The performance of SPMD programs is strongly affected by dynamic load imbalancing factors. The use of a suitable load balancing algorithm is essential for overcoming the effects of these imbalancing factors. In this work, we evaluate the performance of a scientific SPMD parallel application when executed on a computational grid, with different kinds of load balancing strategies. The developed SPMD application computes the macroscopic thermal dispersion in porous media. A set of experiments was conducted on a computational grid composed by two geographically separated clusters. The main contribution of this work is the performance evaluation and comparison of a large variety of load balancing techniques under dynamic environment conditions. The experimental results showed the importance of choosing appropriate load balancing strategies when developing SPMD applications on a grid environment.