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Slope units were found to be appropriate for the fundamental morphological elements in landslide susceptibility evaluation. Following the DEM construction in a loess area susceptible to landslides, the direct-reverse DEM technology was employed to generate 216 slope units in the studied area. Of the 216 slope units, 123 involved landslides. To analyze the mechanism of these landslides, six environmental factors were selected to evaluate landslide occurrence: slope angle, aspect, the height and shape of the slope, distance to river and human activities. The spatial analysis demonstrates that most of the landslides are located on convex slopes at an elevation of 100-150 m with slope angles from 135°-225° and 40°-60°. Landslide occurrence was then checked according to these environmental factors using an artificial neural network with back propagation, optimized by genetic algorithms. A dataset of 120 slope units was chosen for training the neural network model, and the parameters of genetic algorithms and neural networks were set. After training on the datasets, the susceptibility of landslides was mapped for the land-use plan and hazard mitigation. Comparing the susceptibility map with landslide inventory, the verification shows satisfactory agreement with an accuracy of 86.46% between the susceptibility map and the landslide locations. In the landslide susceptibility assessment, ten new slopes were predicted to show potential for failure, which can be confirmed by the engineering geological conditions of these slopes. ",{"EN":164},"Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility",{"VOID":166},"[]",{"VOID":168},"Ayalew, L., and H. Yamagishi. 2005. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, central Japan. Geomorphology 65: 15–31.\nBai, S., G. Lu, J. Wang, P. Zhou, and L. Ding. 2011. GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environmental Earth Sciences 62: 139–149.\nCarrara, A., M. Cardinali, R. Detti, F. Guzzetti, V. Pasqui, and P. Reichenbach. 1991. GIS techniques and statistical models in evaluating landslide hazard. Earth Surface Processes Landforms 16: 427–445.\nCatani, F., N. Casagli, L. Ermini, G. Righini, and G. Menduni. 2005. Landslide hazard and risk mapping at catchment scale in the Arno River basin. Landslides 2: 329–342.\nChung, C.F., and A.G. Fabbri. 2003. Validation of spatial prediction models for landslide hazard mapping. Natural Hazards 30: 451–472.\nChung, C.J. 2006. Using likelihood ratio functions for modeling the conditional probability of occurrence of future landslides for risk assessment. Computer and Geosciences 32: 1052–1068.\nConforti, M., S. Pascale, G. Robustelli, and F. Sdao. 2014. Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy). Catena 113: 236–250.\nDahal, R.K., S. Hasegawa, A. Nonomura, M. Yamanaka, S. Dhakal, and P. Paudyal. 2008. Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence. Geomorphology 102: 496–510.\nDerbyshire, E., J.T. Wang, and X.M. Meng. 1999. A treacherous terrain: background to natural hazards in northern China, with special reference to the history of landslides in Gansu Province. In Landslides in the thick loess terrain of north-west China, ed. E. Derbyshire, X.M. Meng, and T.A. Dijkstra, 11–18.\nErcanoglu, M., and C. Gokceoglu. 2002. Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach. Environ Geol 41: 720–730.\nErmini, L., F. Catani, and N. Casagli. 2005. Artificial Neural Networks applied to landslide susceptibility assessment. Geomorphology 66: 327–343.\nFell, R., J. Corominas, C. Bonnard, L. Cascini, E. Leroi, and W.Z. Savage. 2008. Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology 102: 85–98.\nGarcía-Rodríguez, M.J., and J.A. Malpica. 2010. Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model. Nat. Hazards Earth Syst. Sci. 10: 1307–1315.\nGómez, H., and T. Kavzoglu. 2005. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Engineering Geology 78: 11–27.\nGuzzetti, F., A. Carrara, M. Cardinali, and P. Reichenbach. 1999. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31: 181–216.\nHasekiogullar, G.D., and M. Ercanoglu. 2012. A new approach to use AHP in landslide susceptibility mapping: a case study at Yenice (Karabuk, NW Turkey). Natural Hazards 63: 1157–1179.\nHolland, J.H. Adaptation in natural and artificial systems. Ann Arbour: The University of Michigan Press, 1975.\nKanungoa, D.P., M.K. Arorab, S. Sarkara, and R.P.A. Guptac. 2006. Comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Engineering Geology 85: 347–366.\nKavzoglu, T., E.K. Sahin, and I. Colkesen. 2015. Selecting optimal conditioning factors in shallow translational landslide susceptibility mapping using genetic algorithm. 192: 101–112.\nKesign, U. 2004. Genetic algorithm and artificial neural network for engine optimisation of efficiency and NOx emission. Fuel 83: 885–895.\nLee, S., J.H. Ryu, K. Min, and J.S. Won. 2003. Landslide susceptibility analysis using GIS and artificial neural network. Earth Surface Processes and Landforms 23: 1361–1376.\nLee, S., and D. Pradhan. 2010. Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia. Landslides 7(1): 13–30.\nMadaeni, S.S., N.T. Hasankiadeh, A.R. Kurdian, and A. Rahimpour. 2010. Modeling and optimization of membrane fabrication using artificial neural network and genetic algorithm. Separation of Purification Technology 76: 33–43.\nMaidment, D. 2002. Arc Hydro: GIS for water resources. ESRI 380, New York Street, Redland, California.\nMartinovic, K., K. Gavin, and C. Reale. 2016. Development of a landslide susceptibility assessment for a rail network. Engineering Geology 215: 1–9.\nMelchiorre, C., M. Matteucci, A. Azzoni, and A. Zanchi. 2008. Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology 94: 379–400.\nMeng, X. M., Dijkstra, T. D., Derbyshire, E. 2000. Loess slope instability. In: Derbyshire E, Meng, X.M., Dijkstra, T.A. (eds). Landslides in the thick loess terrain of north-west China, 175–181. Chichester: John Wiley.\nNeaupane, K.M., and S.H. Achet. 2004. Use of back propagation neural network for landslide monitoring: a case study in the higher Himalaya. Engineering Geology 74: 213–226.\nNefeslioglu, H.A., C. Gokceoglu, and H. Sonmez. 2008. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng. Geol. 97: 171–191.\nNefeslioglua, H.A., C. Gokceoglub, H. Sonmez, and T. Gorum. 2011. Medium-scale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey). Landslides 8(4): 459–483.\nNourani, V., B. Pradhan, H. Ghaffari, and S.S. Sharifi. 2014. 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GIS in landslide hazard zonation: a review, with examples from Andes of Colombia. In Mountain Environments and Geographic Information Systems, ed. M. Price and I. Heywood, 135–165. Basingstoke: Taylor & Francis.\nWang, H.B., G.J. Liu, W.Y. Xu, and G.H. Wang. 2005. GIS-based landslide hazard assessment: An overview. Progress in Physical Geography 29: 548–567.\nXie, M.W., T. Esaki, and G.Y. Zhou. 2004. GIS-based probabilistic mapping of landslide hazard using a three-dimensional deterministic model. Natural Hazards 33: 265–282.\nYilmaz, Y. 2009. An Agent Simulation Study on Conflict, Community Climate, and Innovation in Open Source Communities. International Journal of Open Source Software and Processes 1(4): 1–25.\nZhang, A.L., Z.T. Yang, J. Zhong, and F.S. Mi. 1995. Characteristics of late Quaternary activity along the southern border fault zone of Weihe graben basin. 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Chen","ARTICLE",{"url":175,"publisher":274,"properties":330},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":275,"slug":10,"properties":276,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":279,"manageAffiliations":299,"indexDatabases":310,"url":106,"thumbnailPath":18,"statistic":325,"gsStatistic":18,"type":149,"analyzePriority":18},[],{"issn":277,"title":278},{"VOID":13},{"EN":15},[280,284,288,291,295],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":281,"label":282,"description":283,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":285,"label":286,"description":287,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":289,"label":290,"description":18,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{"id":39,"createTime":18,"updateTime":18,"relativeEntities":292,"label":293,"description":294,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":42},{},{"id":45,"createTime":18,"updateTime":18,"relativeEntities":296,"label":297,"description":298,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":48},{},[300,305],{"id":52,"createTime":18,"updateTime":18,"relativeEntities":301,"slug":18,"properties":302,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":304,"statistic":18},[],{"title":303},{"EN":56},[],{"id":59,"createTime":18,"updateTime":18,"relativeEntities":306,"slug":18,"properties":307,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":309,"statistic":18},[],{"title":308},{"EN":63},[65],[311,318],{"id":68,"indexDatabase":312,"url":81,"indexYears":18,"academicFieldIds":317,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":313,"label":314,"description":315,"key":77,"publicationTags":316,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"id":86,"indexDatabase":319,"url":97,"indexYears":98,"academicFieldIds":324,"indexDatabaseRanking":105},{"id":88,"createTime":18,"updateTime":18,"relativeEntities":320,"label":321,"description":322,"key":94,"publicationTags":323,"standard":18},[],{"EN":91,"VI":91},{"EN":91,"VI":93},[96],[100,101,102,103,104],{"impactFactor":19,"impactFactorByYear":326,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":327,"totalCitation":130,"totalCitationByYear":328,"totalCitationPerPublication":139,"totalCitationPerPublicationByYear":329,"hindexLast5Year":148,"hindex":148},{"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":123,"2024":121},{"2015":132,"2016":133,"2017":134,"2018":135,"2019":136,"2020":137,"2022":138},{"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2022":147},{"pages":331,"volume":333},{"VOID":332},"1-12",{"VOID":334},"4","2017-04-14",2017,"ERROR_IN_GET_PLATFORM_ID","2026-07-16T21:53:00.987+00:00",[79,105],false,{"id":342,"createTime":343,"updateTime":344,"relativeEntities":345,"slug":346,"properties":347,"entityType":171,"verifyStatus":172,"verifyTime":358,"verifyNote":174,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":359,"fullTextUrl":18,"authors":360,"publicationType":272,"publisherRelationship":393,"citationCount":18,"citationInfo":18,"publishDate":455,"publishYear":456,"citationAnalyzeStatus":17,"lastCitationAnalyze":457,"indexDatabases":458,"openAccess":18,"references":18,"isForceReanalyzing":340},"7a0e1b01-5854-4aa7-8152-5883bed7bd4f","2023-12-11T19:19:29.293+00:00","2026-07-13T21:59:25.952+00:00",[],"Hydromechanical-constraints-on-piping-failure-of-landslide-dams-an-experimental-investigation",{"abstract":348,"title":350,"gsPaper":352,"references":354,"doi":356},{"EN":349},"Understanding the internal structure and material properties of landslide dams is essential for evaluating their potential failure mechanisms, especially by seepage and piping. Recent research has shown that the behaviour of landslide dams depends on the internal composition of the impoundment. We here present an experimental investigation of the hydromechanical constraints of landslide dam failure by piping. Experiments were conducted in a 2 m × 0.45 × 0.45 m flume, with a flume bed slope of 5°. Uniform dams of height 0.25 m were built with either mixed or homogeneous silica sands. Uniform-sized pebbles encased in a plastic mesh were used to initiate internal erosion. Two laser displacement sensors were used to monitor the behaviour of the dams during the internal erosion process while a linear displacement transducer and a water-level probe were deployed to monitor the onset of internal erosion and the hydrological trend of the upstream lake. Five major phases of the breach evolution process were observed: pipe evolution, pipe enlargement, crest settlement, hydraulic fracturing and progressive sloughing. Two major failure modes were observed: seepage and piping-induced collapse. Majority of the dams composed of homogeneous material failed by seepage and downstream slope saturation, whereas dams built with mixed material failed by piping. We found that an increase in soil density and homogeneity of the dam materials reduced the potential to form a continuous piping hole through the dams. Furthermore, the potential for piping and progression of the piping hole through the dams increased with an increase in the percentage of fines and a decrease in hydraulic conductivity. The rate of pipe enlargement is related to the erodibility of the soil, which itself is inversely proportional to the soil density. This study provides new insights into the governing conditions and breach evolution mechanisms of landslide dams, as triggered by seepage and piping.",{"EN":351},"Hydromechanical constraints on piping failure of landslide dams: an experimental investigation",{"VOID":353},"[\"12107820536082836481\"]",{"VOID":355},"Awal, R., H. Nakagawa, M. Fujita, K. Kawaike, Y. Baba, and H. Zhang. 2011. Study on piping failure of natural dam. Annuals of Disaster Prevention Research Institute Kyoto University 54: 539–547.\nBrauns, J. 1985. Stability of layered granular soil under horizontal groundwater flow. In Proceedings of the 15 th International Congress on Large Dams, vol 1, Lausanne.\nCapra, L. 2007. Volcanic natural dams: identification, stability, and secondary effects. Natural Hazards 43(1): 45–61.\nCapra, L. 2011. Volcanic natural dams associated with sector collapses: textural and sedimentological constraints on their stability. In Natural and Artificial Rockslide Dams, ed. S.G. Evans, R.L. Hermanns, A. Strom, and G. Scarascia-Mugnozza, 279–294. Berlin Heidelberg: Springer.\nCasagli, N., L. Ermini, and G. Rosati. 2003. Determining grain size distribution of material composing landslide dams in the Northern Apennines: sampling and processing methods. Eng Geol (Amsterdam) 69: 83–97.\nChang, D.S., L.M. Zhang, Y. Xu, and R.Q. Huang. 2011. Field testing of erodibility of two landslide dams triggered by the 12 May Wenchuan earthquake. Landslides 8(3): 321–332.\nCharles, J.A. 1986. The significance of problems and remedial works at British earth dams. In Proceedings of BNCOLD\u002FIWES Conference on Reservoirs, Edinburgh, 123–141.\nCosta, J.E., and R.L. Schuster. 1988. The formation and failure of natural dams. Geological Society of America Bulletin 100: 1054–1068.\nCrosta, G.B., P. Frattini, N. Fusi, and R. Sosio. 2006. Formation, characterization and modelling of the 1987 Val Pola rock-avalanche dam (Italy). Italian J Eng Geol Envir, Special Issue 1: 145–150.\nDavies, T.R., and M.J. McSaveney. 2011. Rock-avalanche size and runout–implications for landslide dams. In Natural and Artificial Rockslide Dams, ed. S.G. Evans, R.L. Hermanns, A. Strom, and G. Scarascia-Mugnozza, 441–462. Berlin Heidelberg: Springer.\nDuman, T.Y. 2009. The largest landslide dam in Turkey: Tortum landslide. Engineering Geology 104(1): 66–79.\nDunning, S.A. 2006. The grain-size distribution of rock avalanche deposits in valley-confined settings. Italian J Eng Geol Environ 1: 117–121.\nDunning, S.A., and P.J. Armitage. 2011. The grain-size distribution of rock-avalanche deposits: implications for natural dam stability. In Natural and Artificial Rockslide Dams, ed. S.G. Evans, R.L. Hermanns, A. Strom, and G. Scarascia-Mugnozza, 479–498. Berlin Heidelberg: Springer.\nDunning, S.A., N.J. Rosser, D.N. Petley, and C.R. Massey. 2006. Formation and failure of the Tsatichhu landslide dam, Bhutan. Landslides 3(2): 107–113.\nFaulkner, H. 2006. Piping hazard on collapsible and dispersive soils in Europe. Soil Erosion in Europe 537–562\nFell, R., C.F. Wan, J. Cyganiewicz, and M. Foster. 2003. Time for development of internal erosion and piping in embankment dams. Journal of Geotechnical and Geoenvironmental Engineering 129(4): 307–314.\nFox, G.A., R.G. Felice, T.L. Midgley, G.V. Wilson, and A.S. Al‐Madhhachi. 2014. Laboratory soil piping and internal erosion experiments: evaluation of a soil piping model for low‐compacted soils. Earth Surface Processes and Landforms 39(9): 1137–1145.\nFread, D.L. 1988. The NWS DAMBRK model: Theoretical background\u002Fuser documentation. National Weather Service, NOAA: Hydrologic Research Laboratory.\nGlazyrin, G.Y., and V.N. Reyzvikh. 1968. Computation of the flow hydrograph for the breach of landslide lakes. Soviet Hydrology 5: 492–496.\nHanson, G.J., and K.R. Cook. 1997. Development of excess shear stress parameters for circular jet testing, vol. ASAE Paper No. 972227. St Joseph: American Society of Agricultural Engineering.\nHanson, G.J., and K.M. Robinson. 1993. The influence of soil moisture and compaction on spillway erosion. Transactions of the ASAE 36(5): 1349–1352.\nHanson, G.J., R.D. Tejral, S.L. Hunt, and D.M. Temple. 2010. Internal erosion and impact of erosion resistance. In Proceedings of the 30th US Society on Dams Annual Meeting and Conference, Sacramento, California, 773–784.\nJones, J.A.A. 1994. Soil piping and its hydrogeomorphic function. Cuaternario y Geomorfologia 8(3–4): 77–102.\nJones, J.A.A. 2004. Implications of natural soil piping for basin management in upland Britain. Land Degradation & Development 15(3): 325–349.\nKe, L., and A. Takahashi. 2012. Influence of internal erosion on deformation and strength of gap-graded non-cohesive soil. In Proceedings of the Sixth International Conference on Scour and Erosion, Paris, 847–854.\nKorup, O. 2004. Geomorphometric characteristics of New Zealand landslide dams. Engineering Geology 73(1): 13–35.\nMaknoon, M., and T.F. Mahdi. 2010. Experimental investigation into embankment external suffusion. Natural Hazards 54(3): 749–763.\nMarot, D., F. Bendahmane, and H.H. Nguyen. 2012. Influence of angularity of coarse fraction grains on internal erosion process. In Proceedings of the Sixth International Conference on Scour and Erosion, Paris, 887–894.\nMasannat, Y.M. 1980. Development of piping erosion conditions in the Benson area, Arizona, USA. Quarterly Journal of Engineering Geology and Hydrogeology 13(1): 53–61.\nMattsson, H., J.G.I. Hellström, and T.S. Lundström. 2008. On internal erosion in embankment dams. Research Report: Luleå University of Technology. Retrieved from http:\u002F\u002Fepubl.ltu.se\u002F1402-1528\u002F2008\u002F14\u002FLTU-FR-0814-SE.pdf.\nMora, S., C. Madrigal, J. Estrada, and R.L. Schuster. 1993. The 1992 Rio Toro landslide dam, Costa Rica. Landslide News 7: 19–22.\nOkeke, A.C., F. Wang, T. Sonoyama, and Y. Mitani. 2013. Laboratory experiments on landslide dam failure due to piping: An evaluation of 2011 typhoon-induced landslide and landslide dam in Western Japan. In Progress of Geo-Disaster Mitigation Technology in Asia, ed. F.W. Wang, M. Miyajima, T. Li, S. Wei, and T.F. Fathani, 525–545. Berlin Heidelberg: Springer.\nPushkarenko, V.P., and A.M. Nikitin. 1988. Experience in the regional investigation of the state of mountain lake dams in Central Asia and the character of breach mudflow formation. In Landslides and Mudflows, ed. E. Kozlovskii, 359–362. Moscow: UNEP\u002FUNESCO.\nRichards, K.S., and K.R. Reddy. 2012. Experimental investigation of initiation of backward erosion piping in soils. Geotechnique 62(10): 933–942.\nSchuster, R.L. 1995. Landslide dams-a worldwide phenomenon. In Proceedings of the Annual Symposium of the Japanese Landslide Society, Kansai Branch, Osaka, 1–23.\nShugar, D.H., and J.J. Clague. 2011. The sedimentology and geomorphology of rock avalanche deposits on glaciers. Sedimentology 58(7): 1762–1783.\nSidle, R.C., H. Kitahara, T. Terajima, and Y. Nakai. 1995. Experimental studies on the effects of pipeflow on throughflow partitioning. Journal of Hydrology 165(1): 207–219.\nSingh, V. 1996. Dam breach modeling technology. Water Science and Technology Library: Kleiwer Academic Publishers.\nStene, E.A. 1995. The Teton Basin Project: (Second Draft).. Bureau of Reclamation History Program.\nStrom, A. 2013. Geological prerequisites for landslide dams’ disaster assessment and mitigation in Central Asia. In Progress of Geo-Disaster Mitigation Technology in Asia, ed. F.W. Wang, M. Miyajima, T. Li, S. Wei, and T.F. Fathani, 17–53. Berlin Heidelberg: Springer.\nWan, C.F., and R. Fell. 2004. Investigation of rate of erosion of soils in embankment dams. Journal of Geotechnical and Geoenvironmental Engineering 130(4): 373–380.\nWang, G., R. Huang, T. Kamai, and F. Zhang. 2013. The internal structure of a rockslide dam induced by the 2008 Wenchuan (Mw 7.9) earthquake, China. Engineering Geology 156: 28–36.\nWassmer, P., J.L. Schneider, N. Pollet, and C. Schmitter-Voirin. 2004. Effects of the internal structure of a rock–avalanche dam on the drainage mechanism of its impoundment, Flims sturzstrom and Ilanz paleo-lake, Swiss Alps. Geomorphology 61(1): 3–17.\nWeidinger, J.T. 2006. Landslide dams in the high mountains of India, Nepal and China-stability and life span of their dammed lakes. Italian Journal of Engineering Geology and Environment 1: 67–80.\nWilson, G.V. 2009. Mechanisms of ephemeral gully erosion caused by constant flow through a continuous soil‐pipe. Earth Surface Processes and Landforms 34(14): 1858–1866.\nWilson, G. 2011. Understanding soil‐pipe flow and its role in ephemeral gully erosion. Hydrological Processes 25(15): 2354–2364.\nWit, J.D., J.B. Sellmeijer, and A. Penning. 1981. Laboratory testing on piping, 517–520. In: Tenth International Conference on Soil Mechanics and Foundation Engineering.",{"VOID":357},"10.1186\u002Fs40677-016-0038-9","2024-06-25T10:38:14.192+00:00","http:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-016-0038-9",[361,378],{"id":362,"sortIndex":19,"researcher":18,"roles":363,"affiliations":364,"properties":373,"displayName":375,"givenName":18,"familyName":18},"ed4b1130-e3c2-401b-ab81-71c3a8fa0e8e",[180],[365],{"id":366,"sortIndex":19,"affiliation":367,"properties":18},"6f0cd9b9-5544-4670-893b-bd19b25bb677",{"id":366,"createTime":18,"updateTime":18,"relativeEntities":368,"slug":18,"properties":369,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":372,"statistic":18},[],{"title":370},{"VI":371},"Department of Geoscience, Graduate School of Science and Engineering, Shimane University, Matsue, Japan",[],{"title":374,"gsAuthor":376},{"VI":375},"Austin Chukwueloka-Udechukwu Okeke",{"VOID":377},"[\"0MSjTKQAAAAJ\"]",{"id":379,"sortIndex":192,"researcher":18,"roles":380,"affiliations":381,"properties":388,"displayName":390,"givenName":18,"familyName":18},"0daf2593-3e2b-4046-9074-87c038b3cc7e",[180],[382],{"id":366,"sortIndex":19,"affiliation":383,"properties":18},{"id":366,"createTime":18,"updateTime":18,"relativeEntities":384,"slug":18,"properties":385,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":387,"statistic":18},[],{"title":386},{"VI":371},[],{"title":389,"gsAuthor":391},{"VI":390},"Fawu Wang",{"VOID":392},"[\"bPA7Z8cAAAAJ\"]",{"url":359,"publisher":394,"properties":450},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":395,"slug":10,"properties":396,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":399,"manageAffiliations":419,"indexDatabases":430,"url":106,"thumbnailPath":18,"statistic":445,"gsStatistic":18,"type":149,"analyzePriority":18},[],{"issn":397,"title":398},{"VOID":13},{"EN":15},[400,404,408,411,415],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":401,"label":402,"description":403,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":405,"label":406,"description":407,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":409,"label":410,"description":18,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{"id":39,"createTime":18,"updateTime":18,"relativeEntities":412,"label":413,"description":414,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":42},{},{"id":45,"createTime":18,"updateTime":18,"relativeEntities":416,"label":417,"description":418,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":48},{},[420,425],{"id":52,"createTime":18,"updateTime":18,"relativeEntities":421,"slug":18,"properties":422,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":424,"statistic":18},[],{"title":423},{"EN":56},[],{"id":59,"createTime":18,"updateTime":18,"relativeEntities":426,"slug":18,"properties":427,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":429,"statistic":18},[],{"title":428},{"EN":63},[65],[431,438],{"id":68,"indexDatabase":432,"url":81,"indexYears":18,"academicFieldIds":437,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":433,"label":434,"description":435,"key":77,"publicationTags":436,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"id":86,"indexDatabase":439,"url":97,"indexYears":98,"academicFieldIds":444,"indexDatabaseRanking":105},{"id":88,"createTime":18,"updateTime":18,"relativeEntities":440,"label":441,"description":442,"key":94,"publicationTags":443,"standard":18},[],{"EN":91,"VI":91},{"EN":91,"VI":93},[96],[100,101,102,103,104],{"impactFactor":19,"impactFactorByYear":446,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":447,"totalCitation":130,"totalCitationByYear":448,"totalCitationPerPublication":139,"totalCitationPerPublicationByYear":449,"hindexLast5Year":148,"hindex":148},{"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":123,"2024":121},{"2015":132,"2016":133,"2017":134,"2018":135,"2019":136,"2020":137,"2022":138},{"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2022":147},{"pages":451,"volume":453},{"VOID":452},"1-17",{"VOID":454},"3","2016-04-01",2016,"2026-07-13T21:59:25.951+00:00",[79,105],{"id":460,"createTime":461,"updateTime":462,"relativeEntities":463,"slug":464,"properties":465,"entityType":171,"verifyStatus":172,"verifyTime":475,"verifyNote":174,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":476,"fullTextUrl":18,"authors":477,"publicationType":272,"publisherRelationship":592,"citationCount":18,"citationInfo":18,"publishDate":654,"publishYear":655,"citationAnalyzeStatus":337,"lastCitationAnalyze":656,"indexDatabases":657,"openAccess":18,"references":18,"isForceReanalyzing":340},"8c983842-7d04-46a4-81da-5b51f8dd45b3","2024-01-17T09:37:02.716+00:00","2026-05-07T08:06:25.066+00:00",[],"The-impact-of-COVID-19-outbreak-and-perceptions-of-people-towards-household-waste-management-chain-in-Nepal",{"abstract":466,"title":468,"gsPaper":470,"references":471,"doi":473},{"EN":467},"The spread of COVID-19 is posing significant challenges to the household (HH) waste management sectors putting waste personnel and concerned bodies under massive pressure. The chain of collection, segregation, recycling, and disposal of household generated wastes is interrupted. This study aimed to assess how the household waste management chain was disrupted by novel coronavirus in Nepal and find the perception of the people towards the existing household waste management system (HHWMS). A descriptive online survey was carried out among 512 people using a cross-sectional research design and data was collected through a self-administered questionnaire method. Both descriptive, as well as inferential tests, were conducted using SPSS software. The finding of this study showed that 62.3% of respondents were not satisfied with the present HHWMS. Furthermore, there was a significant association of the satisfaction level of household waste management during coronavirus outbreak with gender, waste volume change in lockdown, PPE for waste collectors, and education on waste handling techniques provided by the government sector at 5% level of significance (p \u003C 0.05). Proper HH waste management has become a challenge, and to address this some innovative works such as awareness programs for people, health and hygiene related support to waste workers, and effective policy formulation and implementation should be done by the Government of Nepal.",{"EN":469},"The impact of COVID-19 outbreak and perceptions of people towards household waste management chain in Nepal",{"VOID":166},{"VOID":472},"Acharya H (2016) Municipal solid waste management; Problem and Opportunity 7\nAlam R, Chowdhury MAI, Hasan GMJ, Karanjit B, Shrestha LR (2008) Generation, storage, collection and transportation of municipal solid waste – a case study in the city of Kathmandu, capital of Nepal. Waste Manag 28(6):1088–1097. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.wasman.2006.12.024\nAldaco R, Hoehn D, Laso J, Margallo M, Ruiz-Salmón J, Cristobal J, Kahhat R, Villanueva-Rey P, Bala A, Batlle-Bayer L, Fullana-i-Palmer P, Irabien A, Vazquez-Rowe I (2020) Food waste management during the COVID-19 outbreak: a holistic climate, economic and nutritional approach. Sci Total Environ 742:140524. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2020.140524\nAsian Development Bank (2013) Solid waste management in Nepal: Current status and policy recommendations. http:\u002F\u002Fsite.ebrary.com\u002Fid\u002F10900904\nAwale S, Kumar R (2020) The COVID-19 Plastic Pandemic Inter Press Service. http:\u002F\u002Fwww.ipsnews.net\u002F2020\u002F08\u002Fcovid-19-plastic-pandemic\u002F\nBelhadi A, Kamble SS, Khan SAR, Touriki FE, Kumar MD (2020) Infectious waste management strategy during COVID-19 pandemic in Africa: an integrated decision-making framework for selecting sustainable technologies. Environ Manag 66(6):1085–1104. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00267-020-01375-5\nBenker B (2021) Stockpiling as resilience: defending and contextualising extra food procurement during lockdown. Appetite 156:104981. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.appet.2020.104981\nCarbone C (2020) Risk of COVID-19 transmission from wastewater higher than believed, study claims. Fox News. https:\u002F\u002Fwww.foxnews.com\u002Fscience\u002Frisk-of-covid-19-transmission-from-waste-water-higher-than-believed-study-claims\nCoronavirus (COVID-19) (2021) Google News. https:\u002F\u002Fnews.google.com\u002Fcovid19\u002Fmap?hl=en-USandgl=USandceid=US:en\nCosgrove K, Vizcaino M, Wharton C (2021) COVID-19-related changes in perceived household food waste in the United States: a cross-sectional descriptive study. Int J Environ Res Public Health 18(3):1104. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijerph18031104\nCoVid19-Dashboard:MoHP (2021) https:\u002F\u002Fcovid19.mohp.gov.np\u002F\nDahal Y, Adhikari B (2018) Characterization and quantification of municipal solid waste in Jeetpur Simara sub- Metropolitan City, Nepal. 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Research in Globalization 2:100033. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.resglo.2020.100033\nParashar N, Hait S (2021) Plastics in the time of COVID-19 pandemic: protector or polluter? Sci Total Environ 759:144274. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2020.144274\nPathak DR, Mainali B, Abuel-Naga H, Angove M, Kong I (2020) Quantification and characterization of the municipal solid waste for sustainable waste management in newly formed municipalities of Nepal. Waste Manag Res 38(9):1007–1018. https:\u002F\u002Fdoi.org\u002F10.1177\u002F0734242X20922588\nPatrício Silva AL, Prata JC, Walker TR, Campos D, Duarte AC, Soares AMVM, Barclò D, Rocha-Santos T (2020) Rethinking and optimising plastic waste management under COVID-19 pandemic: policy solutions based on redesign and reduction of single-use plastics and personal protective equipment. 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land subsidence has been a big concern in Montgomery County, Texas, U.S. since the 2000s. As of 2020, approximately half of the entire county is experiencing subsidence over 5 mm\u002Fyear. This study aims to investigate ongoing land subsidence in Montgomery County using groundwater-level, extensometer, and GPS datasets. According to this study, land subsidence in Montgomery County since the mid-2000s is primarily contributed by sediment compaction in the Evangeline and Jasper aquifers; the compaction of Jasper aquifer contributes approximately one-third of the land subsidence since the mid-2000s; the pre-consolidation heads of the Chicot, Evangeline, and Jasper aquifers in Montgomery County are close to each other, approximately 15–25 m below mean sea level; the virgin-compaction\u002Fhead-decline ratio is approximately 1:250 in the Evangeline aquifer and 1:800 in the Jasper aquifer in central and southern Montgomery County. As of 2020, the Jasper groundwater-level altitude is approximately 20–40 m below the pre-consolidation head in the central and southern Montgomery County; the Evangeline groundwater-level altitude is about 40–60 m below the pre-consolidation head. Land subsidence will continue to occur as long as the groundwater-level altitude in either the Evangeline or the Jasper aquifer remains below the pre-consolidation head.",{"EN":668},"Land subsidence and aquifer compaction in Montgomery County, Texas, U.S.: 2000–2020",{"VOID":670},"[\"10405915285398969356\"]",{"VOID":672},"Agudelo G, Wang G, Liu Y, Bao Y, Turco MJ (2020) GPS geodetic infrastructure for subsidence and fault monitoring in Houston, Texas, USA. Proc Int Assoc Hydrol 382:11–18\nBaker ET, Jr (1979) Stratigraphic and hydrogeologic framework of part of the coastal plain of Texas. Texas Department of Water Resources Report 236, p 43\nBraun CL, Ramage JK (2020) Status of groundwater-level altitudes and long-term groundwater-level changes in the Chicot, Evangeline, and Jasper aquifers, Houston-Galveston region, Texas, 2020. U.S. Geological Survey Scientific Investigations Report 2020–5089, p 18\nCampbell MD, Campbell MD, Wise HM (2018) Growth faulting and subsidence in the Houston, Texas area: guide to the origins, relationships, hazards, potential impacts and methods of investigation: an update. J Geol Geosci 2:1–53\nCasarez IR (2020) Aquifer extents in the coastal lowlands aquifer system regional groundwater availability study area in Texas, Louisiana, Mississippi, Alabama, and Florida. U.S. Geological Survey data release. https:\u002F\u002Fdoi.org\u002F10.5066\u002FP9BH2KG2\nChowdhury AH, Turco MJ (2006) Geology of the Gulf coast aquifer, Texas. Texas Water Dev Board Rep 365:23–50\nCoplin LS, Galloway D (1999) Houston-Galveston, Texas. Land subsidence in the United States. US Geol Surv Circ 1182:35–48\nFurnans J, Keester M, Colvin D, Bauer J, Barber J, Gin G, Danielson V, Erickson L, Ryan R, Khorzad K, Worsley A, Snyder G (2018) Final report: identification of the vulnerability of the major and minor aquifers of Texas to subsidence with regard to groundwater pumping. Texas Water Development Board, Contract report No. 1648302062, p 434\nGabrysch RK (1967) Development of ground water in the Houston district, Texas, 1961–65. Texas Water Dev Board Rep 63:35\nGalloway DL, Burbey TJ (2011) Review: regional land subsidence accompanying groundwater extraction. Hydrogeol J 19:1459–1486\nGreuter A, Petersen P (2021) Determination of groundwater withdrawal and subsidence in Harris and Galveston counties—2020. Harris-Galveston Subsidence District Report. https:\u002F\u002Fhgsubsidence.org\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002F2020-HGSD-AGR_Full-Report-1.pdf\nHelm DC (1975) One-dimensional simulation of aquifer system compaction near Pixley, Calif.: 1. constant parameters. Water Resour Res 11(3):465–478\nKasmarek MC (2012) Hydrogeology and simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas, 1891–2009 (ver. 1.1, December 2013). U.S. Geological Survey Scientific Investigations Report 2012–5154, p 55\nKasmarek MC, Robinson JL (2004) Hydrogeology and simulation of ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas. U.S. Geological Survey Scientific Investigations Report 2004–5102, p 111\nKasmarek MC, Ramage JK, Johnson MR (2016) Water-level altitudes 2016 and water-level changes in the Chicot, Evangeline, and Jasper aquifers and compaction 1973–2015 in the Chicot and Evangeline aquifers, Houston-Galveston region, Texas. U.S. Geological Survey Scientific Investigations Map 3365, pamphlet, 16 sheets, scale 1:100,000\nKearns TJ, Wang G, Bao Y, Jiang J, Lee D (2015) Current land subsidence and groundwater level changes in the Houston metropolitan area (2005–2012). J Surv Eng 141(4):05015002\nKearns TJ, Wang G, Turco MJ, Welch J, Tsibanos V, Liu H (2019) Houston16: a stable geodetic reference frame for subsidence and faulting study in the Houston metropolitan area, Texas. US Geod Geodyn 10(5):382–393\nKelley V, Deeds N, Young SC, Pinkard J, Sheng Z, Seifert J, Marr S (2018) Subsidence risk assessment and regulatory considerations for the brackish Jasper aquifer—Harris-Galveston and Fort Bend Subsidence Districts. Report prepared for Harris-Galveston Subsidence District and Fort Bend Subsidence District, p 69\nKhan SD, Stewart RR, Otoum M, Chang L (2013) A geophysical investigation of the active Hockley fault system near Houston, Texas. Geophysics 78:B177–B185\nLiu Y, Li J, Fang Z (2019a) Groundwater level change management on control of land subsidence supported by borehole extensometer compaction measurements in the Houston-Galveston region. Texas Geosci 9(5):223\nLiu Y, Sun X, Wang G, Turco MJ, Agudelo G, Bao Y, Zhao R, Shen S (2019b) Current activity of the Long Point fault in Houston, Texas constrained by continuous GPS measurements (2013–2018). Remote Sens 11(10):1213\nLSGCD (2013) Lone Star Groundwater Conservation District Management Plan—re-adopted November 12, 2013. https:\u002F\u002Fwww.lonestargcd.org\u002Fdistrict-rules-1\nLSGCD (2020) 2020 Lone Star Groundwater Conservation District Management Plan, as approved on May 15, 2020. https:\u002F\u002Fwww.lonestargcd.org\u002Fdistrict-rules-1\nMiller MM, Shirzaei M (2019) Land subsidence in Houston correlated with flooding from Hurricane Harvey. Remote Sens Environ 225:368–378\nPetersen C, Turco MJ, Vinson A, Turco JA, Petrov A, Evans M (2020) Groundwater regulation and the development of alternative source waters to prevent Subsidence, Houston region, Texas, USA. Proc IAHS 382:797–801\nPopkin BP (1971) Groundwater resources of Montgomery County, Texas. Texas Water Dev Board Rep 136:143\nQu F, Lu Z, Zhang Q, Bawden GW, Kim J, Zhao C, Qu W (2015) Mapping ground deformation over Houston-Galveston, Texas using multi-temporal InSAR. Remote Sens Environ 169:290–306\nQu F, Lu Z, Kim JW, Zheng W (2019) Identify and monitor growth faulting using InSAR over northern greater Houston, Texas, USA. Remote Sens 11(12):1498\nRamage JK (2020) Depth to groundwater measured from wells completed in the Chicot, Evangeline, and Jasper aquifers, Houston-Galveston region, Texas, 2020. U.S. Geological Survey data release\nRamage JK, Shah SD (2019) Cumulative compaction of subsurface sediments in the Chicot and Evangeline aquifers in the Houston-Galveston region, Texas (ver. 2.0, June 2020). U.S. Geological Survey data release\nShah SD, Ramage JK, Braun CL (2018) Status of groundwater-level altitudes and long-term groundwater-level changes in the Chicot, Evangeline, and Jasper aquifers, Houston-Galveston region, Texas, 2018. U.S. Geological Survey Scientific Investigations Report 2018–5101, p 18\nTerzaghi K (1925) Principles of soil mechanics: I-Phenomena of cohesion of clays. Eng News-Rec 95(19):742–746\nThornhill MR, Keester MR (2020) Subsidence investigations—phase 1: assessment of past and current investigations, prepared for Lone Star Groundwater Conservation District. https:\u002F\u002Fwww.lonestargcd.org\u002Fsubsidence\nTurco MJ, Petrov A (2015) Effects of groundwater regulation on aquifer-system compaction and subsidence in the Houston-Galveston Region, Texas, USA. Proc Int Assoc Hydrol Sci 372:511–514\nWang G (2021) The 95% confidence interval for the GNSS-derived site velocities. J Surv Eng. https:\u002F\u002Fdoi.org\u002F10.1061\u002F(ASCE)SU.1943-5428.0000390\nWang G, Soler T (2014) Measuring land subsidence using GPS: ellipsoid height vs. orthometric height. J Surv Eng 141:05014004\nWang G, Yu J, Ortega J, Saenz G, Burrough T, Neill R (2013) A stable reference frame for the study of ground deformation in the Houston metropolitan area, Texas. J Geod Sci 3:188–202\nWang G, Yu J, Kearns TJ, Ortega J (2014) Assessing the accuracy of long-term subsidence derived from borehole extensometer data using GPS observations: case study in Houston, Texas. J Surv Eng 140(3):05014001\nWang G, Welch J, Kearns T, Yang L, Serna J Jr (2015) Introduction to GPS geodetic infrastructure for land subsidence monitoring in Houston, Texas, USA. Proc Int Assoc Hydrol Sci 372:297–303\nWang G, Turco M, Soler T, Kearns TJ, Welch J (2017) Comparisons of OPUS and PPP solutions for subsidence monitoring in the greater Houston area. J Surv Eng 143(4):05017005\nWang G, Zhou X, Wang K, Ke X, Zhang Y, Zhao R, Bao Y (2020) GOM20: a stable geodetic reference frame for subsidence, faulting, and sea-level rise studies along the Coast of the Gulf of Mexico. Remote Sens 12(3):350\nWelch J (2018) Current ground motions in Montgomery, West Liberty, and Northern Harris counties derived from continuous GPS motions. Mather Thesis, Department of Earth and Atmospheric Sciences, University of Houston\nWessel P, Smith WHF, Scharroo R, Luis J, Wobbe F (2013) Generic mapping tools: improved version released. EOS Trans Am Geophys Union 94(45):409–410\nYoung SC, Ewing T, Hamlin S, Baker E, Lupton D (2012) Final report—updating the hydrogeologic framework for the northern portion of the gulf coast aquifer. Contract report for the Texas Water Development Board, p 285\nYoung SC, Jigmond M, Deeds N, Blainey J, Ewing TE, Banerj D, Piemonti D, Jones T, Griffith C, Lupton D, Martinez G, Hudson C, Hamlin S, Sutherland J (2016) Final report: identification of potential brackish groundwater production areas—Gulf Coast Aquifer System. Contract report to the Texas Water Development Board, p 636\nYu J, Wang G, Kearns TJ, Yang L (2014) Is there deep-seated subsidence in the Houston-Galveston area. J Geophys 942834:1–11\nZhou F (2020) The correlation between current land subsidence and groundwater levels in Montgomery County, Texas. Mather Thesis, Department of Earth and Atmospheric Sciences, University of Houston\nZhou X, Wang G, Wang K, Liu H, Lyu H, Turco MJ (2021) Rates of natural subsidence and submergence along the Texas coast derived from GPS and tide gauge measurements (1904–2020). J Surv Eng 147(4):04021020",{"VOID":674},"10.1186\u002Fs40677-021-00199-7","2024-05-16T15:07:23.809+00:00","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-021-00199-7",[678,693,708,721,736],{"id":679,"sortIndex":19,"researcher":18,"roles":680,"affiliations":681,"properties":690,"displayName":692,"givenName":18,"familyName":18},"2a87ccd5-9871-4cce-b91f-421ff578b5f5",[180],[682],{"id":683,"sortIndex":19,"affiliation":684,"properties":18},"567b301d-c8f3-447d-b801-c8f66d8b30e3",{"id":683,"createTime":18,"updateTime":18,"relativeEntities":685,"slug":18,"properties":686,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":689,"statistic":18},[],{"title":687},{"VI":688},"Department of Earth and Atmospheric Sciences, University of Houston, Houston, USA",[],{"title":691},{"VI":692},"Kuan 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are the second biggest natural disasters in Indonesia, occurring mostly in volcanic area with thick and clay rich soils. Examining the changes of land surface and soil morphology brought about by a particular landslide is usually the first step required for vegetative rehabilitation. Most examinations to date, however, have been based on general characters rather than on soil morphology, including physical and chemical characteristics of the soil, which are usually locally specific. This study investigates the morphological characteristics of soil in a landslide-prone slope region of Sumbing Volcano, in Central Java Province of Indonesia. The field investigations are conducted at three landslides sites. It starts with interpreting small format areal-photographs which have been geo-corrected, followed by the delineation of landslide zones (i.e. crowns, main scarps, heads, bodies and toes) based on morphological analysis of the landslide sites. Finally, identification of morphological, physical and chemical characteristics of the soil in each of the landslide zones are conducted in the field, along with laboratory tests. The results demonstrate that soil morphology is unique for each of the landslide zones. The characters of the undisturbed soil, as indicated by well-defined genetic horizons, are found in the crown zones. Outcrop of high clay content soil material layers are seen in the main scarp zones. Meanwhile pedoturbation processes are evident in the zone of bodies and toes, suggesting that the soil is prone for erosion. If natural erosions in these zones are not controlled and\u002For unmitigated, the situation will trigger landslide reactivations. We suggest that in studying landslide, one also considers the characters of soil morphology, as this additional information provides a more complete understanding of both land surface morphology and soil morphology to inform landslide vegetative rehabilitation.",{"EN":827},"The distribution of soil morphological characteristics for landslide-impacted Sumbing Volcano, Central Java - Indonesia",{"VOID":166},{"VOID":830},"Candraningrum ZR (2017) Hubungan mikrorelief dengan karakteristik fisik material tanah permukaan di wilayah longsor aktif (Kasus longsor besar di Desa Margoyoso, Kecamatan Salaman, Kabupaten Magelang, Provinsi Jawa Tengah). Gadjah Mada University. Retrieved from http:\u002F\u002Fetd.repository.ugm.ac.id\u002Findex.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=110330&obyek_id=4\nChae BG, Lee JH, Park HJ, Choi J (2015) A method for predicting the factor of safety of an infinite slope based on the depth ratio of the wetting front induced by rainfall infiltration. Nat Hazards Earth Syst Sci 15:1835–1849. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fnhess-15-1835-2015\nCheng CH, Hsiao SC, Huang YS, Hung CY, Pai CW, Chen CP, Menyailo OV (2016) Landslide-induced changes of soil physicochemical properties in Xitou, Central Taiwan. Geoderma 265:187–195. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geoderma.2015.11.028\nCheng YM, Lau CK (2014) In: CRC Press Taylor & Francis Group (ed) Slope stability analysis and stabilization ISBN: 978-1-4665-8284-2\nGlade T, Crozier MJ (2010) Landslide geomorphology in a changing environment. Geomorphology 120:1–2. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2009.09.018\nGlenn NF, Streutker DR, Chadwick DJ, Thackray GD, Dorsch SJ (2006) Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity. Geomorphology 73:131–148. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2005.07.006\nGylland AS, Rueslåtten H, Jostad HP, Nordal S (2013) Microstructural observations of shear zones in sensitive clay. Eng Geol 163:75–88. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.sssenggeo.2013.06.001\nHadmoko DS, Lavigne F, Sartohadi J, Hadi P, Winaryo (2010) Landslide hazard and risk assessment and their application in risk management and landuse planning in eastern flank of Menoreh Mountains, Yogyakarta Province, Indonesia. Nat Hazards 54:623–642. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11069-009-9490-0\nHassen G, Bantider A (2020) Assessment of drivers and dynamics of gully erosion in case of Tabota Koromo and Koromo Danshe watersheds , South Central. Geoenvironmental Disasters 7(5):1–13. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40677-019-0138-4\nJohannes A, Matter A, Schulin R, Weisskopf P, Baveye PC, Boivin P (2017) Optimal organic carbon values for soil structure quality of arable soils. Does clay content matter? Geoderma 302:14–21. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geoderma.2017.04.021\nKang K, Ponomarev A, Zerkal O, Huang S, Lin Q (2019) Shallow landslide susceptibility mapping in Sochi ski-jump area using GIS and numerical Modelling. Int J Geo Inform 8:148–163. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijgi8030148\nLi X, Cheng X, Chen W, Chen G, Liu S (2015) Identification of forested landslides using LiDar data, object-based image analysis, and machine learning algorithms. Remote Sens 7:9705–9726. https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs70809705\nLindsay JB, Newman DR, Francioni A (2019) Scale-optimized surface roughness for topographic analysis. Geoscience 9(7):322–337. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fgeosciences9070322\nMaeda H, Sasaki T, Furuta K, Takashima K, Umemura A, Kohno M (2012) Relationship between landslides, geologic structures, and hydrothermal alteration zones in the Ohekisawa-Shikerebembetsugawa landslide area, Hokkaido, Japan. J Earth Sci Eng 2:317–327. https:\u002F\u002Fdoi.org\u002F10.17265\u002F2159-581X\u002F2012.06.001\nMalizia JP, Shakoor A (2018) Effect of water content and density on strength and deformation behavior of clay soils. Eng Geol 244:125–131. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.enggeo.2018.07.028\nMarfai MA, King L, Singh LP, Mardiatno D, Sartohadi J, Hadmoko DS, Dewi A (2008) Natural hazards in Central Java Province , Indonesia : an overview. Environ Geol 56:335–351. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00254-007-1169-9\nMhazo N, Chivenge P, Chaplot V (2016) Tillage impact on soil erosion by water: discrepancies due to climate and soil characteristics. Agric Ecosyst Environ 230:231–241. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agee.2016.04.033\nNational Disaster Management Agency (2019). Data Informasi Bencana Indonesia. Badan Nasional Penanggulangan Bencana Indonesia. https:\u002F\u002Fbnpb.cloud\u002Fdibi\u002F.\nNoviyanto A, Purwanto MS, Supriyadi (2017) The assessment of soil quality of various age of land reclamation after coal mining : a chronosequence study. J Degraded Mining Lands Manage 5(1):1009–1018. https:\u002F\u002Fdoi.org\u002F10.15243\u002Fjdmlm.2017.051.1009\nPal DK, Wani SP, Sahrawat KL (2012) Vertisols of tropical Indian environments : Pedology and edaphology. Geoderma 189–190:28–49. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geoderma.2012.04.021\nPal DK, Wani SP, Sahrawat KL, Srivastava P (2014) Red ferruginous soils of tropical Indian environments : a review of the pedogenic processes and its implications for edaphology. Catena 121:260–278. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2014.05.023\nPierre TJ, Primus AT, Simon BD, Philemon ZZ, Hamadjida G, Monique A, Pierre NJ, Lucien BD (2019) Characteristics, classification and genesis of vertisols under seasonally contrasted climate in the Lake Chad Basin, Central Africa. J Afr Earth Sci 150:176–193. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jafrearsci.2018.11.003\nPirajno F (2009) Hydrothermal processes and mineral systems. Springer, Dordrecht. Retrieved from, Dordrecht. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-1-4020-8613-7\nPiron D, Boizard H, Heddadj D, Pérès G, Hallaire V, Cluzeau D (2017) Indicators of earthworm bioturbation to improve visual assessment of soil structure. Soil Tillage Res 173:53–63. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.still.2016.10.013\nPulungan NA, Sartohadi J (2018a) New approach to soil formation in the transitional landscape zone : weathering and alteration of parent rocks. J Environ 5(1):1–7. https:\u002F\u002Fdoi.org\u002F10.20448\u002Fjournal.505.2018.51.1.7\nPulungan NA, Sartohadi J (2018b) Variability of soil development in hilly region, Bogowonto catchment, Java, Indonesia. Int J Soil Sci 13(1):1–8. https:\u002F\u002Fdoi.org\u002F10.3923\u002Fijss.2018.1.8\nRay RL, De Smedt F (2009) Slope stability analysis on a regional scale using GIS : a case study from Dhading , Nepal. Environ Geol 57:1603–1611. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00254-008-1435-5\nRegmi AD, Yoshida K, Dhital MR, Devkota K (2013) Effect of rock weathering , clay mineralogy , and geological structures in the formation of large landslide , a case study from Dumre Besei landslide , Lesser Himalaya Nepal. Landslide 10:1–13. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10346-011-0311-7\nRomán-sánchez A, Reimann T, Wallinga J, Vanwalleghem T (2019) Bioturbation and erosion rates along the soil-hillslope conveyor belt , part 1 : Insights from single-grain feldspar luminescence. Earth Surf Process Landf 44:2051–2065. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fesp.4628\nRuiz S, Or D, Schymanski SJ (2015) Soil penetration by earthworms and plant roots — mechanical energetics of Bioturbation of compacted soils. PLoS One 10(6):1–26. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0128914\nSambodo AP, Setiawan MA, Rokhmaningtyas RP (2018) The evaluation of modified productivity index method on the transitional volcanic-tropical landscape. IOP Conference Series 200(1):1–9. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1755-1315\u002F200\u002F1\u002F012011\nSartohadi J, Pulungan NAHJ, Nurudin M, Wahyudi W (2018) The ecological perspective of landslides at soils with high clay content in the middle Bogowonto watershed, Central Java, Indonesia. Appl Environ Soil Sci 2018:1–9. https:\u002F\u002Fdoi.org\u002F10.1155\u002F2018\u002F2648185\nSchaetzl RJ, Anderson S (2005) Soils genesis and geomorphology. Cambridge University Press, New York ISBN: 978-0-511-11104-4 Retrieved from www.cambridge.org\u002F9780521812016\nSchoeneberger PJ, Wysocki DA, Benham EC, Soil Survey Staff (2012) Field book for describing and sampling soils, version 3.0. Natural Resources Conservation Service. National Soil Survey Center, Lincoln Retrieved from https:\u002F\u002Fbooks.google.com\u002Fbooks?hl=it&lr=&id=nmfK6wJuIs8C&pgis=1\nSchrumpf M, Guggenberger G, Valarezo C, Zech W (2001) Tropical montane rain forest soils: development and nutrient status along an altitudinal gradient in the south Ecuadorian Andes. Erde 132(1):43–59 Retrieved from http:\u002F\u002Feref.uni-bayreuth.de\u002Fid\u002Feprint\u002F22821\nSidle RC, Ochiai H (2006) LANDSLIDES processes, prediction, and land use. American Geophysical Union, Washington DC ISBN: 978-0-87590-322-4\nSparling G, Ross D, Trustrum N, Arnold G, West A, Speir T, Schipper L (2003) Recovery of topsoil characteristics after landslip erosion in dry hill country of New Zealand, and a test of the space-for-time hypothesis. Soil Biol Biochem 35:1575–1586. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.soilbio.2003.08.002\nSzokoli K, Szarka L, Metwaly M, Kalmar J, Pracser E, Szalai S (2018) Characterisation of a landslide by its fracture system using electric resistivity tomography and pressure probe methods. Acta Geod Geophys 53:15–30. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40328-017-0199-3\nVan Bemmelen RW (1949) The geology of Indonesia Vol. I A. The Netherland Goverment Printing\nVan Eynde E, Dondeyne S, Isabirye M, Deckers J, Poesen J (2017) Impact of landslides on soil characteristics: implications for estimating their age. Catena 157:173–179. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2017.05.003\nWhitesides CJ (2015) The bioturbation of Olympic marmots (Marmota olympus) and their impacts on soil properties. Phys Geogr 36(3):202–214. https:\u002F\u002Fdoi.org\u002F10.1080\u002F02723646.2015.1035625\nWida WA, Maas A, Sartohadi J (2019) Pedogenesis of Mt. Sumbing volcanic ash above the alteration clay layer in the formation of landslide susceptible soils in Bompon sub-watershed. Ilmu Pertanian (Agricultural Science) 4(1):15–22. https:\u002F\u002Fdoi.org\u002F10.22146\u002Fipas.41893\nYu B, Zhu Y, Liu Y (2017) Topographical factor-based shallow landslide hazard assessment : a case of Dayi area of Guizhou Province in China. Geoenvironmental Disasters 4(24):1–17. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40677-017-0088-7",{"VOID":832},"10.1186\u002Fs40677-020-00158-8","2024-05-15T13:09:07.291+00:00","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-020-00158-8",[836,851,866],{"id":837,"sortIndex":19,"researcher":18,"roles":838,"affiliations":839,"properties":848,"displayName":850,"givenName":18,"familyName":18},"ac79a8e5-56b0-4136-9486-bbc48fbc8b70",[180],[840],{"id":841,"sortIndex":19,"affiliation":842,"properties":18},"aed77d49-6a7c-48ca-b781-fffb6045aea9",{"id":841,"createTime":18,"updateTime":18,"relativeEntities":843,"slug":18,"properties":844,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":847,"statistic":18},[],{"title":845},{"VI":846},"Master Program in Soil Science, Universitas Gadjah Mada, Yogyakarta, Indonesia",[],{"title":849},{"VI":850},"Amir Noviyanto",{"id":852,"sortIndex":192,"researcher":18,"roles":853,"affiliations":854,"properties":863,"displayName":865,"givenName":18,"familyName":18},"6c76109f-6b1b-443c-917f-f6fde049ed4e",[180],[855],{"id":856,"sortIndex":19,"affiliation":857,"properties":18},"c868139f-eb9e-43c7-b8a8-7256fc9c1cbd",{"id":856,"createTime":18,"updateTime":18,"relativeEntities":858,"slug":18,"properties":859,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":862,"statistic":18},[],{"title":860},{"VI":861},"Department of Soil Science, Universitas Gadjah Mada, Yogyakarta, Indonesia",[],{"title":864},{"VI":865},"Junun Sartohadi",{"id":867,"sortIndex":218,"researcher":18,"roles":868,"affiliations":869,"properties":876,"displayName":878,"givenName":18,"familyName":18},"45f6111f-d548-4d37-b2ea-ce6a3d7be11e",[180],[870],{"id":856,"sortIndex":19,"affiliation":871,"properties":18},{"id":856,"createTime":18,"updateTime":18,"relativeEntities":872,"slug":18,"properties":873,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":875,"statistic":18},[],{"title":874},{"VI":861},[],{"title":877},{"VI":878},"Benito Heru Purwanto",{"url":834,"publisher":880,"properties":936},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":881,"slug":10,"properties":882,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":885,"manageAffiliations":905,"indexDatabases":916,"url":106,"thumbnailPath":18,"statistic":931,"gsStatistic":18,"type":149,"analyzePriority":18},[],{"issn":883,"title":884},{"VOID":13},{"EN":15},[886,890,894,897,901],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":887,"label":888,"description":889,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":891,"label":892,"description":893,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":895,"label":896,"description":18,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{"id":39,"createTime":18,"updateTime":18,"relativeEntities":898,"label":899,"description":900,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":42},{},{"id":45,"createTime":18,"updateTime":18,"relativeEntities":902,"label":903,"description":904,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":48},{},[906,911],{"id":52,"createTime":18,"updateTime":18,"relativeEntities":907,"slug":18,"properties":908,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":910,"statistic":18},[],{"title":909},{"EN":56},[],{"id":59,"createTime":18,"updateTime":18,"relativeEntities":912,"slug":18,"properties":913,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":915,"statistic":18},[],{"title":914},{"EN":63},[65],[917,924],{"id":68,"indexDatabase":918,"url":81,"indexYears":18,"academicFieldIds":923,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":919,"label":920,"description":921,"key":77,"publicationTags":922,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"id":86,"indexDatabase":925,"url":97,"indexYears":98,"academicFieldIds":930,"indexDatabaseRanking":105},{"id":88,"createTime":18,"updateTime":18,"relativeEntities":926,"label":927,"description":928,"key":94,"publicationTags":929,"standard":18},[],{"EN":91,"VI":91},{"EN":91,"VI":93},[96],[100,101,102,103,104],{"impactFactor":19,"impactFactorByYear":932,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":933,"totalCitation":130,"totalCitationByYear":934,"totalCitationPerPublication":139,"totalCitationPerPublicationByYear":935,"hindexLast5Year":148,"hindex":148},{"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":123,"2024":121},{"2015":132,"2016":133,"2017":134,"2018":135,"2019":136,"2020":137,"2022":138},{"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2022":147},{"pages":937,"volume":939},{"VOID":938},"1-19",{"VOID":940},"7","2020-09-11",2020,"2026-04-10T07:19:39.223+00:00",[79,105],{"id":946,"createTime":947,"updateTime":948,"relativeEntities":949,"slug":950,"properties":951,"entityType":171,"verifyStatus":172,"verifyTime":962,"verifyNote":174,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":963,"fullTextUrl":18,"authors":964,"publicationType":272,"publisherRelationship":1023,"citationCount":18,"citationInfo":18,"publishDate":1084,"publishYear":942,"citationAnalyzeStatus":17,"lastCitationAnalyze":1085,"indexDatabases":1086,"openAccess":18,"references":18,"isForceReanalyzing":340},"40a902c3-7652-40a6-80bf-af7406e79d08","2024-01-03T06:41:22.743+00:00","2026-01-31T04:31:41.480+00:00",[],"Lessons-from-April-6-2009-L-Aquila-earthquake-to-enhance-microzoning-studies-in-near-field-urban-areas",{"abstract":952,"title":954,"gsPaper":956,"references":958,"doi":960},{"EN":953},"This study focuses on two weak points of the present procedure to carry out microzoning study in near-field areas: (1) the Ground Motion Prediction Equations (GMPEs), commonly used in the reference seismic hazard (RSH) assessment; (2) the ambient noise measurements to define the natural frequency of the near surface soils and the bedrock depth. The limitations of these approaches will be discussed throughout the paper based on the worldwide and Italian experiences performed after the 2009 L’Aquila earthquake and then confirmed by the most recent 2012 Emilia Romagna earthquake and the 2016–17 Central Italy seismic sequence. The critical issues faced are (A) the high variability of peak ground acceleration (PGA) values within the first 20–30 km far from the source which are not robustly interpolated by the GMPEs, (B) at the level 1 microzoning activity, the soil seismic response under strong motion shaking is characterized by microtremors’ horizontal to vertical spectral ratios (HVSR) according to Nakamura’s method. This latter technique is commonly applied not being fully compliant with the rules fixed by European scientists in 2004, after a 3-year project named Site EffectS assessment using AMbient Excitations (SESAME). Hereinafter, some “best practices” from recent Italian and International experiences of seismic hazard estimation and microzonation studies are reported in order to put forward two proposals: (a) to formulate site-specific GMPEs in near-field areas in terms of PGA and (b) to record microtremor measurements following accurately the SESAME advice in order to get robust and repeatable HVSR values and to limit their use to those geological contests that are actually horizontally layered.",{"EN":955},"Lessons from April 6, 2009 L’Aquila earthquake to enhance microzoning studies in near-field urban areas",{"VOID":957},"[\"9806224682279988825\"]",{"VOID":959},"Abrahamson NA, Silva WJ (2008) Summary of the Abrahamson & Silva NGA ground motion relations. Earthquake Spectra 24(1):67–97\nBard P-Y and the WG (2004) SESAME European research project WP12 – Deliverable D23.12. Guidelines for the implementation of the H\u002FV spectral ratio technique on ambient vibrations measurements, processing and interpretation. http:\u002F\u002Fsesame-fp5.obs.ujf-grenoble.fr\u002Findex.htm\nBergamaschi F, Cultrera G, Luzi L, Azzara RM, Ameri G, Augliera P, Bordoni P, Cara F, Cogliano R, D’alema E, Di Giacomo D, Di Giulio G, Fodarella A, Franceschina G, Galadini F, Gallipoli MR, Gori S, Harabaglia P, Ladina C, Lovati S, Marzorati S, Massa M, Milana G, Mucciarelli M, Pacor F, Parolai S, Picozzi M, Pilz M, Pucillo S, Puglia R, Riccio G, Sobiesiak M (2011) Evaluation of site effects in the Aterno river valley (Central Italy) from aftershocks of the 2009 L’Aquila earthquake. Bull Earthq Eng 9:697–715\nBindi D, Massa M, Luzi L, Ameri G, Pacor F, Puglia R, Augliera P (2014) Pan-European ground-motion prediction equations for the average horizontal component of PGA, PGV and 5%-damped PSA at spectral periods up to 3.0 s using the RESORCE dataset. Bull Earthq Eng 12:391–430. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10518-013-9525-5\nBindi D, Pacor F, Luzi L, Puglia R, Massa M, Ameri G, Paolucci R (2011) Ground-motion prediction equations derived from the Italian strong motion database. Bull Earthq Eng 9(6):1899–1920. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10518-011-9313-z\nBoncio P, Amoroso S, Vessia G, Francescone M, Nardone M, Monaco P, Famiani D, Di Naccio D, Mercuri A, Manuel MR, Galadini F, Milana G (2018) Evaluation of liquefaction potential in an intermountain quaternary lacustrine basin (Fucino basin, Central Italy): implications for seismic microzonation mapping. Bull Earthq Eng 16(1):91–111. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10518-017-0201-z\nBoore DM (2004) Can site response be predicted? J Earthq Eng 8(1):1–41\nBoore DM (2013) What Do Ground-Motion Prediction Equations Tell Us About Motions Near Faults?. 40th Workshop of the International School of Geophysics on properties and processes of crustal fault zones, Ettore Majorana Foundation and Centre for Scientific Culture, Erice, Sicily, Italy, May 18–24 (invited talk)\nBoore DM (2014a) What do data used to develop ground-motion prediction equations tell us about motions near faults? Pure Appl Geophys 171:3023–3043\nBoore DM (2014b) The 2014 William B. Joyner lecture: ground-motion prediction equations: past, present, and future. New Mexico State University, Las Cruces, New Mexico, April 17\nBoschi E, Favali F, Frugoni F, Scalera G, Smriglio G (1995) Massima Intensità Macrosismica risentita in Italia (Map, scale 1:1.500.000)\nBradley BA, Cubrinovski M (2011) Near-source strong ground motions observed in the 22 February 2011 Christchurch earthquake. Bull New Zealand Soc for Earthq Eng 44(4):181–194\nCampbell KW, Bozorgnia Y (2012) A comparison of ground motion prediction equations for arias intensity and cumulative absolute velocity developed using a consistent database and functional form. Earthquake Spectra 28(3):931–941. https:\u002F\u002Fdoi.org\u002F10.1193\u002F1.4000067\nCauzzi C, Faccioli E, Vanini M, Bianchini A (2014) Updated predictive equations for broadband (0.01–10 s) horizontal response spectra and peak ground motions, based on a global dataset of digital acceleration records. Bull Earthq Eng 13:1587–1612. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10518-014-9685-y\nCornell CA (1968) Engineering seismic risk analysis. 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S. D’Amico, 2016 chapter 9 title: “working strategies for addressing microzoning studies in urban areas: lessons from 2009 L'Aquila earthquake”, 233–290, Springer international publishing Switzerland\nVessia G, Russo S, Lo Presti D (2011) A new proposal for the evaluation of the amplification coefficient due to valley effects in the simplified local seismic response analyses. Ital Geotechnical J 4:51–77\nVessia G, Russo S (2013) Relevant features of the valley seismic response: the case study of Tuscan northern Apennine sector. Bull Earthq Eng 11(5):1633–1660\nVessia G, Venisti N (2011) Liquefaction damage potential for seismic hazard evaluation in urbanized areas. Soil Dyn Earthq Eng 31:1094–1105\nWoo G (1996) Kernel estimation methods for seismic hazard area source modeling. Bull Seism Soc Am 86:1–10\nYagoub MM (2015) Spatio-temporal and hazard mapping of earthquake in UAE (1984–2012): remote sensing and GIS application. Geoenviron Disasters 2:13. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs40677-015-0020-y",{"VOID":961},"10.1186\u002Fs40677-020-00147-x","2024-05-12T23:22:52.835+00:00","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-020-00147-x",[965,980,993,1010],{"id":966,"sortIndex":19,"researcher":18,"roles":967,"affiliations":968,"properties":977,"displayName":979,"givenName":18,"familyName":18},"03a33082-dac4-41ef-b88e-0460fccc96cd",[180],[969],{"id":970,"sortIndex":19,"affiliation":971,"properties":18},"ab05fb2a-8acc-4048-a8d4-ba7b5ce09981",{"id":970,"createTime":18,"updateTime":18,"relativeEntities":972,"slug":18,"properties":973,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":976,"statistic":18},[],{"title":974},{"VI":975},"Department of Engineering and Geology, University “G. d’Annunzio” of Chieti-Pescara, Chieti, 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this research, the concentrations of nitrates were investigated in well water sampled from the irrigated perimeter of Beni Moussa (Tadla plain, Morocco), and human health risks via ingestion and dermal pathways for individuals in different age brackets were assessed using the chronic daily intake, the dermal absorbed dose and hazard index (HI). The results showed that the groundwater NO3 contents were between 4.20 to 80.46 mg L− 1, with an average of 32.11 mg L− 1, indicating anthropogenic inputs caused by the infiltration of nitrates not consumed by plants or surface industrial and domestic wastewater into the shallow aquifer. Compared to the Moroccan standard, 17.78%, 40.00%, 37.78% and 4.44% of sampled wells showed poor, fair, good or excellent quality, respectively. For non-carcinogenic risk, the oral ingestion of nitrate appeared to be the main exposure pathway for local human receptors causing the high non-carcinogenic risk, and the dermal exposure met within the accepted precautionary criterion. Infants in the study area are more likely to experience adverse effects to higher nitrate level in groundwater (3.04E-01 \u003C HI \u003C 1.80E+ 00), followed by female (2.39E-01 \u003C HI \u003C 1.41E+ 00), then male (2.22E-01 \u003C HI \u003C 1.31E+ 00) and finally children (2.08E-01 \u003C HI \u003C 1.23E+ 00). The resulting spatial variation in HI values was greatly influenced by human activities and population density. The results of this study could help to shape effective environmental management measures for enhancing the groundwater quality and ensuring safe drinking water.",{"EN":1097},"Groundwater NO3 concentration and its potential health effects in Beni Moussa perimeter (Tadla plain, Morocco)",{"VOID":1099},"Adimalla N, Li P (2019) Occurrence, health risks, and geochemical mechanisms of fluoride and nitrate in groundwater of the rock-dominant semi-arid region, Telangana state, India. Hum Ecol Risk Assess: An Int J 25(1-2):81–103\nAghzar N, Berdai H, Bellouti A, Soudi B (2002) Pollution nitrique des eaux souterraines au Tadla (Maroc). Revue des sciences de l'eau\u002FJournal of Water Science 15:459–492\nAhada CP, Suthar S (2018) Groundwater nitrate contamination and associated human health risk assessment in southern districts of Punjab, India. 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Accessed 15 Apr 2020\nOumenskou H, El Baghdadi M, Barakat A, Aquit M, Ennaji W, Karroum LA, Aadraoui M (2018) Assessment of the heavy metal contamination using GIS-based approach and pollution indices in agricultural soils from Beni Amir irrigated perimeter, Tadla plain, Morocco. Arabian J Geosci 11:692\nOumenskou H, El Baghdadi M, Barakat A, Aquit M, Ennaji W, Karroum LA, Aadraoui M (2019) Multivariate statistical analysis for spatial evaluation of physicochemical properties of agricultural soils from Beni-Amir irrigated perimeter, Tadla plain, Morocco Geology, Ecol Landscapes 3:83–94\nRivett MO, Buss SR, Morgan P, Smith JW, Bemment CD (2008) Nitrate attenuation in groundwater: a review of biogeochemical controlling processes. Water Res 42:4215–4232\nRodier J, Legube B, Merlet N, Brunet R (2009) L'analyse de l'eau-9e éd.: Eaux naturelles, eaux résiduaires, eau de mer. Dunod\nSekhon G (1995) Fertilizer-N use efficiency and nitrate pollution of groundwater in developing countries. J Contam Hydrol 20:167–184\nSerio F, Miglietta PP, Lamastra L, Ficocelli S, Intini F, De Leo F, De Donno A (2018) Groundwater nitrate contamination and agricultural land use: A grey water footprint perspective in Southern Apulia Region (Italy). Sci Total Environ 645:1425–1431\nSoldatova E, Sun Z, Maier S, Drebot V, Gao B (2018) Shallow groundwater quality and associated non-cancer health risk in agricultural areas (Poyang Lake basin, China). Environ Geochem Health 40(5):2223–2242.\nUSEPA (US Environmental Protection Agency) (1989) Risk Assessment Guidance for Superfund, vol. I: Human Health Evaluation Manual (Part A). US Environmental Protection Agency, Office of Emergency and Remedial Response, EPA 540\u002F1-89\u002F 002, Washington, DC\nUSEPA (2004) Air quality criteria for particulate matter. US Environmental Protection Agency, Research Triangle Park\nUSEPA (2014) National summary of impaired waters and TMDL information. Retrieved,\nUSEPA (2018) Integrated Risk Information System (IRIS). http:\u002F\u002Fwww.epa.gov\u002Firis\u002F. Accessed 16 May 2018\nVerset Y (1988) Carte g′eologique du Maroc au 1\u002F100,000 Feuille Qasbat-Tadla: M′emoire explicatif, vol 340 Editions du Service Geologique du Maroc\nVitousek PM et al (1997) Human alteration of the global nitrogen cycle: sources and consequences. Ecol Appl 7:737–750\nWang H, Gu H, Lan S, Wang M, Chi B (2018) Human health risk assessment and sources analysis of nitrate in shallow groundwater of the Liujiang basin, China. Hum Ecol Risk Assess: An Int J 24:1515–1531\nWard MH et al (2018) Drinking water nitrate and human health: an updated review. Int J Environ Res Public Health 15:1557\nWebb J, Menzi H, Pain B, Misselbrook T, Dämmgen U, Hendriks H, Döhler H (2005) Managing ammonia emissions from livestock production in Europe. Environ Pollut 135:399–406\nWHO (World Health Organisation) (2004) Guidelines for Drinking-Water Quality, 3rd. Edition, Vol. 1. World Health Organisation, Geneva\nXu B, Zhang Y, Wang J (2018) Hydrogeochemistry and human health risks of groundwater fluoride in Jinhuiqu irrigation district of Wei river basin, China. Hum Ecol Risk Assess: An Int J 25:230–249\nYang, M., Fei, Y., Ju, Y., Ma, Z., & Li, H. (2012) Health risk assessment of groundwater pollution-A case study of typical city in North China plain. Journal of Earth Science, 23(3), 335–348",{"VOID":1101},"10.1186\u002Fs40677-020-00149-9","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-020-00149-9",[1104],{"id":1105,"sortIndex":19,"researcher":18,"roles":1106,"affiliations":1107,"properties":1116,"displayName":1118,"givenName":18,"familyName":18},"916c66c2-a1c9-48ed-9cd5-6a42f007b6b2",[180],[1108],{"id":1109,"sortIndex":19,"affiliation":1110,"properties":18},"d4ec3bba-94aa-4d28-bd08-7b6c9cf7a0da",{"id":1109,"createTime":18,"updateTime":18,"relativeEntities":1111,"slug":18,"properties":1112,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1115,"statistic":18},[],{"title":1113},{"VI":1114},"Georesources and environment Team, Faculté des Sciences et Techniques, Université Sultan Moulay Slimane, Beni-Mellal, Morocco",[],{"title":1117},{"VI":1118},"Ahmed Barakat",{"url":1102,"publisher":1120,"properties":1176},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1121,"slug":10,"properties":1122,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1125,"manageAffiliations":1145,"indexDatabases":1156,"url":106,"thumbnailPath":18,"statistic":1171,"gsStatistic":18,"type":149,"analyzePriority":18},[],{"issn":1123,"title":1124},{"VOID":13},{"EN":15},[1126,1130,1134,1137,1141],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1127,"label":1128,"description":1129,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1131,"label":1132,"description":1133,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1135,"label":1136,"description":18,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{"id":39,"createTime":18,"updateTime":18,"relativeEntities":1138,"label":1139,"description":1140,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":42},{},{"id":45,"createTime":18,"updateTime":18,"relativeEntities":1142,"label":1143,"description":1144,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":48},{},[1146,1151],{"id":52,"createTime":18,"updateTime":18,"relativeEntities":1147,"slug":18,"properties":1148,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1150,"statistic":18},[],{"title":1149},{"EN":56},[],{"id":59,"createTime":18,"updateTime":18,"relativeEntities":1152,"slug":18,"properties":1153,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1155,"statistic":18},[],{"title":1154},{"EN":63},[65],[1157,1164],{"id":68,"indexDatabase":1158,"url":81,"indexYears":18,"academicFieldIds":1163,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":1159,"label":1160,"description":1161,"key":77,"publicationTags":1162,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"id":86,"indexDatabase":1165,"url":97,"indexYears":98,"academicFieldIds":1170,"indexDatabaseRanking":105},{"id":88,"createTime":18,"updateTime":18,"relativeEntities":1166,"label":1167,"description":1168,"key":94,"publicationTags":1169,"standard":18},[],{"EN":91,"VI":91},{"EN":91,"VI":93},[96],[100,101,102,103,104],{"impactFactor":19,"impactFactorByYear":1172,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":1173,"totalCitation":130,"totalCitationByYear":1174,"totalCitationPerPublication":139,"totalCitationPerPublicationByYear":1175,"hindexLast5Year":148,"hindex":148},{"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":123,"2024":121},{"2015":132,"2016":133,"2017":134,"2018":135,"2019":136,"2020":137,"2022":138},{"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2022":147},{"pages":1177,"volume":1178},{"VOID":651},{"VOID":940},"2020-04-28",[79,105],{"id":1182,"createTime":1183,"updateTime":1184,"relativeEntities":1185,"slug":1186,"properties":1187,"entityType":171,"verifyStatus":172,"verifyTime":1184,"verifyNote":174,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1196,"fullTextUrl":18,"authors":1197,"publicationType":272,"publisherRelationship":1228,"citationCount":18,"citationInfo":18,"publishDate":1289,"publishYear":1290,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":1291,"openAccess":18,"references":18,"isForceReanalyzing":340},"bd2b48ed-531a-4e37-b4f3-6983012a1b88","2024-01-22T05:07:08.615+00:00","2025-02-26T08:33:21.622+00:00",[],"A-Potential-Tsunami-impact-assessment-of-submarine-landslide-at-Baiyun-Depression-in-Northern-South-China-Sea",{"abstract":1188,"title":1190,"references":1192,"doi":1194},{"EN":1189},"With mature hydrocarbon industry, Northern South China Sea (NSCS) is a hot spot for future economic development. However, the local government and researchers lack of estimations about damages brought by a submarine landslide-generated tsunami. According to oceanographic surveys, eleven landslides in different scale have been discovered in Baiyun Depression of NSCS. Hence, the need to study potential tsunamis generated by submarine landslides in NSCS is urgent and necessary. This research, focused on potential threat linked to local tsunami sources, is in its early stage in China but it is of capital importance for the local people, local government and offshore economics. Taking landslide S4 for example, the formation, spreading and run-up are predicted. As calculated, the greatest height of tsunami generated by Landslide S4 is 17.5 m, occurring near Dongsha Islands, and the greatest run-up formed on the coastal line is 5.3 m, occurring near Shanwei City; the general height of waves attacking the coastal line is no more than 1.5m, but abnormally high waves might occur in 32 regions. Prediction of tsunami generated by Landslide S4 suggests that local landslides in NSCS may trigger tsunami hazards. Therefore, more efforts shall be made to investigate potential damages caused by a submarine landslide, particularly the submarine landslides at Baiyun Depression in NSCS.",{"EN":1191},"A Potential Tsunami impact assessment of submarine landslide at Baiyun Depression in Northern South China Sea",{"VOID":1193},"Applied Fluids Engineering Inc University of Delaware, U.S.A: Geowave 1.1 Tutorial. 2008.\nChen Y, Chen Q, Zhang W: Tsunami disaster in China. Journal of Natural Disasters 2007,16(2):1–6.\nDidenkulova I, Pelinovsky E: Runup of tsunami waves in U-shaped bays. Pure Appl Geophys 2010, 168: 1239–1249. 10.1007\u002Fs00024-010-0232-8\nEnet F, Grilli ST and Watts P (2003) Laboratory Experiments for Tsunamis Generated by Underwater Landslides: Comparison with Numerical Modeling. 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Summary report for research institution-based strategic project 2002–2005, NGI report No.20021023–2. 2005.\nOkal EA: T waves from the 1998 Papua New Guinea earthquake and its aftershocks: timing the tsunamigenic slump. Pure Appl Geophys 2003, 160: 1843–1863. 10.1007\u002Fs00024-003-2409-x\nPrior DB: Subaqueous landslides. Proceedings of the IV International Symposium on Landslides, Toronto 1984, 1: 179–196.\nRahiman IHT, Pettinga JR, Watts P: The source mechanism and numerical modeling of the 1953 Suva tsunami, Fiji. Mar Geol 2007, 237: 55–70. 10.1016\u002Fj.margeo.2006.10.036\nSascha B, Andrey YB, Christoph G, Stefan L: Hazard assessment of underwater landslide-generated tsunamis: a case study in the Padang region, Indonesia. Nat Hazards 2010, 53: 205–218. 10.1007\u002Fs11069-009-9424-x\nShi W, Chen H, Chen C: Modeling of pressure evolution and hydrocarbon migration in the Baiyun Depression, Pearl River mouth basin, China. Earth Science-Journal of China University of Geosciences 2006,31(2):229–336.\nState Oceanic Administration of China:Contingency Plan against Disasters of Storm Surges, Sea Waves, Tsunamis and Sea Ice, NO.685. 2009.\nSue LP, Nokes RI, Davidson MJ: Tsunami generation by submarine landslides: comparison of physical and numerical models. Environ Fluid Mech 2011, 11: 133–165. 10.1007\u002Fs10652-010-9205-9\nSun Y: The Mechanism and Prediction of Deepwater Geohazard in the Northern of South China Sea. Institute of Oceanology, Chinese Academy of Sciences, Qingdao; 2011.\nSun Y, Wu S, Wang Z, Li Q, Wang X, Dong D, Liu F: The geometry and deformation characteristics of Baiyun submarine landslide. Mar Geol Quat Geol 2008, 6: 69–77.\nSun Z, Pang X, Zhong Z: Dynamics of tertiary tectonic evolution of the Baiyun Sag in the Pearl River mouth basin. Chinese Journal of Earth Science Frontiers 2005,12(4):489–498.\nTinti S, Bortolucci E: Energy of water waves induced by submarine landslides. Pure Appl Geophys 2000, 157: 281–318. 10.1007\u002Fs000240050001\nTinti S, Bortolucci E, Armigliato A: Numerical simulation of the landslide-induced tsunami of 1988 on Vulcano Island, Italy. Bull Volcanol 1999, 61: 121–137. 10.1007\u002Fs004450050267\nUriten B, Twichell D, Lynett P, Geist E, Chaytor J, Lee H, Buczkowski B, Flores C: Regional Assessment of Tsunami Potential in the Gulf of Mexico – Report to the National Tsunami Hazard Mitigation Program. Geological Survey, U.S; 2009.\nVanneste M, Forsberg CF, Glimsdal S, Harbitz CB, Issler D, Kvalstad TJ, Løvholt F, Nadim F: Submarine Landslides and their Consequences: What do we know, what can we do?. Proceedings of the second World Landslide Forum, Rome; 2011.\nWard SN: Landslide tsunami. J Geophys Res 2001,106(6):11201–11215. 10.1029\u002F2000JB900450\nWard SN, Day S: Ritter Island Volcano-lateral collapse and the tsunami of 1888. Geophys J Int 2003, 154: 891–9-2.\nWijetunge JJ: Field measurements and numerical simulations of the 2004 tsunami impact on the east coast of Sri Lanka. Pure Appl Geophys 2009, 16: 593–622. 10.1007\u002Fs00024-009-0458-5\nYang W, Zhang Y, Li B: Types and characteristics of deepwater geologic hazard in Qiongdongnan of the South China Sea. Offshore Oil 2011,31(1):1–7.\nZhu W, Zhang G, Yang S: Gas Geology in the Northern Continental Margin Basin of South China Sea. Chinese Petroleum Industry Press, Beijing; 2007.",{"VOID":1195},"10.1186\u002Fs40677-014-0007-0","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-014-0007-0",[1198,1213],{"id":1199,"sortIndex":19,"researcher":18,"roles":1200,"affiliations":1201,"properties":1210,"displayName":1212,"givenName":18,"familyName":18},"404bdb11-01dc-415a-aa1f-06a61552fe56",[180],[1202],{"id":1203,"sortIndex":19,"affiliation":1204,"properties":18},"81e3f0de-1782-47a5-b289-2230b9e221dc",{"id":1203,"createTime":18,"updateTime":18,"relativeEntities":1205,"slug":18,"properties":1206,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1209,"statistic":18},[],{"title":1207},{"VI":1208},"The First Institute of Oceanography, SOA, Qingdao City, Laoshan District, China",[],{"title":1211},{"VI":1212},"Sun Yongfu",{"id":1214,"sortIndex":192,"researcher":18,"roles":1215,"affiliations":1216,"properties":1225,"displayName":1227,"givenName":18,"familyName":18},"0244d2f5-7d7f-465e-a0ca-3377b94f850f",[180],[1217],{"id":1218,"sortIndex":19,"affiliation":1219,"properties":18},"64691d7a-8dfe-462f-b657-fcea14aeef3e",{"id":1218,"createTime":18,"updateTime":18,"relativeEntities":1220,"slug":18,"properties":1221,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1224,"statistic":18},[],{"title":1222},{"VI":1223},"Wuhan Center of China Geological Survey, Wuhan City, China",[],{"title":1226},{"VI":1227},"Huang 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principle, the mechanical properties of soil particles are irreversibly changed after particles are subjected to heating. Accordingly, this study performed ring-shear tests on calcareous sand samples subjected to high temperatures to qualitatively investigate the influence exerted by the degradation of the calcareous sand, caused by the thermal effect, on the large displacement shear characteristics of the samples. The effects of the shear velocity and normal stress on the quasi-static shear behavior of the calcareous sand samples were analyzed. The influence of the thermal effect on the quasi-static shear flow behavior of the samples is primarily reflected in the change in the particle mineral composition, particle hardness, and sample density. These variations result in changes in the shear strength, residual shear stress, macroscopic friction coefficient, and other shear characteristics of the calcareous sand samples. Both the shear velocity and the high temperature affect the fluctuation amplitude of the residual shear stress. The results have great theoretical and practical significance in terms of explaining the instability mechanism of a slope. Moreover, a feasible and effective technique is proposed to investigate the large-displacement shear behavior of soil subjected to the thermal effect exerted by a long-runout landslide.",{"EN":1302},"Influence of the thermal effect on quasi-static shear characteristics of calcareous soil: an experimental study",{"VOID":1304},"Agung MW, Sassa K, Fukuoka H et al (2004) Evolution of shear-zone structure in undrained ring-shear tests. Landslide 1(1):101–112\nForterre Y (2008) Flows of dense granular media. Annu Rev Fluid Mech 40:1–24\nHong Y, Sun T, Luan MT et al (2009) Development and application of geotechnical ring shear apparatus: an overview. Rock Soil Mech 30(3):628–634 (In Chinese)\nHu W, Huang RQ, McSaveney M et al (2018) Mineral changes quantify frictional heating during a large low-friction landslide. Geology 46(3):223–226\nHu W, Huang RQ, McSaveney M et al (2019) Superheated steam, hot CO2 and dynamic recrystallization from frictional heat jointly lubricated a giant landslide: field and experimental evidence. Earth Planet Sci Lett 510:85–93\nHuang Y, Dai ZL (2014) Large displacement and failure simulations for geo-disasters using smoothed particle hydrodynamics method. Eng Geol 168:86–97\nHungr O (1995) A model for the runout analysis of rapid flow slides, debris flows, and avalanches. Can Geotech J 32(4):610–623\nJohnson KL (1970) The correlation of indentation experiments. J Mech Phys Solids 18(2):115–126\nKamai T (1998) Monitoring the process of ground failure in repeated landslides and associated stability assessments. Eng Geol 50(1):101–112\nLuo Y, He SM, Song PF (2016) Research status and prospects of thermo-poro-mechanical analysis of long runout landslides motions. J Catastrophol 31(4):162–165\nMa SL, Shimamoto T, Yao L et al (2014) A rotary-shear low to high-velocity friction apparatus in Beijing to study rock friction at plate to seismic slip rates. Earthq Sci 27(5):469–497\nNoda H, Kanagawa K, Hirose T et al (2011) Frictional experiments of dolerite at intermediate slip rates with controlled temperature: Rate weakening or temperature weakening? J Geophys Res 116:B07306\nPinyol NM, Alvarado M, Alonso EE et al (2018) Thermal effects in landslide mobility. Geotechnique 68(6):528–545\nShimamoto T, Tsutsumi A (1994) A new rotary-shear high-speed frictional testing machine: its basic degign and scope of research. J Tecton Res Group Jpn 39:65–78\nSkempton AW (1985) Residual strength of clays in landslides, folded strata and the laboratory. Geotechnique 35(1):3–18\nSmith SAF, Di Toro G, Kim S et al (2013) Coseismic recrystallization during shallow earthquake slip. Geology 41:63–66\nSun QC, Wang GQ (2008) Review on granular flow dynamics and its discrete element method. Adv Mech 38(1):87–100\nTika TE, Hutchinson JN (1999) Ring shear tests on soil from the Vaiont landslide. Geotechnique 49(1):59–74\nUjiie K, Tanaka H, Saito T et al (2013) Low coseismic shear stress on the Tohoku-oki megathrust determined from laboratory experiments. Science 242:1211–1214\nUzuoka R, Yashima A, Kawakami T et al (1998) Fluid dynamics based prediction of liquefaction induced lateral spreading. Comput Geotech 22(3–4):243–282\nWang YY (2006) An approach to rheological characters of viscous debris flow and the stress constitutie. J Mt Sci 24(5):555–561 (In Chinese)\nWang SR, Huang Y (2022a) Experimental study on the effect of particle size on the shear characteristics of large-displacement soil exposed to heat treatment: shear fluctuation and heat degradation. Eng Geol 300:106581\nWang SR, Huang Y (2022b) Experimental study on the shear characteristics of quartz sand exposed to high temperatures. Acta Geotech 17:5031–5041\nXu Q, Li WL, Dong XJ (2017) The Xinmocun landslide on June 24, 2017 in Maoxian, Sichuan: characteristics and failure mechanism. Chin J Rock Mech Eng 36(11):2612–2628",{"VOID":1306},"10.1186\u002Fs40677-022-00228-z","https:\u002F\u002Fgeoenvironmental-disasters.springeropen.com\u002Farticles\u002F10.1186\u002Fs40677-022-00228-z",[1309,1342],{"id":1310,"sortIndex":19,"researcher":18,"roles":1311,"affiliations":1312,"properties":1339,"displayName":1341,"givenName":18,"familyName":18},"0510c86a-7670-4e86-8593-946253ac4b69",[180],[1313,1321,1330],{"id":1314,"sortIndex":19,"affiliation":1315,"properties":18},"28a9a5ac-54df-4511-af2f-361ca1e709df",{"id":1314,"createTime":18,"updateTime":18,"relativeEntities":1316,"slug":18,"properties":1317,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1320,"statistic":18},[],{"title":1318},{"VI":1319},"Department of Civil Engineering, University of Shanghai for Science and Technology, Shanghai, China",[],{"id":1322,"sortIndex":192,"affiliation":1323,"properties":1329},"47344de0-5446-4cb5-a89c-c0394377ae80",{"id":1322,"createTime":18,"updateTime":18,"relativeEntities":1324,"slug":18,"properties":1325,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1328,"statistic":18},[],{"title":1326},{"VI":1327},"Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, China",[],{},{"id":1331,"sortIndex":218,"affiliation":1332,"properties":1338},"007367bf-cb19-4c10-9b4c-9a03a6edc691",{"id":1331,"createTime":18,"updateTime":18,"relativeEntities":1333,"slug":18,"properties":1334,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1337,"statistic":18},[],{"title":1335},{"VI":1336},"Key Laboratory of Geotechnical and Underground Engineering of the Ministry of Education, Tongji University, Shanghai, China",[],{},{"title":1340},{"VI":1341},"Suran Wang",{"id":1343,"sortIndex":192,"researcher":18,"roles":1344,"affiliations":1345,"properties":1359,"displayName":1361,"givenName":18,"familyName":18},"83ee8cea-7987-42fa-8942-da52485cc617",[180],[1346,1352],{"id":1322,"sortIndex":19,"affiliation":1347,"properties":18},{"id":1322,"createTime":18,"updateTime":18,"relativeEntities":1348,"slug":18,"properties":1349,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1351,"statistic":18},[],{"title":1350},{"VI":1327},[],{"id":1331,"sortIndex":192,"affiliation":1353,"properties":1358},{"id":1331,"createTime":18,"updateTime":18,"relativeEntities":1354,"slug":18,"properties":1355,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1357,"statistic":18},[],{"title":1356},{"VI":1336},[],{},{"title":1360},{"VI":1361},"Yu Huang",{"url":1307,"publisher":1363,"properties":1419},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1364,"slug":10,"properties":1365,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1368,"manageAffiliations":1388,"indexDatabases":1399,"url":106,"thumbnailPath":18,"statistic":1414,"gsStatistic":18,"type":149,"analyzePriority":18},[],{"issn":1366,"title":1367},{"VOID":13},{"EN":15},[1369,1373,1377,1380,1384],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1370,"label":1371,"description":1372,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1374,"label":1375,"description":1376,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1378,"label":1379,"description":18,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{"id":39,"createTime":18,"updateTime":18,"relativeEntities":1381,"label":1382,"description":1383,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":42},{},{"id":45,"createTime":18,"updateTime":18,"relativeEntities":1385,"label":1386,"description":1387,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":48},{},[1389,1394],{"id":52,"createTime":18,"updateTime":18,"relativeEntities":1390,"slug":18,"properties":1391,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1393,"statistic":18},[],{"title":1392},{"EN":56},[],{"id":59,"createTime":18,"updateTime":18,"relativeEntities":1395,"slug":18,"properties":1396,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1398,"statistic":18},[],{"title":1397},{"EN":63},[65],[1400,1407],{"id":68,"indexDatabase":1401,"url":81,"indexYears":18,"academicFieldIds":1406,"indexDatabaseRanking":18},{"id":70,"createTime":18,"updateTime":18,"relativeEntities":1402,"label":1403,"description":1404,"key":77,"publicationTags":1405,"standard":18},[],{"EN":73,"VI":73},{"EN":75,"VI":76},[79,80],[83,84],{"id":86,"indexDatabase":1408,"url":97,"indexYears":98,"academicFieldIds":1413,"indexDatabaseRanking":105},{"id":88,"createTime":18,"updateTime":18,"relativeEntities":1409,"label":1410,"description":1411,"key":94,"publicationTags":1412,"standard":18},[],{"EN":91,"VI":91},{"EN":91,"VI":93},[96],[100,101,102,103,104],{"impactFactor":19,"impactFactorByYear":1415,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":1416,"totalCitation":130,"totalCitationByYear":1417,"totalCitationPerPublication":139,"totalCitationPerPublicationByYear":1418,"hindexLast5Year":148,"hindex":148},{"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":123,"2024":121},{"2015":132,"2016":133,"2017":134,"2018":135,"2019":136,"2020":137,"2022":138},{"2015":141,"2016":142,"2017":143,"2018":144,"2019":145,"2020":146,"2022":147},{"pages":1420,"volume":1422},{"VOID":1421},"1-8",{"VOID":1423},"9","2022-11-29",2022,[79,105],{"id":1428,"createTime":1429,"updateTime":1430,"relativeEntities":1431,"slug":1432,"properties":1433,"entityType":171,"verifyStatus":172,"verifyTime":1430,"verifyNote":174,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1442,"fullTextUrl":1443,"authors":1444,"publicationType":272,"publisherRelationship":1521,"citationCount":18,"citationInfo":18,"publishDate":1583,"publishYear":1584,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":1585,"openAccess":18,"references":18,"isForceReanalyzing":340},"1f5813cf-d6ea-47a4-b466-384cce1a33b3","2024-01-28T07:57:13.712+00:00","2025-02-25T12:32:06.249+00:00",[],"Development-of-a-methodology-for-predicting-landslide-hazards-at-a-regional-scale",{"abstract":1434,"title":1436,"references":1438,"doi":1440},{"EN":1435},"Landslide risk analysis is a common geotechnical evaluation and it aims to protect life and infrastructure. In the case of sensitive clay zones, landslides can affect large areas and are difficult to predict. Here we propose a methodology to determine the landslide hazard across a large territory, and we apply our approach to the Saint-Jean-Vianney area, Quebec, Canada. The initial step consists of creating a 3D model of the surficial deposits of the target area. After creating a chart of the material electrical resistivity adapted for eastern Canada, we applied electric induction to interpret the regional soil. We transposed parameter values obtained from the laboratory to a larger scale, that is to a regional slope using the results of a back analysis undertaken earlier, on a smaller slide within the same area. The regional 3D model of deposits is then used to develop a zonation map of slopes that are at risk and their respective constraint areas with the study region. This approach allowed us to target specific areas where a more precise stability analysis would be required. Our methodology offers an effective tool for stability analysis in territories characterized by the presence of sensitive clays.",{"EN":1437},"Development of a methodology for predicting landslide hazards at a regional scale",{"VOID":1439},"Aquaveo (2019) Arc hydro groundwater 3.5. \n                  https:\u002F\u002Fwww.aquaveo.com\u002Fsoftware\u002Fahgw-archydro-groundwater-introduction\n                  \n                \nASTM D2850-15 (2015) Standard test method for unconsolidated-undrained triaxial compression test on cohesive soils. ASTM International, West Conshohocken. \n                  https:\u002F\u002Fstandards.globalspec.com\u002Fstd\u002F3859771\u002Fastm-d2850-15\n                  \n                \nBouchard R (1991). Villages Fantômes, Localités Disparues Ou Méconnues Du Haut-Saguenay. Société historique du Saguenay\nBureau de normalisation du Québec (BNQ) (2013) Sols—analyse granulométrique des sols inorganiques: BNQ 2501-025\u002F2013. \n                  https:\u002F\u002Fwww.bnq.qc.ca\u002Ffr\u002Fnormalisation\u002Fgenie-civil-et-infrastructures-urbaines\u002Fsols\u002Fsols-analyse-granulometrique-des-sols-inorganiques.html\n                  \n                \nBureau de normalisation du Québec (BNQ) (2019) Détermination de La Limite de Liquidité à l’aide de l’appareil de Casagrande et de La Limite de Plasticité: BNQ-2501-090\u002F2019.” \n                  https:\u002F\u002Fwww.bnq.qc.ca\u002Ffr\u002Fnormalisation\u002Fgenie-civil-et-infrastructures-urbaines\u002Fsols\u002Fsols-determination-de-la-limite-de-liquidite-a-l-aide-de-l-appareil-de-casagrande-et-de-la-limite-de-plasticite.html\n                  \n                \nCERM-PACES (2013) Résultats Du Programme d’acquisition de Connaissances Sur Les Eaux Souterraines Du Saguenay-Lac-Saint-Jea. Centre d’études Sur Les Ressources Minérales, Université Du Québec à Chicoutimi\ncitation_journal_title=Comput Geosci; citation_title=Building a geodatabase for mapping hydrogeological features and 3D modeling of groundwater systems: application to the Saguenay-Lac-St.-Jean region, Canada; citation_author=R Chesnaux, M Lambert, J Walter, U Fillastre, M Hay, A Rouleau, R Daigneault, A Moisan, D Germaneau; citation_volume=37; citation_issue=11; citation_publication_date=2011; citation_pages=1870-1882; citation_doi=10.1016\u002Fj.cageo.2011.04.013; citation_id=CR7\ncitation_journal_title=Geophysics; citation_title=Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data; citation_author=SC Constable, RL Parker, CG Constable; citation_volume=52; citation_publication_date=1987; citation_pages=289-300; citation_doi=10.1190\u002F1.1442303; citation_id=CR47\nDemers D, Robitaille D, Locat P, Potvin J (2014) Inventory of large landslides in sensitive clay in the province of Québec, Canada: preliminary analysis. In: Landslides in sensitive clays: from geosciences to risk management, pp 77–89\nde Saguenay V (2007) Carte de zones de contraintes relatives aux glissements de terrain. 1: 5000. 22D06-050-0805.\ncitation_journal_title=Geogr Phys et Quat; citation_title=Late Wisconsinan and Holocene history of the Laurentide ice sheet; citation_author=AS Dyke, VK Prest; citation_volume=41; citation_issue=2; citation_publication_date=1987; citation_pages=237-263; citation_doi=10.7202\u002F032681ar; citation_id=CR10\nESRI (2015) ArcGIS Desktop. \n                  https:\u002F\u002Fwww.esri.com\u002Fen-us\u002Farcgis\u002Fproducts\u002Farcgis-pro\u002Foverview#visualization\n                  \n                .\nFargier Y, Fauchard C, Meriaux P, Royet P, Palma-Lopes S, Francois D, Cote P, Bretar F (2014) Methodology applied to the diagnosis and monitoring of dikes and dams. Novel Approaches and Their Applications in Risk Assessment. \n                  https:\u002F\u002Fdoi.org\u002F10.5772\u002F16318\n                  \n                .\nGouvernement du Québec (2021) Donnée Québec. Disponible à \n                  https:\u002F\u002Fwww.donneesquebec.ca\u002F\n                  \n                . [cité le 2021-04-02\ncitation_title=Controls on the dimensions of landslides in sensitive clays; citation_inbook_title=Landslides in sensitive clays: from geosciences to risk management; citation_publication_date=2014; citation_pages=105-17; citation_id=CR14; citation_author=M Geertsema; citation_author=J-S Heureux; citation_publisher=Springer Netherlands\ncitation_title=Mapping quick clay hazard zones: comparison of methods for the estimation of the retrogression distance; citation_inbook_title=Advances in natural and technological hazards research; citation_publication_date=2017; citation_pages=311-21; citation_id=CR15; citation_author=ED Haugen; citation_author=M Tveit; citation_author=H Heyerdahl; citation_publisher=Springer Netherlands\ncitation_title=An introduction to geotechnical engineering; citation_publication_date=1981; citation_id=CR16; citation_author=RD Holtz; citation_author=WD Kovacs; citation_publisher=Prentice-Hall Inc\ncitation_journal_title=Landslides; citation_title=The Varnes classification of landslide types, an update; citation_author=O Hungr, S Leroueil, L Picarelli; citation_volume=11; citation_issue=2; citation_publication_date=2014; citation_pages=167-194; citation_doi=10.1007\u002Fs10346-013-0436-y; citation_id=CR17\ncitation_journal_title=Publikasjon Norges Geotekniske Institutt; citation_title=Can we predict landslide hazards in soft sensitive clay? Summary of Norwegian practice and experiences; citation_author=K Karlsrud, G Aas, O Gregersen; citation_volume=158; citation_publication_date=1985; citation_pages=405-429; citation_doi=10.1016\u002F0148-9062(86)91270-2; citation_id=CR18\nL’Heureux J-S, Locat A, Leroueil S, Demers D, Locat J (2014) Landslides in sensitive clays—from geosciences to risk management. In: Landslides in Sensitive Clays—From Geosciences to Risk Management, pp 1–12 doi:\n                  https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-94-007-7079-9_1\n                  \n                .\ncitation_title=Rapport de Synthèse Des Études de La Coulée d’argile de Saint-Jean-Vianney; citation_publication_date=1974; citation_id=CR20; citation_author=P LaRochelle; citation_publisher=Ministère des richesses naturelles du Québec\ncitation_journal_title=Can J Earth Sci; citation_title=An Ancient Landslide along the Saguenay River, Quebec; citation_author=P Lasalle, J-Y Chagnon; citation_volume=5; citation_issue=3; citation_publication_date=1968; citation_pages=548-549; citation_doi=10.1139\u002Fe68-049; citation_id=CR21\ncitation_journal_title=Can Geotech J; citation_title=Strength and slope stability in Canadian soft clay deposits; citation_author=G Lefebvre; citation_volume=18; citation_issue=3; citation_publication_date=1981; citation_pages=420-442; citation_doi=10.1139\u002Ft81-047; citation_id=CR22\ncitation_journal_title=Can Geotech J; citation_title=Propriétés caractéristiques des argiles de l'est du Canada; citation_author=S Leroueil, F Tavenas, JPL Bihan; citation_volume=20; citation_issue=4; citation_publication_date=1983; citation_pages=681-705; citation_doi=10.1139\u002Ft83-076; citation_id=CR23\nLeroueil S, Locat J, Vaunat J, Picarelli L, Lee H, Faure R (1996) Geotechnical characterization of slope movements. In: Landslides, pp 53–74\ncitation_journal_title=Can Geotech J; citation_title=Viscosity, yield stress, remolded strength, and liquidity index relationships for sensitive clays; citation_author=J Locat, D Demers; citation_volume=25; citation_issue=4; citation_publication_date=1988; citation_pages=799-806; citation_doi=10.1139\u002Ft88-088; citation_id=CR25\ncitation_journal_title=Eng Geol; citation_title=Analysis of a Retrogressive Landslide in Glaciolacustrine Varved Clay; citation_author=K Marko, H Tiit, T Peeter, K Volli; citation_volume=116; citation_issue=1–2; citation_publication_date=2010; citation_pages=109-116; citation_doi=10.1016\u002Fj.enggeo.2010.07.012; citation_id=CR26\nMinistère des transports, mobilité durable et électrification des transports du Québec. (2017) Guide d’utilisation Des Cartes de Contraintes Relative Aux Glisement de Terrain Dans Les Dépôts Meubles. \n                  www.portailmunicipal.gouv.qc.ca\n                  \n                \ncitation_journal_title=Eng Geol; citation_title=Mass Instabilities in Sensitive Canadian Soils; citation_author=RJ Mitchell, MA Klugman; citation_volume=14; citation_publication_date=1979; citation_pages=109-134; citation_doi=10.1016\u002F0013-7952(79)90080-2; citation_id=CR28\nMunsell HA (2009) Munsell rock-color book. Revised\ncitation_title=Looking into the earth: an introduction to geological geophysics; citation_publication_date=2000; citation_id=CR30; citation_author=AE Mussett; citation_author=M Aftab Khan; citation_publisher=Cambridge University Press\nNatural hazards–infrastructure for floods and slides (2016) In: Metode for Vurdering Av Løsne—Og Utløpsområder for Områdeskred. NVE\nPalacky GJ (1988) Resistivity characteristics of geologic targets. In: Electromagnetic Methods in Applied Geophysics, pp 53–129\ncitation_journal_title=First Break; citation_title=Clay mapping using electromagnetic methods; citation_author=GJ Palacky; citation_publication_date=1987; citation_doi=10.3997\u002F1365-2397.1987015; citation_id=CR33\ncitation_journal_title=Geosciences; citation_title=Overview of retrogressive landslide risk analysis in sensitive clay slope; citation_author=B Richer, A Saeidi, M Boivin, A Rouleau; citation_volume=10; citation_issue=8; citation_publication_date=2020; citation_pages=279; citation_doi=10.3390\u002Fgeosciences10080279; citation_id=CR34\nRocscience (2018) Slide2:Most comprehensive 2D slope stability software. 2018. \n                  https:\u002F\u002Fwww.rocscience.com\u002Fsoftware\u002Fslide2\n                  \n                \nRouleau A, Daigneault R (2013) Dépôts de Surface. CERM UQAC\ncitation_journal_title=Int J Rock Mech Min Sci; citation_title=Assessment of slide surface and pre-slide topography using site investigation data in back analysis; citation_author=A Saeidi, V Maazallahi, A Rouleau; citation_volume=88; citation_publication_date=2016; citation_pages=29-33; citation_doi=10.1016\u002Fj.ijrmms.2016.07.008; citation_id=CR37\nScott M, Raymond M (2001) ZONGE data processing two-dimensional, smooth-model CSAMT Inversion Version 3.00. In 41. Zonge Engineering and Research Organization, Inc\nSeequent (2020) Leapfrog Geo. \n                  https:\u002F\u002Fwww.seequent.com\u002Fproducts-solutions\u002Fleapfrog-Geo\u002F\n                  \n                , \n                  http:\u002F\u002Fwww.leapfrog3d.com\u002F\n                  \n                \ncitation_title=Runout of landslides in sensitive clays; citation_inbook_title=Landslides in sensitive clays; citation_publication_date=2017; citation_pages=289-300; citation_id=CR40; citation_author=SA Strand; citation_author=V Thakur; citation_author=JS L’Heureux; citation_author=S Lacasse; citation_author=K Karlsrud; citation_author=T Nyheim; citation_author=A Rosenquist Åkershult; citation_publisher=Springer\nTavenas F (1984) Landslides in Canadian sensitive clays–a state-of-the-art. In: Proceedings of the 4th international symposium on landslides, pp 16–21. Toronto, Ontario\nTavenas F, Flon P, Leroueil S, Lebuis J (1983) Remolding energy and risk of slide retrogression in sensitive clays. In: Proceedings of the symposium on slopes on soft clays, Linköping, Sweden. 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