Stochastic bedload transport in mountain streams

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We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

The ecological effects of dams on sediment and river flow have been subject to an increasing attention, leading to the implementation of mitigation measures such as environmental flow release and sediment replenishment. However, fine sediment dynamics have ...

Bedload transport often exhibits dual-mode behavior due to interactions of spatiotemporal controlling factors with the migrating three-dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and cluste ...

Reservoir sedimentation is a key challenge for storage sustainability because it causes volume loss, affecting hydropower production capacity, dam safety, and flood management. A preliminary EPFL study proposed and studied an innovative device (called SEDM ...

The Arbogne River is located mainly in the Swiss canton of Fribourg. The River was meandering through the plane at a very low gradient and several exceptional historic floods with large sediment accumulation are mentioned. After important river training wo ...

There is a paradox in the relationship between bedload transport rates and flow variables: laboratory and field studies have reported on how bedload transport rates depend on flow variables through a power law, but none of the empirical laws fitted to the ...

Population equations for infinitely large networks of spiking neurons have a long tradition in theoret-ical neuroscience. In this work, we analyze a recent generalization of these equations to populations of finite size, which takes the form of a nonlinear ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

In this paper, we set the mathematical foundations of the Dynamical Low-Rank Approximation (DLRA) method for stochastic differential equations (SDEs). DLRA aims at approximating the solution as a linear combination of a small number of basis vectors with r ...

Rivers extend beyond the channels that are typically associated with this word. Of particular interest are flood plains, where important hydro- and morphodynamic processes occur as a result of recurrent flooding. Ecologically, they also support the establi ...

We study the compact support property for solutions of the following stochastic partial differential equations: partial derivative tu=aijuxixj(t,x)+biuxi(t,x)+cu+h(t,x,u(t,x))F-center dot(t,x),(t,x)is an element of(0,infinity)xRd,where F-center dot is a sp ...

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex plane, which are obse ...

Stochastic bedload transport in mountain streams

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Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

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Dynamics of Dual-Mode Bedload Transport With Three-Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis

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Experimental characterization of root-reinforced riparian sediment deposits in a restored and widened river course

Scaling behavior of bedload transport: what if Bagnold was right?

On a Finite-Size Neuronal Population Equation

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

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The elliptical Ornstein-Uhlenbeck process