In this paper we propose a trust region algorithm for solving sparse sets of nonlinear equations. It is based on minimizing the $l_1 $-norm of the linearized residual vector within an $l_\infty $-norm trust region, thereby permitting linear programming techniques to be easily applied. The new algorithm has sparsity advantages over the Levenberg-Marquardt algorithm.