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Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data
https://orcid.org/0000-0003-2078-1118
https://orcid.org/0000-0003-0614-012X
Abstract The role of soil saturation condition on the liquefaction occurrence highlights the need for a tool to track the ground-truth soil moisture content involved in this seismic phenomenon. Soil Moisture Active Passive (SMAP) satellite estimates near-real time surface and root zone soil moisture measurements with global coverage. Typical proxies for soil saturation in liquefaction analysis include average water table depth patterns, mean annual precipitation measurements, and topographic conditions. As an alternative to these proxies, this paper incorporates satellite-based soil moisture data to enhance the understanding of the interrelation between saturation conditions and liquefaction events. Proposing a new approach for sampling non-liquefaction cases, a liquefaction/non-liquefaction database was developed in this paper based on reconnaissance reports of eleven target earthquakes. Well-known geospatial explanatory variables as well as new SMAP-based soil moisture parameters, affecting soil liquefaction, are used to develop a new soil moisture-based global liquefaction model (SMGLM), which is compared with an existing global liquefaction model. Considering the ongoing advancement of earth observing satellites, the results of this paper can build a basis for developing fully satellite-based models that could identify liquefied sites using high resolution near-real time soil moisture data.
Highlights The SMAP datasets provide a great opportunity to use near real-time ground-truth soil saturation data in liquefaction models. SMAP soil saturation data are used to develop a soil moisture-based liquefaction model. The model lays a basis for future satellite-based systems identifying and predicting liquefied sites using next generation of soil saturation data.
Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data
https://orcid.org/0000-0003-2078-1118
https://orcid.org/0000-0003-0614-012X
Abstract The role of soil saturation condition on the liquefaction occurrence highlights the need for a tool to track the ground-truth soil moisture content involved in this seismic phenomenon. Soil Moisture Active Passive (SMAP) satellite estimates near-real time surface and root zone soil moisture measurements with global coverage. Typical proxies for soil saturation in liquefaction analysis include average water table depth patterns, mean annual precipitation measurements, and topographic conditions. As an alternative to these proxies, this paper incorporates satellite-based soil moisture data to enhance the understanding of the interrelation between saturation conditions and liquefaction events. Proposing a new approach for sampling non-liquefaction cases, a liquefaction/non-liquefaction database was developed in this paper based on reconnaissance reports of eleven target earthquakes. Well-known geospatial explanatory variables as well as new SMAP-based soil moisture parameters, affecting soil liquefaction, are used to develop a new soil moisture-based global liquefaction model (SMGLM), which is compared with an existing global liquefaction model. Considering the ongoing advancement of earth observing satellites, the results of this paper can build a basis for developing fully satellite-based models that could identify liquefied sites using high resolution near-real time soil moisture data.
Highlights The SMAP datasets provide a great opportunity to use near real-time ground-truth soil saturation data in liquefaction models. SMAP soil saturation data are used to develop a soil moisture-based liquefaction model. The model lays a basis for future satellite-based systems identifying and predicting liquefied sites using next generation of soil saturation data.
Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data
https://orcid.org/0000-0003-2078-1118
https://orcid.org/0000-0003-0614-012X
Abstract The role of soil saturation condition on the liquefaction occurrence highlights the need for a tool to track the ground-truth soil moisture content involved in this seismic phenomenon. Soil Moisture Active Passive (SMAP) satellite estimates near-real time surface and root zone soil moisture measurements with global coverage. Typical proxies for soil saturation in liquefaction analysis include average water table depth patterns, mean annual precipitation measurements, and topographic conditions. As an alternative to these proxies, this paper incorporates satellite-based soil moisture data to enhance the understanding of the interrelation between saturation conditions and liquefaction events. Proposing a new approach for sampling non-liquefaction cases, a liquefaction/non-liquefaction database was developed in this paper based on reconnaissance reports of eleven target earthquakes. Well-known geospatial explanatory variables as well as new SMAP-based soil moisture parameters, affecting soil liquefaction, are used to develop a new soil moisture-based global liquefaction model (SMGLM), which is compared with an existing global liquefaction model. Considering the ongoing advancement of earth observing satellites, the results of this paper can build a basis for developing fully satellite-based models that could identify liquefied sites using high resolution near-real time soil moisture data.
Highlights The SMAP datasets provide a great opportunity to use near real-time ground-truth soil saturation data in liquefaction models. SMAP soil saturation data are used to develop a soil moisture-based liquefaction model. The model lays a basis for future satellite-based systems identifying and predicting liquefied sites using next generation of soil saturation data.
Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data
Farahani, Ali (author) / Ghayoomi, Majid (author)
2023-11-12
Article (Journal)
Electronic Resource
English
Soil Moisture Active Passive (SMAP) Data for Ground Monitoring during Earthquakes
| British Library Conference Proceedings | 2023