This study focuses on the comparison of two optimization algorithms for Artificial Neural Network (ANN) watershed runoff simulation by considering geomorphologic catchment properties The first algorithm is the evolution based algorithm Continues Genetic Algorithm (CGA) while the second is the traditional Back-Propagation algorithm (BP). In this work the multi-layer feed forward Geomorphologic based Artificial Neural Network (GANN) model has been selected to simulate watershed runoff. Two network models that are the GANN- CGA and GANN-BP have been tested for simulating surface flow and surface and subsurface flows combinedly.