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A Kalman filter application to a spectral wave model     Kalman filter  spectral wave model       font style='font-size:12px;'> 2009/11/11
A sequential time dependent data assimilation scheme based on the Kalman filter is applied to a spectral wave model. Usually, the first guess covariance matrices used in optimal interpolation schemes ...
Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series an...
The ability to detect the chaotic signal from a finite time series observation of hydrologic systems is addressed in this paper. The presence of random and seasonal components in hydrological time ser...
Many evidences of oscillations accompanying the acceleration of critical systems have been reported. These oscillations are usually related to discrete scale invariance properties of the systems and e...
An efficient class of nonlinear models, constructed using cardinal B-spline (CBS) basis functions, are proposed for high tide forecasts at the Venice lagoon. Accurate short term predictions of high ti...
In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountai...
Spatial dependences among precipitation maxima over Belgium     Spatial dependences  precipitation maxima  Belgium       font style='font-size:12px;'> 2009/11/3
For a wide range of applications in hydrology, the probability distribution of precipitation maxima represents a fundamental quantity to build dykes, propose flood planning policies, or more generally...
We use multifractal analysis to estimate the Rényi dimensions of river basins by two different partition methods. These methods differ in the way that the Euclidian plane support of the measure is cov...
The transformation of nonlinear long internal waves in a two-layer fluid is studied in the Boussinesq and rigid-lid approximation. Explicit analytic formulation of the evolution equation in terms of t...
Meteorological uncertainty and rainfall downscaling     Meteorological uncertainty  rainfall downscaling       font style='font-size:12px;'> 2009/11/3
We explore the sources of forecast uncertainty in a mixed dynamical-stochastic ensemble prediction chain for small-scale precipitation, suitable for hydrological applications. To this end, we apply th...
We study numerically the comparison between Lagrangian experiments on turbulent particle dispersion in 2-D turbulent flows performed, on the one hand, on the basis of direct numerical simulations (DNS...
The complexity of the daily pluviometric regime of the Iberian Peninsula is analysed from the point of view of its lacunarity, predictability and predictive instability. The database consists of daily...
In this study, we report results from scaling analysis of 2.5 m spatial and 1 s temporal resolution lidar-rainfall data. The high resolution spatial and temporal data from the same observing system al...
We present an analytical study of the large scale instability of a generalized turbulent Kolmogorov flow, i.e. a periodic shear flow where the molecular viscosity has been substituted by an eddy visco...
This paper presents a numerical evaluation of the randomness which can be observed in the geometry of major river channels. The method used is based upon that of generating a Sierpinski triangle via t...

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