Estimation of Surface Irrigation Parameters

Abstract

The basic concepts and procedures for the estimation of roughness and infiltration parameters encountered in surface irrigation are presented. A review of existing predictive and nonpredictive parameter‐estimation methods is presented with a formulation of the inverse surface irrigation problem. Conjugate gradient and variable metric techniques are used for the search of the parameter set that minimizes the errors between field observations and the linearized zero‐inertia model. Appropriate constraints that restrict the variation of parameters within physically realistic limits are also imposed on the objective function. The performance and radius of convergence of the search algorithm are studied by numerical tests that demonstrate the steps in the development of the associated objective function and the strategy required for convergence to the correct values of the field parameters. It is concluded that a key role is played by the formulation of the direct problem and its numerical solution, and that the nonlinear field‐parameter search converges quickly when the influence of independent parameters can be decoupled during construction of the objective function.