Elastic loading and rebound is a well-studied phenomenon which can accurately model the earth’s response to surface loading in many areas. In these areas, the mass of water depresses the earth and causes subsidence, which is recoverable when the mass is removed. However, there are some regions which can exhibit a porous or poroelastic response to surface water loading. In these areas, the subsurface can expand with the introduction of water, either by the filling of pore spaces or inflation of subsurface reservoirs. This process has the opposite sign of elastic loading, and is often non-recoverable. To accurately understand and quantify the effects of water loading, we need a method to classify which regions are behaving elastically versus porously. In this study, we propose exploiting the relative temporal responses of GPS stations across California to known hydrologic conditions (from GRACE and local lake and stream gauges) to determine where regions fall on the spectrum of elastic-to-porous responses. We will use the degree of correlation between the predicted elastic response and the actual station timeseries, then extrapolate spatially, finding areas of higher and lower correlation with elastic deformation. This will determine which regions can be modeled with elastic loading, and which need a more complex poroelastic model. The classification will also inform the relative drought risk of different regions of the state.