Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data

被引:3
|
作者
Farahani, Ali [1 ]
Ghayoomi, Majid [1 ]
机构
[1] Univ New Hampshire, Dept Civil & Environm Engn, Durham, NH 03824 USA
关键词
Liquefaction database; Remote sensing; SMAP; Soil moisture; Rapid response; Satellite data; Geospatial modelling; EARTHQUAKE-INDUCED LIQUEFACTION; SHEAR-WAVE VELOCITY; RESISTANCE; VALIDATION; MITIGATION; MAP;
D O I
10.1016/j.soildyn.2023.108350
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
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.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data
    Sadeghi, Morteza
    Ebtehaj, Ardeshir
    Crow, Wade T.
    Gao, Lun
    Purdy, Adam J.
    Fisher, Joshua B.
    Jones, Scott B.
    Babaeian, Ebrahim
    Tuller, Markus
    JOURNAL OF HYDROMETEOROLOGY, 2020, 21 (02) : 241 - 253
  • [42] The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch Calibration and Validation of the SMAP Soil Moisture Algorithms
    McNairn, Heather
    Jackson, Thomas J.
    Wiseman, Grant
    Belair, Stephane
    Berg, Aaron
    Bullock, Paul
    Colliander, Andreas
    Cosh, Michael H.
    Kim, Seung-Bum
    Magagi, Ramata
    Moghaddam, Mahta
    Njoku, Eni G.
    Adams, Justin R.
    Homayouni, Saeid
    Ojo, Emmanuel RoTimi
    Rowlandson, Tracy L.
    Shang, Jiali
    Goita, Kalifa
    Hosseini, Mehdi
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (05): : 2784 - 2801
  • [43] Comparative analysis of CYGNSS soil moisture data with SMAP satellite and ISMN stations
    Cevikalp, Muhammed Rasit
    Isik, Mustafa Serkan
    Celik, Mehmet Furkan
    Musaoglu, Nebiye
    GEOMATIK, 2024, 9 (02): : 227 - 237
  • [44] Ocean Salinity Retrieval and Prediction for Soil Moisture Active Passive Satellite Using Data-to-Data Translation
    Han, Kyung-Hoon
    Hong, Sungwook
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [45] Frequency-Agile Radar Electronics for the Soil Moisture Active/Passive (SMAP) Mission
    Fischman, Mark
    Chan, Samuel
    Huang, Nelson
    Pak, Kyung
    IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2015, 3 (01) : 10 - 19
  • [46] Development and assessment of the SMAP enhanced passive soil moisture product
    Chan, S. K.
    Bindlish, R.
    O'Neill, P.
    Jackson, T.
    Njoku, E.
    Dunbar, S.
    Chaubell, J.
    Piepmeier, J.
    Yueh, S.
    Entekhabi, D.
    Colliander, A.
    Chen, F.
    Cosh, M. H.
    Caldwell, T.
    Walker, J.
    Berg, A.
    McNairn, H.
    Thibeault, M.
    Martinez-Fernandez, J.
    Uldall, F.
    Seyfried, M.
    Bosch, D.
    Starks, P.
    Collins, C. Holifield
    Prueger, J.
    van der Velde, R.
    Asanuma, J.
    Palecki, M.
    Small, E. E.
    Zreda, M.
    Calvet, J.
    Crow, W. T.
    Kerr, Y.
    REMOTE SENSING OF ENVIRONMENT, 2018, 204 : 931 - 941
  • [47] A soil moisture-based framework for guiding the number and location of soil moisture sensors in agricultural fields
    Rossini, Pedro R.
    Ciampitti, Ignacio Antonio
    Hefley, Trevor
    Patrignani, Andres
    VADOSE ZONE JOURNAL, 2021, 20 (06)
  • [48] An Integrated Active-Passive Soil Moisture Retrieval Algorithm for SMAP for Bare Surfaces
    Akbar, Ruzbeh
    Moghaddam, Mahta
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 16 - 19
  • [49] Soil moisture measurements at global scale using active and passive microwave sensors
    Paloscia, S
    Macelloni, G
    Pampaloni, P
    Santi, E
    Koike, T
    IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, 2000, : 1241 - 1243
  • [50] PHYSICALLY-BASED ACTIVE-PASSIVE MODELLING AND RETRIEVAL FOR SMAP SOIL MOISTURE INVERSION ALGORITHM
    Jagdhuber, T.
    Entekhabi, D.
    Hajnsek, I.
    Konings, A. G.
    McColl, K. A.
    Alemohammad, S. H.
    Das, N. N.
    Montzka, C.
    2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 1300 - 1303