To adequately evaluate risk associated hurricane flooding, numerous surge events must be considered, and the cost associated with high resolution numerical modeling for several storms is excessive. The Joint Probability Method with Optimal Sampling (JPM-OS) has been recently shown to be a reliable method in estimating extreme value probabilities of hurricane flooding – it relies heavily on a hurricane surge matrix comprised of surge values from several hurricane scenarios (with varying meteorological and climate change characteristics). Surge Response Functions (SRFs) are physics-based equations developed using scaling laws to adequately scale surge response in dimensionless space; they serve as surrogates to high resolution numerical models in estimating hurricane peak surge to populate the JPM-OS surge matrix. Research presented in this dissertation is primarily focused on the development of dimensionless formulations using physics-based scaling laws to account for the contribution of forward speed (v_f), approach angle (theta) and Sea Level Rise (SLR). These parameters are incorporated into pre-existing SRFs for open coast locations and bays. For the bays, in addition to accounting for the effects of v_f and theta in the SRFs, a new dimensionless formulation for the influence of storm size (R_p) is included in the SRFs.   To account for the influence of v_f in the SRFs, the dimensionless formulations primarily consist of the time it takes for surge to build up (over the shelf, for open coast SRFs and within the bays, for bay SRFs). The formulation for the influence of theta primarily accounts for the rotation of the hurricane wind field as the storm makes landfall. For the influence of R_p in the bays, the new formulation scales R_p with the farthest distance through which water mass will move inside the bay, from its center of gravity. A simple correction based on a linear model is derived to account for the influence of SLR on surge response at open coast locations and in bays. The developed dimensionless formulations for v_f and theta (and R_p for bay SRFs) are incorporated into the SRFs to obtain revised versions of the response functions. For open coast locations, the revised SRFs estimate peak surge with an increased accuracy (based on root-mean-square errors of modeled versus SRF-estimated peak surge) of up to 12.5% reduction in root-mean-square errors. In addition, the new formulations improve the predictions of 65% of surge events of 2 m or greater. For the bays, the revised SRFs reduce the root-mean-square errors (by up to 54% in Matagorda Bay), when compared to the previous formulation. These results indicate that the new formulations, which include v_f and tehta (and R_p for bay SRFs), significantly improve the accuracy of the SRFs. Application of the revised open coast SRFs to the JPM-OS framework shows only minor impacts of v_f and theta variation on surge versus return period curves (about 5.2% maximum increase in surge for theta varying from -80 degrees to +80 degrees, and a maximum of 6.7% for fvvarying from 1.54 m/s to 10.8 m/s). Climate change parameters however show a much more significant impact on the surge versus return period curves. SLR variation from 0.5 m to 2.0 m yields a maximum of 42.4% increase in surge, while hurricane intensification from 0.5 degrees C to 1.5 degrees C yields an increase of up to 11.3% in surge.