21,791 research outputs found
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The impact of uncertainty in satellite data on the assessment of flood inundation models
The performance of flood inundation models is often assessed using satellite observed data; however these data have inherent uncertainty. In this study we assess the impact of this uncertainty when calibrating a flood inundation model (LISFLOOD-FP) for a flood event in December 2006 on the River Dee, North Wales, UK. The flood extent is delineated from an ERS-2 SAR image of the event using an active contour model (snake), and water levels at the flood margin calculated through intersection of the shoreline vector with LiDAR topographic data. Gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. Residuals between the satellite observed data points and those from the reference line are spatially clustered into groups of similar values. We show that model calibration achieved using pattern matching of observed and predicted flood extent is negatively influenced by this spatial dependency in the data. By contrast, model calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present.
To test the impact of removing spatial dependency a new method of evaluating flood inundation model performance is developed by using multiple random subsamples of the water surface elevation data points. By testing for spatial dependency using Moran’s I, multiple subsamples of water elevations that have no significant spatial dependency are selected. The model is then calibrated against these data and the results averaged. This gives a near identical result to calibration using spatially dependent data, but has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Moreover, by using the variations found in the subsamples of the observed data it is possible to assess the effects of observational uncertainty on the assessment of flooding risk
Validation of a model of regulation in the tryptophan operon against multiple experiment data using global optimisation
This paper is concerned with validating a mathematical model of regulation in the tryptophan operon using global optimization. Although a number of models for this biochemical network are proposed, in many cases only qualitative agreement between the model output and experimental data was demonstrated, since very little information is currently available to guide the selection of parameter values for the models. This paper presents a model validating method using both multiple experimental data and global optimization
Least-squares methods for identifying biochemical regulatory networks from noisy measurements
<b>Background</b>:
We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS). The Total Least Squares (TLS) technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks.
<b>Results</b>:
The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and <i>mdm2</i> messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL)-6 and (IL)-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL)-6 and (IL)-12b by ATF3.
<b>Conclusion</b>:
The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable more accurate and reliable identification and modelling of biochemical networks
Finite to infinite steady state solutions, bifurcations of an integro-differential equation
We consider a bistable integral equation which governs the stationary
solutions of a convolution model of solid--solid phase transitions on a circle.
We study the bifurcations of the set of the stationary solutions as the
diffusion coefficient is varied to examine the transition from an infinite
number of steady states to three for the continuum limit of the
semi--discretised system. We show how the symmetry of the problem is
responsible for the generation and stabilisation of equilibria and comment on
the puzzling connection between continuity and stability that exists in this
problem
Emergence of steady and oscillatory localized structures in a phytoplankton-nutrient model
Co-limitation of marine phytoplankton growth by light and nutrient, both of
which are essential for phytoplankton, leads to complex dynamic behavior and a
wide array of coherent patterns. The building blocks of this array can be
considered to be deep chlorophyll maxima, or DCMs, which are structures
localized in a finite depth interior to the water column. From an ecological
point of view, DCMs are evocative of a balance between the inflow of light from
the water surface and of nutrients from the sediment. From a (linear)
bifurcational point of view, they appear through a transcritical bifurcation in
which the trivial, no-plankton steady state is destabilized. This article is
devoted to the analytic investigation of the weakly nonlinear dynamics of these
DCM patterns, and it has two overarching themes. The first of these concerns
the fate of the destabilizing stationary DCM mode beyond the center manifold
regime. Exploiting the natural singularly perturbed nature of the model, we
derive an explicit reduced model of asymptotically high dimension which fully
captures these dynamics. Our subsequent and fully detailed study of this model
- which involves a subtle asymptotic analysis necessarily transgressing the
boundaries of a local center manifold reduction - establishes that a stable DCM
pattern indeed appears from a transcritical bifurcation. However, we also
deduce that asymptotically close to the original destabilization, the DCM
looses its stability in a secondary bifurcation of Hopf type. This is in
agreement with indications from numerical simulations available in the
literature. Employing the same methods, we also identify a much larger DCM
pattern. The development of the method underpinning this work - which, we
expect, shall prove useful for a larger class of models - forms the second
theme of this article
Probing a non-biaxial behavior of infinitely thin hard platelets
We give a criterion to test a non-biaxial behavior of infinitely thin hard
platelets of symmetry based upon the components of three order
parameter tensors. We investigated the nematic behavior of monodisperse
infinitely thin rectangular hard platelet systems by using the criterion.
Starting with a square platelet system, and we compared it with rectangular
platelet systems of various aspect ratios. For each system, we performed
equilibration runs by using isobaric Monte Carlo simulations. Each system did
not show a biaxial nematic behavior but a uniaxial nematic one, despite of the
shape anisotropy of those platelets. The relationship between effective
diameters by simulations and theoretical effective diameters of the above
systems was also determined.Comment: Submitted to JPS
Longtime behavior of nonlocal Cahn-Hilliard equations
Here we consider the nonlocal Cahn-Hilliard equation with constant mobility
in a bounded domain. We prove that the associated dynamical system has an
exponential attractor, provided that the potential is regular. In order to do
that a crucial step is showing the eventual boundedness of the order parameter
uniformly with respect to the initial datum. This is obtained through an
Alikakos-Moser type argument. We establish a similar result for the viscous
nonlocal Cahn-Hilliard equation with singular (e.g., logarithmic) potential. In
this case the validity of the so-called separation property is crucial. We also
discuss the convergence of a solution to a single stationary state. The
separation property in the nonviscous case is known to hold when the mobility
degenerates at the pure phases in a proper way and the potential is of
logarithmic type. Thus, the existence of an exponential attractor can be proven
in this case as well
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Using airborne laser altimetry to improve river flood extents delineated from SAR data
Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data
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