This paper presents an experimental comparison of dynamic partitioning techniques for blockwise parallel structured adaptive mesh refinement applications. A new partitioning technique, G-MISP, is described. Policies for the automatic selection of partitioner based on application and system state are outlined. Adaptive methods for the numerical solution to partial differential equations yield highly advantageous ratios for cost/accuracy compared to methods based upon static uniform approximations. Distributed implementations offer the potential for accurate solution of physically realistic models of important applications. They also lead to interesting challenges in dynamic resource allocation, e.g. dynamic load balancing. The results show that G-MISP is preferable for communication dominated cases where the block graph has high granularity. Recommendations for appropriate partitioning techniques, given application and system state, are given. It was found that our classification model needs to be extended to accurately capture the behavior of the cases studied.