Brocca, L., Ponziani, F., Moramarco, T., Melone, F., Berni, N., and Wagner, W.: Improving landslide forecasting using ASCAT-derived soil moisture data: A case study of the torgiovannetto landslide in central Italy, Remote Sens., 4, 1232–1244, https://doi.org/10.3390/rs4051232, 2012.
Caine, N.: The rainfall intensity–duration control of shallow landslides and debris flows, Geogr. Ann. A, 62, 23–27, https://doi.org/10.1080/04353676.1980.11879996, 1980.
Cepeda, J., Höeg, K., and Nadim, F.: Landslide-triggering rainfall thresholds: A conceptual framework, Q. J. Eng. Geol. Hydroge., 43, 69–84, https://doi.org/10.1144/1470-9236/08-066, 2010.
Conrad, J. L., Morphew, M. D., Baum, R. L., and Mirus, B. B.: HydroMet: A new code for automated objective optimization of hydrometeorological thresholds for landslide initiation. Water, 13, 1752, https://doi.org/10.3390/w13131752, 2021.
D'Ippolito, A., Lupiano, V., Rago, V., Terranova, O. G., and Iovine, G.: Triggering of Rain-Induced Landslides, with Applications in Southern Italy, Water, 15, 277, https://doi.org/10.3390/w15020277, 2023.
Fayaz, M., Meraj, G., Khader, S. A., and Farooq, M.: ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas, Environmental Challenges, 9, 100624, https://doi.org/10.1016/j.envc.2022.100624, 2022.
Gain, A. K., Bühler, Y., Haegeli, P., Molinari, D., Parise, M., Peres, D. J., Pinto, J. G., Schröter, K., Trigo, R. M., Llasat, M. C., and Kreibich, H.: Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences, Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, 2022.
Godt, J. W., Baum, R. L., and Chleborad, A. F.: Rainfall characteristics for shallow landsliding in Seattle, Washington, USA, Earth Surf. Proc. Land., 31, 97–110, https://doi.org/10.1002/esp.1237, 2006.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: The rainfall intensity-duration control of shallow landslides and debris flows: An update, Landslides, 5, 3–17, https://doi.org/10.1007/s10346-007-0112-1, 2008.
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007.
Kirschbaum, D., Stanley, T., and Zhou, Y.: Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15, https://doi.org/10.1016/j.geomorph.2015.03.016, 2015.
Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., and Lerner-Lam, A.: A global landslide catalog for hazard applications: Method, results, and limitations, Nat. Hazards, 52, 561–575, https://doi.org/10.1007/s11069-009-9401-4, 2010.
Klose, M.: Landslide Databases as Tools for Integrated Assessment of Landslide Risk, Springer Theses, Springer, Cham, https://doi.org/10.1007/978-3-319-20403-1, 2015.
Knights, M. J., Montgomery, J., and Carcamo, P. S.: Development of a slope failure database for Alabama highways, B. Eng. Geol. Environ., 79, 423–438, https://doi.org/10.1007/s10064-019-01543-w, 2020.
Lazzari, M., Piccarreta, M., Ray, R. L., and Manfreda, S.: Modeling antecedent soil moisture to constrain rainfall thresholds for shallow landslides occurrence, in: Landslides – Investigation and Monitoring, edited by: Ray, R. and Lazzari, M., IntechOpen, London, https://doi.org/10.5772/intechopen.92730, 2020.
Leonarduzzi, E., Molnar, P., and McArdell, B. W.: Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data, Water Resour. Res., 53, 6612–6625, https://doi.org/10.1002/2017WR021044, 2017.
Lin, Q., Lima, P., Steger, S., Glade, T., Jiang, T., Zhang, J., Liu, T., and Wang, Y.: National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data, Geosci. Front., 12, https://doi.org/10.1016/j.gsf.2021.101248, 2021.
Machan, G. and Bennett, V. G.: Use of Inclinometers for Geotechnical Instrumentation on Transportation Projects: State of the Practice, Transportation Research Circular E-C129, Transportation Research Board, Washington, D.C., 1–92,
https://onlinepubs.trb.org/onlinepubs/circulars/ec129.pdf (last access: 15 June 2026), 2008.
Mandal, P. and Sarkar, S.: Estimation of rainfall threshold for the early warning of shallow landslides along National Highway-10 in Darjeeling Himalayas, Nat. Hazards, 105, 2455–2480, https://doi.org/10.1007/s11069-020-04407-9, 2021.
Marino, P., Peres, D. J., Cancelliere, A., Greco, R., and Bogaard, T. A.: Soil moisture information can improve shallow landslide forecasting using the hydrometeorological threshold approach, Landslides, 17, 2041–2054, https://doi.org/10.1007/s10346-020-01420-8, 2020.
Martelloni, G., Segoni, S., Fanti, R., and Catani, F.: Rainfall thresholds for the forecasting of landslide occurrence at regional scale, Landslides, 9, 485–495, https://doi.org/10.1007/s10346-011-0308-2, 2012.
McKinney, W.: Data Structures for Statistical Computing in Python, in: Proceedings of the 9th Python in Science Conference, edited by: van der Walt, S. and Millman, J., Austin, Texas, 56–61, https://doi.org/10.25080/Majora-92bf1922-00a, 2010.
Mikkelsen, P. E.: Advances in inclinometer data analysis, in: Field Measurements in Geomechanics: Proceedings of the 6th International Symposium on Field Measurements in Geomechanics, Oslo, Norway, 23–26 September 2003, edited by: Myrvoll, F., A. A. Balkema, Lisse, the Netherlands, ISBN 9789058096029, 555–567, 2003.
Millán-Arancibia, C. and Lavado-Casimiro, W.: Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data, Nat. Hazards Earth Syst. Sci., 23, 1191–1206, https://doi.org/10.5194/nhess-23-1191-2023, 2023.
Mirus, B. B., Morphew, M. D., and Smith, J. B.: Developing hydro-meteorological thresholds for shallow landslide initiation and early warning, Water, 10, 1274, https://doi.org/10.3390/W10091274, 2018a.
Mirus, B. B., Becker, R. E., Baum, R. L., and Smith, J. B.: Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning, Landslides, 15, 1909–1919, https://doi.org/10.1007/s10346-018-0995-z, 2018b.
Mirus, B. B., Jones, E. S., Baum, R. L., Godt, J. W., Slaughter, S., Crawford, M. M., Lancaster, J., Stanley, T., Kirschbaum, D. B., Burns, W. J., Schmitt, R. G., Lindsey, K. O., and McCoy, K. M.: Landslides across the USA: occurrence, susceptibility, and data limitations, Landslides, 17, 2271–2285, https://doi.org/10.1007/s10346-020-01424-4, 2020.
Montgomery, J., Knights, M., Xuan, M., and Carcamo, P.: Evaluation of landslides along Alabama highways, ALDOT Research Report, Project 930-931, Highway Research Center, Auburn University, Auburn, Alabama,
https://www.eng.auburn.edu/research/centers/hrc/hrc-files/930-931final-montgomery.pdf (last access: 15 June 2026), 2019.
NOAA Physical Sciences Laboratory (PSL): CPC Global Unified Gauge-Based Analysis of Daily Precipitation, NOAA PSL [data set], Boulder, Colorado, USA,
https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html (last access: 15 June 2026), 2024.
Oorthuis, R., Hürlimann, M., Vaunat, J., Moya, J., and Lloret, A.: Monitoring the role of soil hydrologic conditions and rainfall for the triggering of torrential flows in the Rebaixader catchment (Central Pyrenees, Spain): Role of soil hydrologic conditions and rainfall for torrential flows in the Rebaixader catchment, Landslides, 20, 249–269, https://doi.org/10.1007/s10346-022-01975-8, 2023.
Piciullo, L., Gariano, S. L., Melillo, M., Brunetti, M. T., Peruccacci, S., Guzzetti, F., and Calvello, M.: Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides, Landslides, 14, 995–1008, https://doi.org/10.1007/s10346-016-0750-2, 2017.
Rahimikhameneh, L., Reyna, A. A., Montgomery, J., and O'Donnell, F.: Integrating precipitation and soil moisture 535 measurements to understand landslide movements along Alabama highways, Geo-Congress 2024, 613–622, https://doi.org/10.1061/9780784485316.063, 2024.
Rahimikhameneh, L., Montgomery, J., Knights, M., Reyna, A. A., O'Donnell, F., and Carcamo, P.: Inventory of Landslides Along Alabama Highways, DesignSafe-CI [data set], https://doi.org/10.17603/ds2-xs04-th22, 2025.
Ray, R. L., Jacobs, J. M., and Cosh, M. H.: Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US, Remote Sens. Environ., 114, 2624–2636, https://doi.org/10.1016/j.rse.2010.05.033, 2010.
Reichle, R., De Lannoy, G., Koster, R. D., Crow, W. T., Kimball, J. S., and Liu, Q.: SMAP L4 Global 3-hourly 9 k
m EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data, Version 4, NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) [data set], https://doi.org/10.5067/KPJNN2GI1DQR, 2018.
Roccati, A., Paliaga, G., Luino, F., Faccini, F., and Turconi, L.: Rainfall threshold for shallow landslides initiation and analysis of long-term rainfall trends in a mediterranean area, Atmosphere, 11, 1367, https://doi.org/10.3390/atmos11121367, 2020.
Rodríguez-Fernández, N. J., Muñoz Sabater, J., Richaume, P., de Rosnay, P., Kerr, Y. H., Albergel, C., Drusch, M., and Mecklenburg, S.: SMOS near-real-time soil moisture product: processor overview and first validation results, Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, 2017.
Santangelo, M., Althuwaynee, O., Alvioli, M., Ardizzone, F., Bianchi, C., Bornaetxea, T., Brunetti, M. T., Bucci, F., Cardinali, M., Donnini, M., Esposito, G., Gariano, S. L., Grita, S., Marchesini, I., Melillo, M., Peruccacci, S., Salvati, P., Yazdani, M., and Fiorucci, F.: Inventory of landslides triggered by an extreme rainfall event in Marche-Umbria, Italy, on 15 September 2022, Sci. Data, 10, https://doi.org/10.1038/s41597-023-02336-3, 2023.
Segoni, S., Piciullo, L., and Gariano, S. L.: A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, 15, 1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018a.
Segoni, S., Rosi, A., Lagomarsino, D., Fanti, R., and Casagli, N.: Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system, Nat. Hazards Earth Syst. Sci., 18, 807–812, https://doi.org/10.5194/nhess-18-807-2018, 2018b.
Sepúlveda, S. A., Ward, B. C., Cosman, S. B., and Jacobs, R.: Preliminary investigations of ground failures triggered during the mid-November 2021 atmospheric river event along the southwestern British Columbia highway corridors, Can. Geotech. J., 60, 580–586, https://doi.org/10.1139/cgj-2022-0093, 2023.
Skulovich, O. and Gentine, P.: A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset, Sci. Data, 10, https://doi.org/10.1038/s41597-023-02053-x, 2023.
Stanley, T. A., Kirschbaum, D. B., Benz, G., Emberson, R. A., Amatya, P. M., Medwedeff, W., and Clark, M. K.: Data-Driven Landslide Nowcasting at the Global Scale, Front. Earth Sci., 9, 640043, https://doi.org/10.3389/feart.2021.640043, 2021.
Stark, T. D. and Choi, H.: Slope inclinometers for landslides, Landslides, 5, 339–350, https://doi.org/10.1007/s10346-008-0126-3, 2008.
Szabo, E. W., Osborne, W. E., Copeland, C. W., Jr., and Neathery, T. L.: Geologic map of Alabama, Special Map 220, scale 1:250,000, Geological Survey of Alabama, Tuscaloosa, Alabama,
https://ngmdb.usgs.gov/Prodesc/proddesc_55859.htm (last access: 15 June 2026), 1988.
Taylor, F. E., Tarolli, P., and Malamud, B. D.: Preface: Landslide–transport network interactions, Nat. Hazards Earth Syst. Sci., 20, 2585–2590, https://doi.org/10.5194/nhess-20-2585-2020, 2020.
Uwihirwe, J., Hrachowitz, M., and Bogaard, T. A.: Landslide precipitation thresholds in Rwanda, Landslides, 17, 2469–2481, https://doi.org/10.1007/s10346-020-01457-9, 2020.
Valenzuela, P., Domínguez-Cuesta, M. J., Mora García, M. A., and Jiménez-Sánchez, M.: Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias, NW Spain), Landslides, 15, 273–282, https://doi.org/10.1007/s10346-017-0878-8, 2018.
Voumard, J., Derron, M.-H., and Jaboyedoff, M.: Natural hazard events affecting transportation networks in Switzerland from 2012 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2093–2109, https://doi.org/10.5194/nhess-18-2093-2018, 2018.
Wicki, A., Lehmann, P., Hauck, C., Seneviratne, S. I., Waldner, P., and Stähli, M.: Assessing the potential of soil moisture measurements for regional landslide early warning, Landslides, 17, 1881–1896, https://doi.org/10.1007/s10346-020-01400-y, 2020.
Winter, M. G., Shearer, B., Palmer, D., Peeling, D., Harmer, C., and Sharpe, J.: The Economic Impact of Landslides and Floods on the Road Network, Procedia Engineer., 143, 1425–1434, https://doi.org/10.1016/j.proeng.2016.06.168, 2016.
Xie, P., Yatagai, A., Chen, M., Hayasaka, T., Fukushima, Y., Liu, C., and Yang, S.: A gauge-based analysis of daily precipitation over East Asia, J. Hydrometeorol., 8, 607–626, https://doi.org/10.1175/JHM583.1, 2007.
Yang, H., Hu, K., Zhang, S., and Liu, S.: Feasibility of satellite-based rainfall and soil moisture data in determining the triggering conditions of debris flow: the Jiangjia Gully (China) case study, Eng. Geol., 315, 107041, https://doi.org/10.1016/j.enggeo.2023.107041, 2023.
Zhao, S., Zeng, R., Zhang, Z., Meng, X., Qi, T., Long, Z., Guo, W., and Si, G.: Landslide mapping and causes of landslides in the China–Nepal transportation corridor based on remote sensing technology, Remote Sens., 16, 356, https://doi.org/10.3390/rs16020356, 2024.
Zhuo, L., Dai, Q., Han, D., Chen, N., Zhao, B., and Berti, M.: Evaluation of remotely sensed soil moisture for landslide hazard assessment, IEEE J. Sel. Top. Appl., 12, 162–173, https://doi.org/10.1109/JSTARS.2018.2883361, 2019.
