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  • Articles  (8,948)
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  • Articles  (8,948)
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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
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    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 
    ISSN: 1436-3259
    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 
    ISSN: 1436-3259
    Keywords: Key words: Risk ; clustering ; point process ; Poisson ; flood.
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    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
    Source: Springer Online Journal Archives 1860-2000
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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 
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    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.
    Source: Springer Online Journal Archives 1860-2000
    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 
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    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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    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 
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    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 
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    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
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    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 
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    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 14 (2000), S. 109-122 
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    Notes: Abstract. We consider the problem of upscaling transient real gas flow through heterogeneous bounded reservoirs. One of the commonly used methods for deriving effective permeabilities is based on stochastic averaging of nonlinear flow equations. Such an approach, however, would require rather restrictive assumptions about pressure-dependent coefficients. Instead, we use Kirchhoff transformation to linearize the governing stochastic equations prior to their averaging. The linearized problem is similar to that used in stochastic analysis of groundwater flow. We discuss the effects of temporal localization of the nonlocal averaged Darcy's law, as well as boundary effects, on the upscaled gas permeability. Extension of the results obtained by means of small perturbation analysis to highly heterogeneous porous formations is also discussed.
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    Stochastic environmental research and risk assessment 14 (2000), S. 139-158 
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    Keywords: Key words: Confluent hypergeometric, generalised inverse Gaussian, Halphen system of distributions, modified Bessel, randomisation, simulation, sufficient statistics.
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    Notes: Abstract. Some of the considerable statistical content of modified Bessel functions of the second kind and of Tricomi's confluent hypergeometric function is illustrated. Moment solutions for the parameters of exponential class distribution functions based on both are derived. Unlike the generalised inverse Gaussian, the Tricomi exponential distribution is little known but it emerges that it is of wide applicability, highly flexible and has the gamma distribution as a special case.
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    Stochastic environmental research and risk assessment 14 (2000), S. 159-160 
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    Stochastic environmental research and risk assessment 14 (2000), S. 173-179 
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    Notes: Abstract.  The use of complicated models of the cancer process has been limited by the need to have a mathematical framework allowing for a general expansion of the theory of carcinogenesis while maintaining numerically tractable results. A system of ordinary differential equations is derived for calculating tumor incidence in multistage models of carcinogenesis. The resulting system of equations is applicable to nonhomogenous processes (i.e. ones in which the rates change with time, age, etc.). In addition, a solution is given for the case of instantaneous initiation. These formulae can easily be coupled with physiologically-based pharmacokinetic models to link biomarkers of exposure to cancer risks. An example is presented.
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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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    Journal of geographical systems 2 (2000), S. 85-90 
    ISSN: 1435-5949
    Keywords: Key words: GIS, spatial analysis, behavioral modeling, human spatial behavior
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. In recent years, comprehensive geographic data sets of metropolitan areas and individual-level, georeferenced data are becoming more available to social scientists. At the same time, tools for performing spatial analysis in a GIS environment have also become more available. These developments provide many new opportunities for the analysis and theoretical understanding of disaggregate human spatial behavior. This paper examines how these developments may enable the researcher to represent complex urban and cognitive environments more realistically, and to overcome the limitations of aggregate spatial data framework. It explores their implications for the theoretical and methodological development in geography and other social science disciplines.
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    Journal of geographical systems 2 (2000), S. 91-97 
    ISSN: 1435-5949
    Keywords: Key words: GIS, epidemiology, spatial statistics, spatial models
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. This paper summarizes contributions of GIS in epidemiology, and identifies needs required to support spatial epidemiology as science. The objective of spatial epidemiology is to identify disease causes and correlates by relating spatial disease patterns to geographic variation in health risks. GIS supports disease mapping, location analysis, the characterization of populations, and spatial statistics and modeling. Although laudable, these accomplishments are not sufficient to fully identify disease causes and correlates. One reason is the failure of present-day GIS to provide tools appropriate for epidemiology. Two needs are most pressing. First, we must reject the static view: meaningful inference about the causes of disease is impossible without both spatial and temporal information. Second, we need models that translate space-time data on health outcomes and putative exposures into epidemiologically meaningful measures. The first need will be met by the design and implementation of space-time information systems for epidemiology; the second by process-based disease models.
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    Topics: Geography
    Notes: Abstract. This paper shows an explanatory tool (a FORTRAN program linked to GIS software), called VCM (Variable Clumping Method), for detecting statistically significant `multi-level clumps' in the distribution of points. The multi-level clumps imply a set of clumps whose clumping radius varies from a small radius to a large radius (in spirits, VCM is similar to the K-function method). Compared with the ordinary (fixed radius) clumping method, VCM can detect overall significant clumps in the distribution of points.
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    Journal of geographical systems 2 (2000), S. 157-165 
    ISSN: 1435-5949
    Keywords: Key words: Aggregation, bias, parameter composition ; JEL classification: C4, C5, C8, R1
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. The spatial aggregation problem – also termed the modifiable areal unit problem – has attracted regular attention in spatial statistics and econometrics. In this study econometric aggregation analysis is used to investigate the formal composition of meso-areal parameters given micro-areal underlying relations with spatial dependence. Impact on stochastic terms (possible meso-areal spatial autocorrelation) is also studied. Finally consequences for meso-areal estimation are derived, the general finding having been that spatial aggregation leads to meso-region specific parameter values, with the estimation problems this implies.
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    Journal of geographical systems 2 (2000), S. 121-140 
    ISSN: 1435-5949
    Keywords: Key words: Data rough, data smooth, table look up, pattern perception, interactive graphics ; JEL Classification: C21, C51, C52, C88
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. A consistent theme in recent work on developing exploratory spatial data analysis (ESDA) has been the importance attached to visualization techniques, particularly following the pioneering development of packages such as SPIDER and REGARD (Haslett et al. 1990).  The focus on visual techniques is often justified in two ways: (a) the power of modern graphical interfaces means that graphics is no longer a way of simply presenting results in the form of maps or graphs, but a tool for the extraction of information from data; (b) graphical, exploratory methods are felt to be more intuitive for non-specialists to use than methods of numerical spatial statistics enabling wider participation in the process of getting data insights. However, little work has been done to decide which visualization tools might be needed to support ESDA, or how they can be most effectively implemented.  This paper briefly reviews a theoretical framework that has been suggested for addressing these issues, which comprises two elements: firstly a data model, based on the distinction between rough and smooth properties of spatial data, that defines what an analyst is looking for in data (Haining et al. 1998) and secondly a theoretical model for assessing the quality of visualisation tools (Cleveland 1994). The emphasis of this paper is the use of the theoretical framework to structure an assessment of SAGE, a software system that has been written for the spatial statistical analysis (including both exploratory and confirmatory data analysis) of area based data linked to a GIS. The aim of the assessment is to identify the desirable features of the system (that might be employed in other systems) whilst also highlighting what the additional requirements are thereby contributing to the development of systems for ESDA that contain good quality scientific visualization tools for exploratory spatial data analysis.
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    Journal of geographical systems 2 (2000), S. 201-220 
    ISSN: 1435-5949
    Keywords: Key words: Geocomputation, spatial econometrics, spatial statistics, SpaceStat ; JEL classification: C87, C88, C49
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. This paper describes the functionality and architecture of SpaceStat, the SpaceStat Extension for ArcView and the DynESDA Extension for ArcView. It compares the features of these packages to five other software implementations for spatial data analysis. Some ideas are formulated on generic requirements and future directions pertaining to computing environments for spatial data analysis.
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    Journal of geographical systems 2 (2000), S. 31-35 
    ISSN: 1435-5949
    Keywords: Key words: GIS, GIScience, spatial analysis, computational geography, future trends
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. It is past time for us to examine the relationship that exists between what we commonly call spatial analysis on the one hand, and geographic information systems or GIS on the other. GIS technology is widely used but seems to incorporate only a portion of the tools found in spatial analysis. Spatial analysis can be accused of overly simplistic approaches that severely limit its practical utility. This paper suggests that discarding myopic views and meeting upon a common ground of increased knowledge of modern computing concepts and techniques, including object-orientation, can prove extremely fruitful to both sides.
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    Journal of geographical systems 2 (2000), S. 43-47 
    ISSN: 1435-5949
    Keywords: Key words: GIS, spatial analysis, substantive research
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    Topics: Geography
    Notes: Abstract. This paper is concerned with the intersection of GIS and spatial analysis, its accessibility for scientists who may be less methodologically oriented than others, and its use in substantive research driven by theoretical, conceptual, and empirical issues central to one's discipline. GIS/SA use in this manner has lagged considerably. The case is documented, that there may be shifts in this trend is noted, and suggestions for moving ahead more quickly are put forth. These include instructional efforts, software development, and substantive research that will provide a demonstration effect, guide, and direction for others.
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    Journal of geographical systems 2 (2000), S. 55-60 
    ISSN: 1435-5949
    Keywords: Key words: Spatial analysis, geographic information science, Euclidean space, distance, direction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. Spatial analysis mostly developed in an era when data was scarce and computational power was expensive. Consequently, traditional spatial analysis greatly simplifies its representations of geography. The rise of geographic information science (GISci) and the changing nature of scientific questions at the end of the 20th century suggest a comprehensive re-examination of geographic representation in spatial analysis. This paper reviews the potential for improved representations of geography in spatial analysis. Existing tools in spatial analysis and new tools available from GISci have tremendous potential for bringing more sophisticated representations of geography to the forefront of spatial analysis theory and application.
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    Journal of geographical systems 2 (2000), S. 99-105 
    ISSN: 1435-5949
    Keywords: Key words: Multi-agent systems, computational geography, field-computing
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    Topics: Geography
    Notes: Abstract. Geographical Information Science is essentially computational geography and has its own research program, namely all aspects of formal models for spatial natural processes and the interaction of humans with the environment in space and time. This is not a question of technology and technology-related research; but technology influences what questions can be researched effectively. Collection of data in the field and the simulation of field experience through Virtual Reality are just two questions of how spatial reality and human experience are linked. The focus on human spatial cognition is similarly found in software engineering for interoperable Geographic Information Systems.
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    Journal of geographical systems 2 (2000), S. 107-110 
    ISSN: 1435-5949
    Keywords: Key words: Spatial data analysis, spatial structure, data mining, neural and evolutionary computations, GIS
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. The discussion is structured around two themes, namely spatial data analysis and spatial structure/process analysis. With respect to spatial data analysis, I concentrate on the issues related to geographical information systems (GIS), as well as spatial data mining and knowledge discovery in databases. With reference to spatial structure/process analysis, the emphasis is placed on the analysis of complex systems.
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    Journal of geographical systems 2 (2000), S. 257-286 
    ISSN: 1435-5949
    Keywords: Key words: Exploratory analysis, regionalisation, visualisation, autocorrelation, spatial regressions, client-server computing, brushing ; JEL classification: C21, C51, C52, C87, C88
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
    Notes: Abstract. This paper provides a description of SAGE, a software package linked to the Arc/Info GIS that can be used to undertake spatial statistical analysis of area based data. The paper is written from the perspective of the user who wishes to undertake exploratory and confirmatory spatial data analysis. The paper discusses design aspects of the package and also the statistical analysis philosophy underlying its contents. The paper describes the statistical analyses which SAGE can perform and details on how it performs them together with some illustrative examples. Detail on visualisation aspects of SAGE are discussed in a separate paper (Haining et al. 2000). The wider contribution of the paper is to build on earlier developments in this area and identify the needs of software packages if they are to enable users to implement effective spatial statistical analysis.
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    Journal of geographical systems 2 (2000), S. 375-398 
    ISSN: 1435-5949
    Keywords: Key words: Resels, exploratory data analysis, filtering, visualization, census ; JEL classification: C10, C80, C81, J10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography
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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 
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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 
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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
    Source: Springer Online Journal Archives 1860-2000
    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 
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    Keywords: JEL classification: R1, R12 ; Key words:Central place theory, choice rules, generalised Voronoi diagrams, market areas
    Source: Springer Online Journal Archives 1860-2000
    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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    Papers in regional science 79 (2000), S. 111-134 
    ISSN: 1435-5957
    Keywords: JEL classification: R11, R15, R30 ; Key words:Demography of the firm, regional economic growth, micro-simulation, firm formation, firm dissolution
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Economics
    Notes: Abstract. Recently, there is an increasing demand in spatial planning for models based on the demographic concepts of birth and death of firms. This article describes the structure of a spatial demographic simulation model of firms, and its application within The Netherlands. The model structure is essentially of the familiar demographic cohort component type, where an initial cohort of firms ages in a number of discrete steps, and where in each step additions and subtractions to and from the population are modelled using birth, death and migration components. Apart from the central processes of birth, death and migration, the type of economic activity and firm size are highly important for understanding firm behaviour over time. The article describes the transition functions for each of the demographic components and for firm growth. In addition, some empirical results are presented of a number of model simulations in The Netherlands. The results were partly validated using observed economic demographic data. It is concluded that a substantial amount of work remains to be done in this new field. The model presented here has direct implications for the research agenda of the study of the demography of the firm.
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    Papers in regional science 79 (2000), S. 233-242 
    ISSN: 1435-5957
    Keywords: JEL classification: C67, D57, E17, R15 ; Key words: Input-output analysis, social accounting, model closure, expenditure lags, supply effects
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Economics
    Notes: Abstract. Cole (1989, 1997, 1999) advocates the introduction of expenditure lags and the fullest possible closure of single-region input-output models. Jackson et al. (1997, 1999) claim that closing also with regard to the Rest-of-the-World leads to inconsistencies and zero exogenous demand, which makes impact studies impossible. Using somewhat different arguments I agree with them: endogenous interregional feedbacks are conceptually impossible outside a full interregional model. Two hardly discussed points, however, remain for further research. First, closing with regard to all other regional demand is precarious too, as it empirically and theoretically amplifies the one-sidedness of the demand-driven input-output model. Realistic impact studies ask for models including supply-side aspects. Second, adding expenditure lags is an improvement, but the way in which this can be done and should be done requires further theoretical development.
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  • 82
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    Keywords: JEL classification: D83, R10 ; Key words: Search, spatial search, spatial economics
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    Topics: Geography , Economics
    Notes: Abstract. This is the second part of a two-part analysis of optimal spatial search begun in Harwitz et al. (1998). In the present article, two explicit computational procedures are developed for the optimal spatial search problem studied in Part I. The first uses reservation prices with continuous known distributions of prices and is illustrated for three stores. The second does not use reservation prices but assumes known discrete distributions. It is a numerical approximation to the first and also a tool for examining examples with larger numbers of stores.
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    Papers in regional science 79 (2000), S. 355-373 
    ISSN: 1435-5957
    Keywords: JEL classification: R12, C33 ; Key words: Firm formation, regions, panel data
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geography , Economics
    Notes: Abstract. This article investigates regional variations in firm formation in Finland between 1989 and 1993, and estimates the effects of regional factors on firm formation utilising panel and cross-sectional data. Panel data evidence shows that the average size of firms and establishments in the subregions tends to explain firm formation in Finland most robustly. Cross-sectional results for Finland and several other countries tend to show that demand growth is also an important factor explaining regional firm formation. Panel data results appear to differ from the cross-sectional ones.
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    Papers in regional science 79 (2000), S. 393-411 
    ISSN: 1435-5957
    Keywords: JEL Classification: R11 ; Key words: Human capital, US states, gross regional product, growth accounting
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    Topics: Geography , Economics
    Notes: Abstract. This article analyzes the extent to which human capital differences can explain the differences in gross state product (GSP) per capita levels between the richer and poorer states of the US. It uses 1990 Census and Bureau of Economic Analysis data on educational attainment, wage levels of different segments of the labor force, and GSP to compare New York – our representative rich state – with the poorest third of the states. The findings indicate that human capital differences explain at least 49% of the observed difference in GSP per capita between New York and each of the poor states.
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    Stochastic environmental research and risk assessment 14 (2000), S. 79-89 
    ISSN: 1436-3259
    Keywords: Key words: Shoreline erosion, time-dependent process, wave climate, safety function.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract. The dynamical responses of a shoreline over long-term (years or decades) is a non-linear and time-dependent random process. It is affected by both longshore and cross-shore sediment transports. The former tends to cause cumulative changes in the mean shoreline position while the latter usually only leads to beach profile fluctuations relative to the moving mean beach profile. Due to the time-dependency of the process the life-cycle approach is ideally suited to formulate the probability distribution of extreme shoreline erosion. A model based on such approach and using standard Monte Carlo simulation techniques has been reported by Dong and Chen (1999). In this paper a simplified procedure is developed by introducing the assumption that the longshore and cross-shore processes are statistically independent. This then allows the probability distribution of the extreme erosion to be calculated in terms of the marginal probability distributions of the maximum recessions due to purely longshore and purely cross-shore transport. This method was applied to two idealised shoreline configurations and its usefulness for engineering applications is evaluated by comparison with the full Monte Carlo method.
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    Stochastic environmental research and risk assessment 14 (2000), S. 161-171 
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract.  Models of dose–response for environmental pollutants generally do not include explicit consideration of the stochastic nature of the spatial pattern of dose delivered to an organ or tissue, or the correlation between events leading to a final health endpoint (such as cancer). The result can be significant errors in risk calculations when these stochastic properties contribute as strongly to the dose–response relationship as do the dose–response relationships for individual cells. The present paper considers the issue of stochasticity of dose and events (initiation, promotion and inactivation) for the case of carcinogenicity following exposure to environmental pollutants, using the case of irradiation by high LET emitters such as radon and progeny from water or air. The model is based on the concepts of hit probabilities and effect-specific track length probabilities (probability of damage per unit track length), and is applied first to in vitro data and then to predictions in vivo. It is shown that inhomogeneity of dose throughout an irradiated tissue or organ volume, and correlation between initiation, promotion and inactivation, can lead to significant differences in predicted risk.
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    Stochastic environmental research and risk assessment 14 (2000), S. 195-206 
    ISSN: 1436-3259
    Keywords: Key words: Uncertainty, risk assessment, risk management
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract.  The selection of optimal management strategies for environmental contaminants requires detailed information on the risks imposed on populations. These risks are characterized by both inter-subject variability (different individuals having different levels of risk) and by uncertainty (there is uncertainty about the risk associated with the Yth percentile of the variability distribution). In addition, there is uncertainty introduced by the inability to agree fully on the appropriate decision criteria. This paper presents a methodology for incorporating uncertainty and variability into a multi-medium, multi-pathway, multi-contaminant risk assessment, and for placing this assessment into an optimization framework to identify optimal management strategies. The framework is applied to a case study of a sludge management system proposed for North Carolina and the impact of stochasticity on selection of an optimal strategy considered. Different sets of decision criteria reflecting different ways of treating stochasticity are shown to lead to different selections of optimal management strategies.
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  • 88
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    Notes: Abstract.  Although hydrological time series for different sites in a given region are usually correlated and that climate changes should have a regional impact on water resources, very little has appeared in the literature about multivariate change-point analysis. This paper generalizes the univariate Bayesian approach for the detection of a single shift in the mean level to study a change in the mean-vector of a sequence of multivariate normal vectors. Two different problems are considered: the first one is the estimation of the unknown regional change-point under the hypothesis that a shift occurred, while the second one is the overall assessment of change versus no change. This method is illustrated by an application to streamflow data series for six rivers situated in the Northern Québec Labrador region.
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    Stochastic environmental research and risk assessment 14 (2000), S. 275-295 
    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 variability of rainfall is a key component determining how the continental surfaces react to the atmospheric forcing. When studying the impact of climatic fluctuations onto the water resources, it is thus of paramount importance to evaluate to which extent the atmospheric models used in this kind of studies are able to reproduce the variability of the rain process, both in space and time. First among these are the general circulation models (GCM) with coarse resolution, which has two consequences: (i) a simplified parametrisation of convection; (ii) a scale of representation of rainfields which is not adequate when it comes to use them as inputs to hydrologic models. Since linking GCM's and regional hydrologic models is the corner stone of impact studies, it is necessary to analyse the consequences of this gap in scales and to find ways of bridging it. As a preliminary step in that direction, a comparative analysis of the observed and of the GCM rainfall variabilities is carried out for a tropical semi-arid zone of West Africa displaying a high sensitivity to climatic fluctuations. Over tropical regions the GCM used here (LMD-6) has a space resolution of 1.6° in latitude and of 3.75° in longitude. The comparative study shows that the errors of the GCM rainfall outputs may be traced down to two fundamental shortcomings: (i) a wrong seasonal cycle, probably linked to problems in representing the large scale circulation; (ii) an unrealistic simulation of the mesoscale convective systems that are responsible for 90% of the rainfall over this area. This latter problem is especially damaging from an hydrological point of view, as shown from a detailed analysis of high resolution rainfall observations. Even though it is possible to design rainfall desaggregation models producing realistic small scale rainfields from large scale rainfields, such models are of limited utility as long as atmospheric models are not able to produce a realistic climatology in term of number and magnitude of convective systems.
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    Stochastic environmental research and risk assessment 14 (2000), S. 371-383 
    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.  Environmental companies bidding on multiple projects are presented with the opportunity for diversification in several areas of the environmental market but, also, with the risk of exposure to uncertain events that can result in major financial loss and/or make the company liable to future claims. Accordingly, each corporation determines its maximum financial involvement in a project by evaluating a project's risk characteristics. Further, a company usually takes a global perspective on the total amount it is prepared to lose without compromising its operational viability. This frequently translates into taking less than 100% working interest in a contract and having to determine the combination of working interests for the projects that satisfy both the financial constraints to risk and the requirement to maximize the total profit. This study provides a procedure that can be easily implemented numerically to quantitatively assess the participation in a number of projects under exponential and parabolic utility models. In particular, the parabolic utility model lends itself to analytic expressions for the working interests. Application of the method is illustrated in the case of three projects arranged at an increasing order of expected return, tolerance to risk, uncertainty, and potential to financial loss. Depending on the global risk tolerance, a greater interest is taken in the least uncertain (but least profitable) project, riskier projects considered only after full participation has been achieved in safer projects.
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    Stochastic environmental research and risk assessment 14 (2000), S. 384-411 
    ISSN: 1436-3259
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    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract.  Over a decade ago, point rainfall models based upon Poisson cluster processes were developed by Rodriguez-Iturbe, Cox and Isham. Two types of point process models were envisaged: the Bartlett–Lewis and the Neyman–Scott rectangular pulse models. Recent developments are reviewed here, including a number of empirical studies. The parameter estimation problem is addressed for both types of Poisson-cluster based models. The multiplicity of parameters which can be obtained for a given data set using the method of moments is illustrated and two approaches to finding a best set of parameters are presented. The use of a proper fitting method will allow for the problems encountered in regionalisation to be adequately dealt with. Applications of the point process model to flood design are discussed and finally, results for a model with dependent cell depth and duration are given. Taking into account the spatial features of rainfall, three multi-site models are presented and compared. They are all governed by a master Poisson process of storm origins and have a number of cell origins associated with each storm origin. The three models differ as to the type of dependence structure between the cell characteristics at different sites. Analytical properties are presented for these models and their ability to represent the spatial structure of a set of raingauge data in the South-West of England is examined. Continuous spatial-temporal models are currently being developed and results are presented for a model in which storm centres arrive in a homogeneous Poisson process in space-time, and cells follow them in time according to a Bartlett–Lewis type cluster. Examples of simulations using this model are shown and compared with radar data from the South-West of England. The paper concludes with a summary of the main areas in which further research is required.
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    Stochastic environmental research and risk assessment 14 (2000), S. 471-478 
    ISSN: 1436-3259
    Keywords: Key words: Random fields, norm, covariance, permissibility, estimation.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Notes: Abstract.  Permissibility of a covariance function (in the sense of Bochner) depends on the norm (or metric) that determines spatial distance in several dimensions. A covariance function that is permissible for one norm may not be so for another. We prove that for a certain class of covariances of weakly homogeneous random fields, the spatial distance can be defined only in terms of the Euclidean norm. This class includes commonly used covariance functions. Functions that do not belong to this class may be permissible covariances for some non-Euclidean metric. Thus, a different class of covariances, for which non-Euclidean norms are valid spatial distances, is also discussed. The choice of a coordinate system and associated norm to describe a physical phenomenon depends on the nature of the properties being described. Norm-dependent permissibility analysis has important consequences in spatial statistics applications (e.g., spatial estimation or mapping), in which one is concerned about the validity of covariance functions associated with a physically meaningful norm (Euclidean or non-Euclidean).
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    Stochastic environmental research and risk assessment 14 (2000), S. 428-448 
    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.  An efficient numerical solution for the two-dimensional groundwater flow problem using artificial neural networks (ANNs) is presented. Under stationary velocity conditions with unidirectional mean flow, the conductivity realizations and the head gradients, obtained by a traditional finite difference solution to the flow equation, are given as input-output pairs to train a neural network. The ANN is trained successfully and a certain level of recognition of the relationship between input conductivity patterns and output head gradients is achieved. The trained network produced velocity realizations that are physically plausible without solving the flow equation for each of the conductivity realizations. This is achieved in a small fraction of the time necessary for solving the flow equations. The prediction accuracy of the ANN reaches 97.5% for the longitudinal head gradient and 94.7% for the transverse gradient. Head-gradient and velocity statistics in terms of the first two moments are obtained with a very high accuracy. The cross covariances between head gradients and the fluctuating log-conductivity (log-K) and between velocity and log-K obtained with the ANN approach match very closely those obtained by a traditional numerical solution. The same is true for the velocity components auto-covariances. The results are also extended to transport simulations with very good accuracy. Spatial moments (up to the fourth) of mean-concentration plumes obtained using ANNs are in very good agreement with the traditional Monte Carlo simulations. Furthermore, the concentration second moment (concentration variance) is very close between the two approaches. Considering the fact that higher moments of concentration need more computational effort in numerical simulations, the advantage of the presented approach in saving long computational times is evident. Another advantage of the ANNs approach is the ability to generalize a trained network to conductivity distributions different from those used in training. However, the accuracy of the approach in cases with higher conductivity variances is being investigated.
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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
    Source: Springer Online Journal Archives 1860-2000
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    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
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    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
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    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
    Source: Springer Online Journal Archives 1860-2000
    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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