DocumentCode :
184367
Title :
Optimal state estimation in an overland flow model using the adjoint method
Author :
Van Tri Nguyen ; Georges, Didier ; Besancon, Gildas
Author_Institution :
Gipsa-Lab., Univ. Grenoble Alpes, St. Martin d´Hères, France
fYear :
2014
fDate :
8-10 Oct. 2014
Firstpage :
2034
Lastpage :
2039
Abstract :
In this paper, an optimal estimation method for initial conditions in an overland flow based on the adjoint method is presented. This system is described by an infinite dimensional model given by the first continuity equation of the well-known one-dimensional Saint-Venant equations. Infiltration process is also taken account in this work by using the so-called Green-Ampt model. The adjoint model is obtained by means of a variational approach. Both the system and adjoint equations are numerically solved by using the nonlinear implicit Preissmann scheme. From the combination between the steepest descent method and a line search method, the cost functional is optimized in order to estimate the mentioned initial conditions from a set of lumped observation values. Finally, a simulation example with a simple overland flow and infiltration in a variable rainfall period is presented in order to demonstrate the effectiveness of this solution.
Keywords :
gradient methods; hydrology; search problems; shallow water equations; state estimation; Green-Ampt model; adjoint method; continuity equation; infiltration process; infinite dimensional model; line search method; lumped observation values; nonlinear implicit Preissmann scheme; one-dimensional Saint-Venant equations; optimal state estimation; overland flow model; rainfall period; steepest descent method; variational approach; Analytical models; Equations; Estimation; Mathematical model; Numerical models; Optimization; Soil; Green-Ampt infiltration model; Infinite dimensional system; Inverse problem; Overland flow; Saint-Venant equations; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications (CCA), 2014 IEEE Conference on
Conference_Location :
Juan Les Antibes
Type :
conf
DOI :
10.1109/CCA.2014.6981602
Filename :
6981602
Link To Document :
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