Effect of spatial variation characteristics on contouring of design storm depth     

Ke‐Sheng Cheng  Chiang Wei  Yen‐Ben Cheng  Hui‐Chung Yeh 《水文研究》2003,17(9):1755-1769

The ordinary kriging method, a geostatistical interpolation technique, was applied for developing contour maps of design storm depth in northern Taiwan using intensity–duration–frequency (IDF) data. Results of variogram modelling on design storm depths indicate that the design storms can be categorized into two distinct storm types: (i) storms of short duration and high spatial variation and (ii) storms of long duration and less spatial variation. For storms of the first category, the influence range of rainfall depth decreases when the recurrence interval increases, owing to the increasing degree of their spatial independence. However, for storms of the second category, the influence range of rainfall depth does not change significantly and has an average of approximately 72 km. For very extreme events, such as events of short duration and long recurrence interval, we do not recommend usage of the established design storm contours, because most of the interstation distances exceed the influence ranges. Our study concludes that the influence range of the design storm depth is dependent on the design duration and recurrence interval and is a key factor in developing design storm contours. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

SAMPLING REMOTELY SENSED IMAGERY FOR STORAGE,RETRIEVAL, AND RECONSTRUCTION*     

P. M. Atkinson  P. J. Curran  R. Webster 《The Professional geographer》1990,42(3):345-353

A major difficulty in remote sensing is handling the many data from sensors aboard aircraft and satellites. In this paper we identify an optimal procedure for sampling remotely sensed data before their storage or on their retrieval. The procedure depends on spatial correlation in the scene and uses kriging to estimate values that have been lost. An example in which data from an airborne multispectral scanner could be diminished to only about one tenth without serious loss of precision illustrates the method.  相似文献   

Assessing the population size of the European storm petrel (Hydrobates pelagicus) using spatial autocorrelation between counts from segments of criss-cross ship transects     

van der Meer  Jaap; Leopold  Mardik F. 《ICES Journal of Marine Science》1995,52(5):809-818

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Uncertainty as the overlap of alternate conditional distributions     

Olena Babak  Clayton V. Deutsch 《Computational Geosciences》2008,12(4):503-512

An important task in modern geostatistics is the assessment and quantification of resource and reserve uncertainty. This uncertainty is valuable support information for many management decisions. Uncertainty at specific locations and uncertainty in the global resource is of interest. There are many different methods to build models of uncertainty, including Kriging, Cokriging, and Inverse Distance. Each method leads to different results. A method is proposed to combine local uncertainties predicted by different models to obtain a combined measure of uncertainty that combines good features of each alternative. The new estimator is the overlap of alternate conditional distributions.  相似文献   

Kriging with imprecise (fuzzy) variograms. I: Theory   总被引：2，自引：0，他引：2  

A. Bardossy  I. Bogardi  W. E. Kelly 《Mathematical Geology》1990,22(1):63-79

Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The accuracy of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create good experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data.  相似文献   

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1     

Jo R?islien  Henning Omre 《Mathematical Geology》2006,38(7):821-849

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.  相似文献   

Spatial and temporal variability of pore‐water pressures in residual soil slopes in a tropical climate     

R. B. Rezaur  H. Rahardjo  E. C. Leong 《地球表面变化过程与地形》2002,27(3):317-338

It is critical to understand and quantify the temporal and spatial variability in hillslope hydrological data in order to advance hillslope hydrological studies, evaluate distributed parameter hydrological models, analyse variability in hydrological response of slopes and design efficient field data sampling networks. The spatial and temporal variability of field‐measured pore‐water pressures in three residual soil slopes in Singapore was investigated using geostatistical methods. Parameters of the semivariograms, namely the range, sill and nugget effect, revealed interesting insights into the spatial structure of the temporal situation of pore‐water pressures in the slopes. While informative, mean estimates have been shown to be inadequate for modelling purposes, indicator semivariograms together with mean prediction by kriging provide a better form of model input. Results also indicate that significant temporal and spatial variability in pore‐water pressures exists in the slope profile and thereby induces variability in hydrological response of the slope. Spatial and temporal variability in pore‐water pressure decreases with increasing soil depth. The variability decreases during wet conditions as the slope approaches near saturation and the variability increases with high matric suction development following rainfall periods. Variability in pore‐water pressures is greatest at shallow depths and near the slope crest and is strongly influenced by the combined action of microclimate, vegetation and soil properties. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

Combining ordination techniques and geostatistics to determine the patterns of diatom distributions at Lake Lama, Central Siberia   总被引：4，自引：0，他引：4  

Ulrike Kienel  Thomas Kumke 《Journal of Paleolimnology》2002,28(2):181-194

The patterns of spatial variation of diatom assemblages from surface sediments in Lake Lama were quantified using a combined approach of ordination and geostatistics. The aims were (i) to estimate the amount of variation between diatom assemblages within the lake, (ii) to model the spatial variability of the diatom assemblages and their diversity, and (iii) to map the diatom distributions in the lake. A correspondence analysis (CA) separated the diatom assemblages into a planktonic and a periphytic group. Rheophilic taxa were found within the periphytic group. Variogram analysis showed that only the sample scores of the first CA axis and the Shannon diversity index were spatially structured. The range of spatial correlation was estimated to be 55 km for both variables. The diversity and, to a lesser extent, the sample scores had considerable small-scale variability of about 20 and 3%, respectively. Estimates of the first component of the CA and the Shannon index were derived using block-kriging. The maps of the estimates provided a basis for partitioning Lake Lama according to the spatial structures into an eastern and a western basin, a north–south connection between the basins, and a north–south directed tip at the far eastern end. It was shown that variation in diatom assemblages is mainly spatially structured at the catchment scale and that there is a considerable amount of variation at smaller scales. According to the modeled spatial distribution, the assemblages are most likely affected by the lake size, morphology, and the water and nutrient input introduced by rivers. This has to be taken into account when paleolimnological interpretations are drawn from records of complex lake systems like Lake Lama.  相似文献   

Disjunctive Kriging with Hard and Imprecise Data     

Xavier Emery 《Mathematical Geology》2003,35(6):699-718

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.  相似文献   

Dynamic stochastic estimation of physical variables   总被引：1，自引：0，他引：1  

George Christakos  Vijayanivas R. Raghu 《Mathematical Geology》1996,28(3):341-365

A fundamental problem facing the physical sciences today is analysis of natural variations and mapping of spatiotemporal processes. Detailed maps describing the space/time distribution of groundwater contaminants, atmospheric pollutant deposition processes, rainfall intensity variables, external intermittency functions, etc. are tools whose importance in practical applications cannot be overestimated. Such maps are valuable inputs for numerous applications including, for example, solute transport, storm modeling, turbulent-nonturbulent flow characterization, weather prediction, and human exposure to hazardous substances. The approach considered here uses the spatiotemporal random field theory to study natural space/time variations and derive dynamic stochastic estimates of physical variables. The random field model is constructed in a space/time continuum that explicitly involves both spatial and temporal aspects and provides a rigorous representation of spatiotemporal variabilities and uncertainties. This has considerable advantages as regards analytical investigations of natural processes. The model is used to study natural space/time variations of springwater calcium ion data from the Dyle River catchment area, Belgium. This dataset is characterized by a spatially nonhomogeneous and temporally nonstationary variability that is quantified by random field parameters, such as orders of space/time continuity and random field increments. A rich class of covariance models is determined from the properties of the random field increments. The analysis leads to maps of continuity orders and covariances reflecting space/time calcium ion correlations and trends. Calcium ion estimates and the associated statistical errors are calculated at unmeasured locations/instants over the Dyle region using a space/time kriging algorithm. In practice, the interpretation of the results of the dynamic stochastic analysis should take into consideration the scale effects.  相似文献