共查询到20条相似文献，搜索用时 736 毫秒
1.
Multifractal modelling and spectrum analysis: Methods and applications to gamma ray spectrometer data from southwestern Nova Scotia, Canada 总被引：1，自引：0，他引：1
CHENG Qiuming . State Key Lab of Geological Processes Mineral Resources China University of Geosciences Wuhan China . Department of Earth Space Science Engineering Department of Geography York University Keele Street Toronto Ontario MJ P Canada 《中国科学D辑(英文版)》2006,49(3):283-294
Multifractal theory was developed for handling scale invariant fields instead of geometry only[1―4]. From a multifractal point of view, some fractal models, ordinary physical processes and relevant probability distribution types can be considered as special cases of multifractal models which provides new insight into the interrelationships between systems and subjects. For example, the low order moment exponents τ (0), τ (1), τ (2) or τ ″(1) obtained by means of the moment method determi… 相似文献
2.
Climate extremes in South Western Siberia: past and future 总被引：1，自引：1，他引：0
Degefie T. Degefie Elisa Fleischer Otto Klemm Andrey V. Soromotin Olga V. Soromotina Andrey V. Tolstikov Nikolay V. Abramov 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(8):2161-2173
In this study, the temporal and spatial trends of ten climate extreme indices were computed based on observed daily precipitation and on daily maximum and minimum temperatures at 26 weather stations in South Western Siberia during the period 1969–2011 and, based on projected daily maximum and minimum temperatures, during 2021–2050. The Mann–Kendall test was employed to analyze the temporal trend and a combination of multiple linear regressions and semivariogram functions were used to evaluate the regional spatial trends and the local spatial variability of climate extremes, respectively. The results show that the temperature-based climate extremes increase at a 0.05 significance level while none of the precipitation-based climate extremes did. Spatially, dominant gradients are observed along latitude: The northern taiga vegetation zone experiences a colder and wetter climate while the southern forest steppe zone is drier and hotter. Over time, a tendency towards homogenization of the regional climate is observed through a decrease of the spatial variability for most climate extreme indices. In the future, the most intense changes are anticipated for the bio-climate indicators “growing season length” and “growing degree days” in the north, while the warming indicators, “warm day” and “warm night” are expected to be high to the south. 相似文献
3.
The variability of flow in river channels influences the spatial and temporal variability of many biophysical processes including the transport of sediment and waterborne pollutants and the recruitment of aquatic animals and plants. In this study, inter- and intra-basin patterns of flood variability are examined for catchments east of Australia’s Great Dividing Range. Three measures of flood variability are explored with uncertainty quantified using bootstrap resampling. The two preferred measures of flood variability (namely a flood quantile ratio and a power law scaling coefficient) produced similar results. Catchments in the wet tropics of far north Queensland experience low flood variability. Flood variability increased southwards through Queensland, reaching a maximum in the vicinity of the Fitzroy and Burnett River basins. The small near-coast catchments of southern Queensland and northern New Wales experience low flood variability. Flood variability is also high in the southern Hunter River and Hawkesbury–Nepean basins. Using L-moment ratio diagrams with data from 424 streamflow stations, we also conclude that the Generalised Pareto distribution is preferable for modelling flood frequency curves for this region. These results provide a regional perspective that can be used to develop new hypotheses about the effects of hydrologic variability on the biophysical characteristics of these Australian rivers. 相似文献
4.
Geostatistical estimation (kriging) and geostatistical simulation are routinely used in ground water hydrology for optimal spatial interpolation and Monte Carlo risk assessment, respectively. Both techniques are based on a model of spatial variability (semivariogram or covariance) that generally is not known but must be inferred from the experimental data. Where the number of experimental data is small (say, several tens), as is not unusual in ground water hydrology, the model fitted to the empirical semivariogram entails considerable uncertainty. If all the practical results are based on this unique fitted model, the final results will be biased. We propose that, instead of using a unique semivariogram model, the full range of models that are inside a given confidence region should be used, and the weight that each semivariogram model has on the final result should depend on its plausibility. The first task, then, is to evaluate the uncertainty of the model, which can be efficiently done by using maximum likelihood inference. The second task is to use the range of plausible models in applications and to show the effect observed on the final results. This procedure is put forth here with kriging and simulation applications, where the uncertainty in semivariogram parameters is propagated into the final results (e.g., the prediction of ground water head). A case study using log-transmissivity data from the Vega de Granada aquifer, in southern Spain, is given to illustrate the methodology. 相似文献
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Spatial variability of liquefaction potential in regional mapping using CPT and SPT data 总被引：5，自引：0，他引：5
Cone penetration test (CPT) and standard penetration test (SPT) are widely used for the site specific evaluation of liquefaction potential and are getting increased use in the regional mapping of liquefaction hazard. This paper compares CPT and SPT-based liquefaction potential characterizations of regional geologic units using the liquefaction potential index (LPI) across the East Bay of the San Francisco Bay, California, USA and examines the statistical and spatial variability of LPI across and within geologic units. Overall, CPT-based LPI characterizations result in higher hazard than those derived from the SPT. This bias may result from either mis-classifications of soil type in the CPT or a bias in the CPT simplified procedure for liquefaction potential. Regional mapping based on cumulative distribution of LPI values show different results depending on which dataset is used. For both SPT and CPT-based characterizations, the geologic units in the area have broad LPI distributions that overlap between units and are not distinct from the population as a whole. Regional liquefaction classifications should therefore give a distribution, rather than a single hazard rating that does not provide for variability within the area. The CPT-based LPI values have a higher degree of spatial correlation and a lower variance over a greater distance than those estimated from SPTs. As a result, geostatistical interpolation can provide a detailed map of LPI when densely sampled CPT data are available. The statistical distribution of LPI within specific geologic units and interpolated maps of LPI can be used to understand the spatial variability of liquefaction potential. 相似文献
8.
This work aims to present new modeling tools that help to better monitor and predict the groundwater level in sparsely gauged basins. The working area is the Mires basin of Mesara valley in the island of Crete (Greece). Efficient groundwater management in the basin is crucial in light of regional climate change model estimates showing a substantial risk of desertification for Crete. We propose that the prediction of the hydraulic head spatial variability in Mires basin can be improved by incorporating in the trend the distance of the prediction points from a temporary river crossing the basin and a component based on the generalized Thiem’s equation for multiple wells as well as using the flexible Spartan semivariogram family to perform Residual Kriging. Our proposal is supported by the results of cross validation analysis. Our results are applicable to other unconfined aquifers. 相似文献
9.
Design flood estimates for a given return period are required in both gauged and ungauged catchments for hydraulic design and risk assessments. Contrary to classical design estimates, synthetic design hydrographs provide not only information on the peak magnitude of events but also on the corresponding hydrograph volumes together with the hydrograph shapes. In this study, we tested different regionalization approaches to transfer parameters of synthetic design hydrographs from gauged to ungauged catchments. These approaches include classical regionalization methods such as linear regression techniques, spatial methods, and methods based on the formation of homogeneous regions. In addition to these classical approaches, we tested nonlinear regression models not commonly used in hydrological regionalization studies, such as random forest, bagging, and boosting. We found that parameters related to the magnitude of the design event can be regionalized well using both linear and nonlinear regression techniques using catchment area, length of the main channel, maximum precipitation intensity, and relief energy as explanatory variables. The hydrograph shape, however, was found to be more difficult to regionalize due to its high variability within a catchment. Such variability might be better represented by looking at flood-type specific synthetic design hydrographs. 相似文献
10.
Assessment of rainfall spatial variability and its influence on runoff modelling: A case study in the Brue catchment,UK 
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下载免费PDF全文 This study explores rainfall spatial variability and its influence on runoff modelling. A novel assessment scheme integrated with coefficient of variance and Moran's I is introduced to describe effective rainfall spatial variability. Coefficient of variance is widely accepted to identify rainfall variability through rainfall intensity, whereas Moran's I reflects rainfall spatial autocorrelation. This new assessment framework combines these two indicators to assess the spatial variability derived from both rainfall intensity and distribution, which are crucial in determining the time and magnitude of runoff generation. Four model structures embedded in the Variable Infiltration Capacity model are adopted for hydrological modelling in the Brue catchment of England. The models are assigned with 1, 3, 8, and 27 hydrological response units, respectively, and diverse rainfall spatial information for 236 events are extracted from 1995. This study investigates the model performance of different partitioning based on rainfall spatial variability through peak volume (Qp) and time to peak (Tp), along with the rainfall event process. The results show that models associated with dense spatial partitioning are broadly capable of capturing more spatial information with better performance. It is unnecessary to utilize models with high spatial density for simple rainfall events, though they show distinct advantages on complex events. With additional spatial information, Qp experiences a notable improvement over Tp. Moreover, seasonal patterns signified by the assessment scheme imply the feasibility of seasonal models. 相似文献
11.
Ryan M. Pollyea Jerry P. Fairley Robert K. Podgorney Travis L. McLing 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(7):1735-1740
The stochastic continuum (SC) representation is one common approach for simulating the effects of fracture heterogeneity in groundwater flow and transport models. These SC reservoir models are generally developed using geostatistical methods (e.g., kriging or sequential simulation) that rely on the model semivariogram to describe the spatial variability of each continuum. Although a number of strategies for sampling spatial distributions have been published in the literature, little attention has been paid to the optimization of sampling in resource- or access-limited environments. Here we present a strategy for estimating the minimum sample spacing needed to define the spatial distribution of fractures on a vertical outcrop of basalt, located in the Box Canyon, east Snake River Plain, Idaho. We used fracture maps of similar basalts from the published literature to test experimentally the effects of different sample spacings on the resulting semivariogram model. Our final field sampling strategy was based on the lowest sample density that reproduced the semivariogram of the exhaustively sampled fracture map. Application of the derived sampling strategy to an outcrop in our field area gave excellent results, and illustrates the utility of this type of sample optimization. The method will work for developing a sampling plan for any intensive property, provided prior information for a similar domain is available; for example, fracture maps or ortho-rectified photographs from analogous rock types could be used to plan for sampling of a fractured rock outcrop. 相似文献
12.
Prasanna Venkatesh Sampath Hua‐Sheng Liao Zachary Kristopher Curtis Matthew E. Herbert Patrick J. Doran Christopher A. May Douglas A. Landis Shu‐Guang Li 《水文研究》2016,30(19):3390-3407
Fens, which are among the most biodiverse of wetland types in the USA, typically occur in glacial landscapes characterized by geo‐morphologic variability at multiple spatial scales. As a result, the hydrologic systems that sustain fens are complex and not well understood. Traditional approaches for characterizing such systems use simplifying assumptions that cannot adequately capture the impact of variability in geology and topography. In this study, a hierarchical, multi‐scale groundwater modelling approach coupled with a geologic model is used to understand the hydrology of a fen in Michigan. This approach uses high‐resolution data to simulate the multi‐scale topographic and hydrologic framework and lithologic data from more than 8500 boreholes in a statewide water well database to capture the complex geology. A hierarchy of dynamically linked models is developed that simulates groundwater flow at all scales of interest and to delineate the areas that contribute groundwater to the fen. The results show the fen receiving groundwater from multiple sources: an adjacent wetland, local recharge, a nearby lake and a regional groundwater mound. Water from the regional mound flows to an intermediate source before reaching the fen, forming a ‘cascading’ connection, while other sources provide water through ‘direct’ connections. The regional mound is also the source of water to other fens, streams and lakes in this area, thus creating a large, interconnected hydrologic system that sustains the entire ecosystem. In order to sustainably manage such systems, conservation efforts must include both site‐based protection and management, as well as regional protection and management of groundwater source areas. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
13.
Lacustrine groundwater discharge (LGD) can be an important pathway for delivering pollutants to lakes but this pathway is often poorly characterized. Evaluating the potential impact of LGD on lake water quality requires understanding the magnitude and spatial variability of LGD, as well as understanding the age and flow paths of the discharging groundwater (e.g., recharge area, groundwater flow paths, and travel times). This study first compares LGD rates along two ~40 km shoreline lengths of a large glacial lake, Lake Simcoe, Canada, that were independently estimated via a radon-222 (222Rn) field survey and via regional scale groundwater-surface water modelling. Backward particle tracking analysis is then used to examine the age and flow paths of the LGD and thereby assess the potential for the LGD to deliver anthropogenic pollutants to the lake. The field and modelling results compare well with respect to the magnitude and spatial variability of LGD. However, the comparison highlights the need for well-defined hydrogeological characterization if regional scale models are to be applied for LGD estimation. The particle tracking analysis indicates large variation in the groundwater flow path lengths and travels times (>1000 years to <50 years) for LGD along the shoreline. This illustrates that the LGD along different shoreline areas has varying potential to deliver anthropogenic pollutants to the lake. The study findings demonstrate the benefits of comparing independent field measured and model-simulated LGD estimates, and moreover suggest that it may be possible, in some cases, to use existing regional scale groundwater-surface water models, purpose-built for other water resource and quality objectives, to conduct preliminary evaluation of LGD contributions to lakes. Preliminary model-based evaluation would enable field efforts aiming to quantify and manage LGD to be better targeted rather than relying solely on regional scale field techniques that are often highly resource intensive. 相似文献
14.
Long-term time-dependent stochastic modelling of extreme waves 总被引：4，自引：3，他引：1
Erik Vanem 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(2):185-209
This paper presents a literature survey on time-dependent statistical modelling of extreme waves and sea states. The focus
is twofold: on statistical modelling of extreme waves and space- and time-dependent statistical modelling. The first part
will consist of a literature review of statistical modelling of extreme waves and wave parameters, most notably on the modelling
of extreme significant wave height. The second part will focus on statistical modelling of time- and space-dependent variables
in a more general sense, and will focus on the methodology and models used also in other relevant application areas. It was
found that limited effort has been put on developing statistical models for waves incorporating spatial and long-term temporal
variability and it is suggested that model improvements could be achieved by adopting approaches from other application areas.
In particular, Bayesian hierarchical space–time models were identified as promising tools for spatio-temporal modelling of
extreme waves. Finally, a review of projections of future extreme wave climate is presented. 相似文献
15.
It is well known that snow plays an important role in land surface energy balance; however, modelling the subgrid variability of snow is still a challenge in large‐scale hydrological and land surface models. High‐resolution snow depth data and statistical methods can reveal some characteristics of the subgrid variability of snow depth, which can be useful in developing models for representing such subgrid variability. In this study, snow depth was measured by airborne Lidar at 0.5‐m resolution over two mountainous areas in south‐western Wyoming, Snowy Range and Laramie Range. To characterize subgrid snow depth spatial distribution, measured snow depth data of these two areas were meshed into 284 grids of 1‐km × 1‐km. Also, nine representative grids of 1‐km × 1‐km were selected for detailed analyses on the geostatistical structure and probability density function of snow depth. It was verified that land cover is one of the important factors controlling spatial variability of snow depth at the 1‐km scale. Probability density functions of snow depth tend to be Gaussian distributions in the forest areas. However, they are eventually skewed as non‐Gaussian distribution, largely due to the no‐snow areas effect, mainly caused by snow redistribution and snow melt. Our findings show the characteristics of subgrid variability of snow depth and clarify the potential factors that need to be considered in modelling subgrid variability of snow depth. 相似文献
16.
The spatial variability of each parameter affecting storm runoff must be accounted for in distributed modelling. The objective of the work reported here is to assess the effects of using distributed versus lumped hydraulic roughness coefficients in the modelling of direct surface runoff. A spatially variable data set composed of Manning roughness coefficients is used to model direct surface runoff. To assess the information content (as measured by entropy) of spatially variable data and its significance in distributed modelling, various degrees of smoothing are applied. The error resulting from smoothing the hydraulic roughness coefficients is determined by modelling overland flow using a finite element solution. The Manning roughness coefficients were taken from field measurements of the Manning roughness coefficient at 0.6 m on a 14 m hillslope. These values were then used in a numerical simulation of outflow hydrographs to investigate the dependence of error on spatial variability. Our study focuses on the characteristics of spatial data used in distributed hydrological modelling. The field sites have fractal dimensions of ≈? 1.4, which is close to a Brownian variation. The sampling interval that captures the essential spatial variability of the Manning roughness coefficient does not seem to matter due to its Brownian variation in the field sites. Hence due to the nearly uniform random distribution, measurements at 0.6 m intervals are not necessary and larger intervals would yield results that are just as acceptable provided the mean value together with a uniformly random distribution is maintained for any size of finite element or sampling resolution. Because detailed measurements of hydraulic roughness are not practically available for deterministic catchment modelling, it is important to know that larger sampling resolutions may be used than 0.6 m. 相似文献
17.
Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
18.
In this paper, a technique is proposed in order to study triple time series. It combines the variable of interest, sulfur
dioxide (SO2) with two related meteorological variables. Hence, three variables measured at the same time points are jointly analyzed.
Instead of using classical multiple time series analysis, it is suggested to consider the measurements of the two meteorological
variables as coordinates of a two-dimensional space and the simultaneous observation of the third variable (associated SO2 concentrations) at each pair of coordinates. Subsequently, well-known optimum interpolation is used for predicting the SO2 concentrations on the basis of six meteorological variables. All the variables of the study are measured at the same times
(all days in 2000) around the city of Istanbul, Turkey. The triple diagrams, in the form of contour maps, help to answer various
questions concerning the SO2 concentration variability with respect to meteorological variables. The same diagrams also provide a basis for the prediction
of SO2 concentrations. It is shown that the relative prediction error is less than 10%, which is acceptable for the practical studies. 相似文献
19.
In watershed modelling, the traditional practice of arbitrarily filling topographic depressions in digital elevation models has raised concerns. Advanced high‐resolution remote sensing techniques, including airborne scanning laser altimetry, can identify naturally occurring depressions that impact overland flow. In this study, we used an ensemble physical and statistical modelling approach, including a 2D hydraulic model and two‐point connectivity statistics, to quantify the effects of depressions on high‐resolution overland flow patterns across spatial scales and their temporal variations in single storm events. Computations for both models were implemented using graphic processing unit‐accelerated computing. The changes in connectivity statistics for overland flow patterns between airborne scanning laser altimetry‐derived digital elevation models with (original) and without (filled) depressions were used to represent the shifts of overland flow response to depressions. The results show that depressions can either decrease or increase (to a lesser degree and shorter duration) the probability that any two points (grid locations) are hydraulically connected by overland flow pathways. We used macro‐connectivity states (Φ) as a watershed‐specific indicator to describe the spatiotemporal thresholds of connectivity variability caused by depressions. Four states of Φ are identified in a studied watershed, and each state represents different magnitudes of connectivity and connectivity changes (caused by depressions). The magnitude of connectivity variability corresponds to the states of Φ, which depend on the topological relationship between depressions, the rising/recession limb, and the total rainfall amount in a storm event. In addition, spatial distributions of connectivity variability correlate with the density of depression locations and their physical structures, which cause changes in streamflow discharge magnitude. Therefore, this study suggests that depressions are “nontrivial” in watershed modelling, and their impacts on overland flow should not be neglected. Connectivity statistics at different spatial scales and time points within a watershed provide new insights for characterizing the distributed and accumulated effects of depressions on overland flow. 相似文献
20.
ABSTRACTEvapotranspiration (ET) is one of the most important components in the hydrological cycle, and a key variable in hydrological modelling and water resources management. However, understanding the impacts of spatial variability in ET and the appropriate scale at which ET data should be incorporated into hydrological models, particularly at the regional scale, is often overlooked. This is in contrast to dealing with the spatial variability in rainfall data where existing guidance is widely available. This paper assesses the impacts of scale on the estimation of reference ET (ETo) by comparing data from individual weather stations against values derived from three national datasets, at varying resolutions. These include the UK Climate Impacts Programme 50 km climatology (UKCP50), the UK Met Office 5 km climatology (UKMO5) and the regional values published in the Agricultural Climate of England and Wales (ACEW). The national datasets were compared against the individual weather station data and the UKMO5 was shown to provide the best estimate of ETo at a given site. The potential impacts on catchment modelling were then considered by mapping variance in ETo to show how geographical location and catchment size can have a major impact, with small lowland catchments having much higher variance than those with much larger areas or in the uplands. Some important implications for catchment hydrological modelling are highlighted.
Editor D. Koutsoyiannis; Associate editor L. Ruiz 相似文献