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  • 11
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 94-94 
    ISSN: 1436-3259
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 12
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 95-114 
    ISSN: 1436-3259
    Schlagwort(e): Soil moisture ; time scale ; non-Gaussian ; colored-noise
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: 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.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 13
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 115-127 
    ISSN: 1436-3259
    Schlagwort(e): Rainfall-runoff modeling ; transfer response ; dynamic non-linear models ; normal and gamma observational distribution ; predictive performance
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: 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.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 14
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 129-143 
    ISSN: 1436-3259
    Schlagwort(e): Stochastic analysis ; perturbation methods ; unsaturated transport ; heterogeneous porous media
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: 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.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 15
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 65-93 
    ISSN: 1436-3259
    Schlagwort(e): Nonparametric ; Monte Carlo ; precipitation ; weather
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: 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.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 16
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 255-266 
    ISSN: 1436-3259
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: 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.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 17
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 229-254 
    ISSN: 1436-3259
    Schlagwort(e): Model validation ; analysis of uncertainty ; model verification ; quality assurance ; system identification ; model calibration
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract The development and use of models for predicting exposures are increasingly common and are essential for many risk assessments of the United States Environmental Protection Agency (EPA). Exposure assessments conducted by the EPA to assist regulatory or policy decisions are often challenged to demonstrate their “scientific validity”. Model validation has thus inevitably become a major concern of both EPA officials and the regulated community, sufficiently so that the EPA's Risk Assessment Forum is considering guidance for model validation. The present paper seeks to codify the issues and extensive foregoing discussion of validation with special reference to the development and use of models for predicting the impact of novel chemicals on the environment. Its preparation has been part of the process in formulating a White Paper for the EPA's Risk Assessment Forum. Its subject matter has been drawn from a variety of fields, including ecosystem analysis, surface water quality management, the contamination of groundwaters from high-level nuclear waste, and the control of air quality. The philosophical and conceptual bases of model validation are reviewed, from which it is apparent that validation should be understood as a task of product (or tool) design, for which some form of protocol for quality assurance will ultimately be needed. The commonly used procedures and methods of model validation are also reviewed, including the analysis of uncertainty. Following a survey of past attempts at resolving the issue of model validation, we close by introducing the notion of a model having maximum relevance to the performance of a specific task, such as, for example, a predictive exposure assessment.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 18
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 303-321 
    ISSN: 1436-3259
    Schlagwort(e): Simulation ; hydrograph rise and recession ; rainfall process ; probability distribution
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract A model is developed for annual low flow hydrographs. Its two primary components reflect the fact that hydrologic processes during streamflow rise (function of water input) and recession (function of basin storage) are different. Durations of periods of rise (wet intervals) and recession (dry intervals) are modelled by discrete probability distributions — negative binomial for dry intervals and negative binomial or modified logarithmic series for wet intervals depending on goodness of fit. During wet intervals, the total inflow is modelled by the lognormal distribution and daily amounts are allocated according to a pattern-averaged model. During dry intervals, the flow recedes according to a deterministic-stochastic recession model. The model was applied to three Canadian basins with drainage area ranging from 2210 to 22000 km2 to generate 50 realizations of low flow hydrographs. The resulting two standard-error confidence band for the simulated probability distribution of annual minimum 7-day flows enclosed the probability distribution estimated from the observed record. A sensitivity analysis for the three basins revealed that in addition to the recession submodel, the most important submodel is that describing seasonality. The state of the basin at the beginning of the low flow period is of marginal importance and the daily distribution of input is unimportant.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 19
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 267-295 
    ISSN: 1436-3259
    Schlagwort(e): Space/time processes ; stochastic analysis ; regression model ; solute contents
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract A regression model is used to study spatiotemporal distributions of solute content ion concentration data (calcium, chloride and nitrate), which provide important water contamination indicators. The model consists of three random and one deterministic components. The random space/time component is assumed to be homogeneous/stationary and to have a separable covariance. The purely spatial and the purely temporal random components are assumed to have homogenous and stationary increments, respectively. The deterministic component represents the space/time mean function. Inferences of the random components involve maximum likelihood and semi-parametric methods under some restrictions on the data configuration. Computational advantages and modelling limitations of the assumptions underlying the regression model are discussed. The regression model leads to simplifications in the space/time kriging and cokriging systems used to obtain space/time estimates at unobservable locations/instants. The application of the regression model in the study of the solute content ions was done at a global scale that covers the entire region of interest. The variability analysis focuses on the calculation of the spatial direct and cross-variograms and the evaluation of correlations between the three solute content ions. The space/time kriging system is developed in terms of the space direct and cross-variograms, and allows the separate estimation of the regression model components. Maps of these components are then obtained for each one of the three ions. Using the estimates of the purely spatial component, spatial dependencies between the ions are studied. Physical causes and consequences of the space/time variability are discussed, and comparisons are made with previous analyses of the solute content dataset.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 20
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 11 (1997), S. 323-330 
    ISSN: 1436-3259
    Schlagwort(e): Kolmogorov-Smirnov test ; identification of periodic component ; goodness-of-fit test for white noise ; periodogram ; residuals
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract A modified version of the widely used Kolmogorov-Smirnov (K-S) test of null hypothesis is constructed, that a given time series is Gaussian white noise, against the alternative hypothesis that the time series contains an added or multiplicative deterministic-periodic component of unspecified frequency. The usual KS test is treated as a special case. The proposed test is more powerful than the ordinary K-S test in detecting extreme (low or high) hidden periodicities. Computational procedure necessary for implementation are also given.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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