et dans le temps, et à indiquer les précautions à prendre pour rendre comparables les différentes topographies.
    Notes: Zusammenfassung Ohne auf Einzelheiten zunächst näher einzugehen, werden die für die magnetische Landesaufnahme wichtigen Grundbergriffe und ihre Hauptaufgabe einer eingehenderen Diskussion unterzogen. Jede magnetische Aufnahme hat heute eine doppelte Bedeutung, einmal einen Beitrag zur Kenntnis des gesamten Erdfeldes zu liefern, anderseits die Grundlagen für eine weitere Erforschung der obersten Erdschichten nach den Methoden der angewandten Geophysik zu geben. Daraus ergeben sich die verschiedenen Bedeutungen, die den einzelnen gemessenen Werten zukommen und zwischen denen zu unterscheiden ist. Es ist Wert darauf gelegt worden, gewisse Grundbegriffe, wie räumliche Reichweite und Repräsentativität eines Meßpunktes, Gültigkeitsbereich der Angaben eines Observatoriums in räumlicher und zeitlicher Beziehung möglichst klar zu fassen und darzustellen, sowie alle wesentlichen Maßnahmen anzugeben, durch die derartige Aufnahmen unter sich vergleichbar werden.
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