Pseudospectral methods provide fast and accurate solutions for the horizontal infiltration equation

An extremely fast and accurate pseudospectral numerical method is presented, which can be used in inverse methods for estimating soil hydraulic parameters from horizontal infiltration or desorption experiments. Chebyshev polynomial dierentiation in conjunction with the flux concentration formulation of Philip (1973) results in a numerical solution of high order accuracy that is directly dependent on the number of Chebyshev nodes used. The level of accuracy (< 0:01% for 100 nodes) is confirmed through a comparison with two dierent, but numerically demanding, exact closed-form solutions where an infinite derivative occurs at either the wetting front or the soil surface. Application of our computationally ecient method to estimate soil hydraulic parameters is found to take less than one second using modest laptop computer resources. The pseudospectral method can also be applied to evaluate analytical approximations, and in particular, those of Parlange and Braddock (1980) and Parlange et al (1994) are chosen. It is shown that both these approximations produce excellent estimates of both the sorptivity and moisture profile across a wide range of initial and boundary conditions and numerous physically realistic diusivity functions

Matrix-based numerical modelling of financial differential equations

Differentiation matrices provide a compact and unified formulation for a variety of differential equation discretisation and time-stepping algorithms. This paper illustrates their use for solving three differential equations of finance: the classic Black-Scholes equation (linear initial-boundary value problem), an American option pricing problem (linear complementarity problem), and an optimal maintenance and shutdown model (nonlinear boundary value problem with free boundary). We present numerical results that show the advantage of an L-stable time-stepping method over the Crank-Nicolson method, and results that show how spectral collocation methods are superior for boundary value problems with smooth solutions, while finite difference methods are superior for option-pricing problems.Peer reviewe