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A discontinuous finite element suspended sediment transport model for water quality assessments in river networks 
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下载免费PDF全文 Suspended sediment plays an important role in the distribution and transport of many pollutants (such as radionuclides) in rivers. Pollutants may adsorb on fine suspended particles (e.g. clay) and spread according to the suspended sediment movement. Hence, the simulation of the suspended sediment mechanism is indispensable for realistic transport modelling. This paper presents and tests a simple mathematical model for predicting the suspended sediment transport in river networks. The model is based on the van Rijn suspended load formula and the advection–diffusion equation with a source or sink term that represents the erosion or deposition fluxes. The transport equation is solved numerically with the discontinuous finite element method. The model evaluation was performed in two steps, first by comparing model simulations with the measured suspended sediment concentrations in the Grote Nete–Molse Nete River in Belgium, and second by a model intercomparison with the sediment transport model NST MIKE 11. The simulations reflect the measurements with a Nash‐Sutcliffe model efficiency of 0.6, while the efficiency between the proposed model and the NST MIKE 11 simulations is 0.96. Both evaluations indicate that the proposed sediment transport model, that is sufficiently simple to be practical, is providing realistic results. 相似文献
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Some natural substrates record environmental information and, as such, provide a means to reconstruct the environmental conditions
from the period these substrates were formed. Samples from environmental archives are not always equally spaced in distance.
When a periodic time series model is estimated from these unequally spaced proxy records, the search for reasonable starting
values is the main difficulty. In this work, a non-parametric method based on the regressive Fourier series is first presented,
which reduces averaging errors starting from unequally spaced records. The method is applied to synthetic data and generally
performs well in all circumstances. Secondly, a parametric method for the construction of a time base and the elimination
of averaging errors from unequally spaced records is presented. This parametric method uses the non-parametric method to produce
starting values for the parameters. The method is compared with the time series construction method with the averaging effect
taken into account and it is observed that only the current method produces acceptable results. The statistical performance
of the method is verified with a Monte Carlo simulation and the estimator is proven to be an efficient estimator. The applicability
of the method is demonstrated on the vessel density measurement in a mangrove tree, Rizophora mucronata, which is a proxy for the rainfall in tropical coastal regions. 相似文献
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Veerle Beelaerts Maite Bauwens Emma Versteegh Frank Dehairs Rik Pintelon 《Mathematical Geosciences》2011,43(6):635-662
Identifying a periodic time-series model from environmental records, without imposing the positivity of the growth rate, does
not necessarily respect the time order of the data observations. Consequently, subsequent observations, sampled in the environmental
archive, can be inversed on the time axis, resulting in a non-physical signal model. In this paper an optimization technique
with linear constraints on the signal model parameters is proposed that prevents time inversions. The activation conditions
for this constrained optimization are based upon the physical constraint of the growth rate, namely, that it cannot take values
smaller than zero. The actual constraints are defined for polynomials and first-order splines as basis functions for the nonlinear
contribution in the distance-time relationship. The method is compared with an existing method that eliminates the time inversions,
and its noise sensitivity is tested by means of Monte Carlo simulations. Finally, the usefulness of the method is demonstrated
on the measurements of the vessel density, in a mangrove tree, Rhizophora mucronata, and the measurement of Mg/Ca ratios, in a bivalve, Mytilus trossulus. 相似文献
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On the Elimination of Bias Averaging-Errors in Proxy Records 总被引：2，自引：2，他引：0
Veerle Beelaerts Fjo De Ridder Nele Schmitz Maite Bauwens Frank Dehairs Johan Schoukens Rik Pintelon 《Mathematical Geosciences》2009,41(2):129-144
Knowledge of and insight into past environmental conditions can be obtained by processing and analyzing proxies. The proxies
need to be processed as precisely and accurately as possible, otherwise the conclusion of the analysis will be biased. A calibration
method which reduces bias errors in the proxy measurements due to averaging is presented. Sampling with nonzero sample sizes
causes an averaging of the true proxy signal over the volume of the sample. The method is applied on a linear synthetic record
which results in an optimal correction for frequency components ranging from the dc-frequency (DC) to one half of the sample
frequency (f
s
/2). Next, the method is tested on non-linear synthetic data where the signal is reconstructed reasonably well. Finally, the
method is applied to a real vessel density record of R.
mucronata from Makongeni, Kenya, and to a real delta deuterium record of ice core EDC from dome C, Antarctica. The method discussed
in this paper is a valuable tool for the calibration of proxy measurements; it can be applied as a correction for low resolution
measurements and expanded to other types of samples and proxies. Working with small sample sizes (high resolution) amounts
to working near the detection limit, where the signal-to-noise-ratio is low. This correction method provides an alternative
in which low resolution measurements can be upgraded to minimize the loss of information due to larger sample sizes. 相似文献
5.
Time-Series Reconstruction from Natural Archive Data with the Averaging Effect Taken into Account 总被引：2，自引：2，他引：0
Veerle Beelaerts Fjo De Ridder Nele Schmitz Maite Bauwens Rik Pintelon 《Mathematical Geosciences》2010,42(6):705-722
Environmental information of the past can be obtained by processing and analyzing proxies recorded by environmental archives.
Natural archives are sampled at a distance grid along their accretion axis. Starting from these distance series, a time series
needs to be constructed, because comparison of different data records is only meaningful on a time grid. However, distance–time
relationships are nonlinear as the accretion rate of natural archives is dependent on environmental and physiological factors.
Furthermore, in environmental archives, samples are taken over a volume in distance, rather than over a point in distance.
This implies that the sample-values will be averaged over the volume of the sample. In this paper a method is proposed, which
establishes the nonlinear distance–time relationship and corrects for the averaging effects. The method is built upon the
assumption that the proxy record on a time axis is harmonic. If this is not the case, then a harmonic approximation is made.
As a consequence of the nonlinear distance–time relationship, this harmonic proxy signal is nonlinearly distorted on a distance
axis. As such, a harmonic signal model with a nonlinear phase distortion and an averaging effect is fitted on the data. Since
environmental records are short data records, the statistical performance of the estimator on noisy data is verified by means
of Monte Carlo simulations. The applicability of the method is demonstrated on the measurement of the vessel density, in a
mangrove tree, Rhizophora mucronata, which is an indicator of the rainfall in tropical coastal ecosystems. 相似文献
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Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium 总被引：1，自引：0，他引：1
Sara Verbeiren Herman Eerens Isabelle Piccard Ides Bauwens Jos Van Orshoven 《International Journal of Applied Earth Observation and Geoinformation》2008,10(4):486
Global time series of low resolution images are available with high repeat frequency and at low cost, but their analysis is hampered by the presence of mixed pixels and the difficulty in locating detailed spatial features. This study examined the potential of sub-pixel classification for regional crop area estimation using time series of monthly NDVI-composites of the 1 km resolution sensor SPOT-VEGETATION. Belgium was selected as test zone, because of the availability of ample reference data in the form of a vectorial GIS with the boundaries and cover type of the large majority of agricultural fields. Two different methods were investigated: the linear mixture model and neural networks. Both result in area fraction images (AFIs), which contain for each 1 km pixel the estimated area proportions occupied by the different cover types (crops or other land use). Both algorithms were trained with part of the reference data and validated with the remainder. Validation was repeated at three different levels: the 1 km pixel, the municipality and the agro-statistical district. In general, the neural network outperformed the linear mixture model. For the major classes (winter wheat, maize, forest) the obtained acreage estimates showed good agreement with the true values, especially when aggregated to the level of the municipality (R2 ≈ 85%) or district (R2 ≈ 95%). The method seems attractive for wide-scale, regional area estimation in data-poor countries. 相似文献
7.
Befekadu?Taddesse?WoldegiorgisEmail authorView author&#;s OrcID profile Fu-Chun?Wu Ann?Van?Griensven Willy?Bauwens 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1771-1782
This paper presents a heuristic probabilistic approach to estimating the size-dependent mobilities of nonuniform sediment based on the pre- and post-entrainment particle size distributions (PSDs), assuming that the PSDs are lognormally distributed. The approach fits a lognormal probability density function to the pre-entrainment PSD of bed sediment and uses the threshold particle size of incipient motion and the concept of sediment mixture to estimate the PSDs of the entrained sediment and post-entrainment bed sediment. The new approach is simple in physical sense and significantly reduces the complexity and computation time and resource required by detailed sediment mobility models. It is calibrated and validated with laboratory and field data by comparing to the size-dependent mobilities predicted with the existing empirical lognormal cumulative distribution function approach. The novel features of the current approach are: (1) separating the entrained and non-entrained sediments by a threshold particle size, which is a modified critical particle size of incipient motion by accounting for the mixed-size effects, and (2) using the mixture-based pre- and post-entrainment PSDs to provide a continuous estimate of the size-dependent sediment mobility. 相似文献
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