# Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment
## 4 Discussion
In this seismic zone, there are a remarkable number of grids with a high _MDI_, but most of them are outside of the regions with high values of PGA and MMI, and also liquefied areas. As expected, for earthquakes with a 24 h SMAP event window, including Croatia 2020, Greece 2020, Italy 2018, and Taiwan 2016, the results show more substantial evidence than those with a 48-72 h SMAP data time interval. By expanding the target earthquake database, future studies may yield more finely tuned quantitative formulations. \(\Delta SM_{SMAP}\) maps combined with seismic records and damage proxy maps show that grid cells where the _MDI_ > 0 contain liquefied areas mapped by reconnaissance teams as well as regions with a high probability of liquefaction occurrence that were beyond the reconnaissance extent. Field reconnaissance teams could use the method presented in this study to identify regions that experienced a high soil moisture increase after each earthquake and, in combination with the USGS model results, to prioritize those regions in field surveys. For example, grids with both high values of _MDI_ and a high liquefaction probability are highly likely to be regions that experienced liquefaction. Future research is recommended to better understand how to improve the accuracy of liquefaction probability models using _MDI_ as a potential parameter for the surface soil saturation condition after an earthquake. In addition to the L3_SM_P_E surface soil moisture used for this study, other SMAP data products might have value for the earthquake community. For instance, L4-SM provides estimates of the root zone soil moisture in the top 1 m of the soil column. This data product is produced by assimilating SMAP observations from the top 5 cm of the soil column with estimates provided by land surface models. L4-SM and its downscaled version [91] could be used to evaluate the effects of the pre-event root zone soil moisture on seismic site response as well as ground failures and earthquake damage. Conceptualization, A.F., M.G. and J.M.J. ; methodology, A.F., M.M., M.G. and J.M.J. ; data curation, A.F. ; writing--original draft preparation, A.F. ; writing--review and editing, A.F., M.M., M.G. and J.M.J. ; visualization, A.F. ; supervision, M.G. and J.M.J. ; project administration, M.G. ; funding acquisition, M.G. and J.M.J. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Aeronautics and Space Administration (NASA), Soil Moisture Active Passive Science Team (SMAP ST) program through award No. 80 NSSC20K1808. All data used in this study are available from the first author upon reasonable request. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 12: Soil moisture change reported by SMAP and GLDAS and accumulated precipitation in the SMAP event window on 25 km \(\times\) 25 km grids. Figure 13: \(\Delta\)_SM\({}_{\text{SMAP}}\)_(9 km \(\times\) 9 km) in grids with (**a**) available soil moisture data, (**b**) \(MDI\)\(>\) 0.08, (**c**) \(MDI\)\(>\) 0.04, (**d**) \(MDI\)\(>\) 0.02 cm\({}^{3}\)/cm\({}^{3}\), (**e**) \(MDI\)\(>\) 0 cm\({}^{3}\)/cm\({}^{3}\) integrated with seismic records for Kaikoura, New Zealand 2016 earthquake.