We investigate optimal stopping problems for systems driven by the Brownian sheet. Our analysis is divided into two parts. In the first part we derive explicit solutions to two optimal stopping problems for the exponentially discounted Brownian sheet. The first problem consists in determining the optimal two-parameter first hitting point tau = (tau1,tau2) maximizing E[exp(-rho tau1 tau2) h(B(tau1,tau2))], where rho > 0 is a discount factor and h is a reward function. Restricting attention to first hitting points of levels, we obtain a closed-form characterization of the optimal stopping threshold. In particular, for linear rewards h(y)=y the optimal level is y_hat = (2 rho)^(-1/2). The second problem concerns optimal stopping of the integrated discounted Brownian sheet with payoff E[int_0^{tau1} int_0^{tau2} exp(-rho t x) B(t,x) dt dx]. We show that the optimal first hitting level is strictly positive and give an explicit representation of the value function in terms of the exponential integral function. The optimal threshold is characterized as the unique solution of a nonlinear equation derived from a Laplace transform identity for the product tau1 tau2. In the second and main part of the paper we develop a potential theoretic framework for two-parameter optimal stopping problems associated with stochastic partial differential equations driven by the Brownian sheet, proving that the value function is the least superharmonic majorant of the reward and establishing existence of optimal stopping points in the plane.