{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T04:45:33Z","timestamp":1791434733024,"version":"4.3.3"},"reference-count":108,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T00:00:00Z","timestamp":1677715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Shallow landslides due to hydro-meteorological factors are one of the most common destructive geological processes, which have become more frequent in recent years due to changes in rainfall frequency and intensity. The present study assessed a dynamic, physically based slope stability model, Transient Rainfall Infiltration and Grid-Based Slope Stability Model (TRIGRS), in Idukki district, Kerala, Western Ghats. The study compared the impact of hydrogeomechanical parameters derived from two different data sets, FAO soil texture and regionally available soil texture, on the simulation of the distribution and timing of shallow landslides. For assessing the landslide distribution, 1913 landslides were compared and true positive rates (TPRs) of 68% and 60% were obtained with a nine-day rainfall period for the FAO- and regional-based data sets, respectively. However, a false positive rate (FPR) of 36% and 31% was also seen, respectively. The timing of occurrence of nine landslide events was assessed, which were triggered in the second week of June 2018. Even though the distribution of eight landslides was accurately simulated, the timing of only three events was found to be accurate. The study concludes that the model simulations using parameters derived from either of the soil texture data sets are able to identify the location of the event. However, there is a need for including a high-spatial-resolution hydrogeomechanical parameter data set to improve the timing of landslide event modeling.<\/jats:p>","DOI":"10.3390\/ijgi12030105","type":"journal-article","created":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T01:43:00Z","timestamp":1677807780000},"page":"105","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Assessment of a Dynamic Physically Based Slope Stability Model to Evaluate Timing and Distribution of Rainfall-Induced Shallow Landslides"],"prefix":"10.3390","volume":"12","author":[{"given":"Juby","family":"Thomas","sequence":"first","affiliation":[{"name":"Department of Geology, University of Delhi, Delhi 110007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manika","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Geology, University of Delhi, Delhi 110007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4155-630X","authenticated-orcid":false,"given":"Prashant K.","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1442-1423","authenticated-orcid":false,"given":"George P.","family":"Petropoulos","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou 70, 17671 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Manenti, S., Amicarelli, A., Palazzolo, N., Bordoni, M., Creaco, E., and Meisina, C. (2020). Post-Failure Dynamics of Rainfall-Induced Landslide in Oltrep\u00f2 Pavese. Water, 12.","DOI":"10.3390\/w12092555"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"16374","DOI":"10.1038\/s41598-021-95978-5","article-title":"Measuring Landslide Vulnerability Status of Chukha, Bhutan Using Deep Learning Algorithms","volume":"11","author":"Saha","year":"2021","journal-title":"Sci. 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