Combined analytical solution of overland flow and sediment transport

With reference to the kinematic wave theory coupled with the hypothesis of constant linear velocity for the rating curve, rising limb analytical solutions have been calculated for overland flow, over an Hortonian-infiltrating surface, and sediment discharge. These analytical solutions are certainly easier to use than the numerical integration of the basic equations and they may be used to obtain an initial evaluation of the parameters of more complex models generally devised for complicated cases.Notation a exponent of the Horton law [T^–1] - b exponent of the rill erosion equation - B inter-rill erosion coefficient [ML^–m–2T ^m–1] - c sediment concentration [ML^–3] - c _o reference sediment concentration [ML^–3] - E _I inter-rill erosion [ML^–2T^–1] - E _R rill erosion [ML^–2T^–1] - f _c final infiltration rate of the soil [LT^–1] - f _o initial infiltration rate of the soil [LT^–1] - h flow depth [L] - h _o reference flow depth [L] - i infiltration rate [LT^–1] - k rill erosion coefficient [ML^–1–b T^–1] - K integration constant - L() Laplace transformation - m exponent of the inter-rill erosion equation - n Manning's coefficient [L^–1/3T] - p rainfall intensity [LT^–1] - q water discharge per unit width [L²T^–1] - q _s sediment discharge per unit width [ML^–1T^–1] - t time [T] - t _p ponding time [T] - x distance along the flow direction [L] Greek Letters coefficient of the stage-discharge equation [L^2–T^–1] - exponent of the stage-discharge equation - rill erosion coefficient [L^–1]     

Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations,climates and methods of analysis on model sensitivity to crop parameters

Sensitivity analysis studies how the variation in model outputs can be due to different sources of variation. This issue is addressed, in this study, as an application of sensitivity analysis techniques to a crop model in the Mediterranean region. In particular, an application of Morris and Sobol' sensitivity analysis methods to the rice model WARM is presented. The output considered is aboveground biomass at maturity, simulated at five rice districts of different countries (France, Greece, Italy, Portugal, and Spain) for years characterized by low, intermediate, and high continentality. The total effect index of Sobol' (that accounts for the total contribution to the output variation due a given parameter) and two Morris indices (mean μ and standard deviation σ of the ratios output changes/parameter variations) were used as sensitivity metrics. Radiation use efficiency (RUE), optimum temperature (T_opt), and leaf area index at emergence (LAI_ini) ranked in most of the combinations site × year as first, second and third most relevant parameters. Exceptions were observed, depending on the sensitivity method (e.g. LAI_ini resulted not relevant by the Morris method), or site-continentality pattern (e.g. with intermediate continentality in Spain, LAI_ini and T_opt were second and third ranked; with low continentality in Portugal, RUE was outranked by T_opt). Low σ values associated with the most relevant parameters indicated limited parameter interactions. The importance of sensitivity analyses by exploring site × climate combinations is discussed as pre-requisite to evaluate either novel crop-modelling approaches or the application of known modelling solutions to conditions not explored previously. The need of developing tools for sensitivity analysis within the modelling environment is also emphasized.     

A heuristic approach for packing identical rectangles in convex regions

In this paper we propose a heuristic approach for the problem of packing equal rectangles within a convex region. The approach is based on an Iterated Local Search scheme, in which the key step is the perturbation move. Different perturbation moves, both combinatorial and continuous ones, are proposed and compared through extensive computational experiments on a set of test instances. The overall results are quite encouraging.     

Numerical identification of a nonlinear diffusion coefficient by discrete mollification

The discrete mollification method is a convolution-based filtering procedure suitable for the regularization of ill-posed problems. Combined with explicit space-marching finite difference schemes, it provides stability and convergence for a variety of coefficient identification problems in linear parabolic equations. In this paper, we extend such a technique to identify some nonlinear diffusion coefficients depending on an unknown space dependent function in one dimensional parabolic models. For the coefficient recovery process, we present detailed error estimates and to illustrate the performance of the algorithms, several numerical examples are included.     

A protocol for the ranking of interpolation algorithms based on confidence levels

The choice of the best interpolation algorithm of data gathered at a finite number of locations has been a persistently relevant topic. Typical papers take a single data set, a single set of data points, and a handful of algorithms. The process considers a subset I of the data points as known, builds the interpolant with each algorithm, applies it to the points of another subset C, and evaluates the MAE (mean absolute error), the RMSE (root mean square error), or any other metric over such points. The less these statistics are, the better the algorithm is, so a deterministic ranking between methods (without confidence level) can be derived based upon it. Ties between methods are usually not considered. In this article a complete protocol is proposed in order to build, with a modest additional effort, a ranking with a confidence level. To illustrate this point, the results of two tests are shown. In the first one, a simple Monte Carlo experiment was devised using irregularly distributed points taken from a reference DEM (digital elevation model) in raster format. Different metrics led to different rankings, suggesting that the choice of the metric to define the ‘best interpolation algorithm’ would need a trade-off. The second experiment used mean daily radiation data from an international interpolation comparison exercise and RMSE as the metric of success. Only five simple interpolation methods were employed. The ranking using this protocol anticipated correctly the first and second place, afterwards confirmed employing independent control data.     

Analyzing execution traces: critical-path analysis and distance analysis

International Journal on Software Tools for Technology Transfer - System designers make trade-offs between metrics of interest such as execution time, functional quality and cost to create a...     

Learning vector quantization with training data selection

In this paper, we propose a method that selects a subset of the training data points to update LVQ prototypes. The main goal is to conduct the prototypes to converge at a more convenient location, diminishing misclassification errors. The method selects an update set composed by a subset of points considered to be at the risk of being captured by another class prototype. We associate the proposed methodology to a weighted norm, instead of the Euclidean, in order to establish different levels of relevance for the input attributes. The technique was implemented on a controlled experiment and on Web available data sets.     

Near-infrared photodetection with a diruthenium complex having redox-switchable wavelength response

We report on the electrochromic behavior of a dinuclear ruthenium complex, which provides high environmental stability together with an intense absorption maximum at 1237 nm in solution in its +3 oxidation state. To verify its optoelectronic properties, we used this complex as the photoactive material in a planar photodetector prototype for near-infrared light pulses, succeeding in the detection of a train of light pulses at a wavelength of 1280 nm.