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Application of landslide hazard scenarios at annual scale in the Niraj River basin (Transylvania Depression, Romania)
The main objective of the study was to determine the landslide hazard in the drainage basin of the Niraj River taking into account as far as possible the dichotomous relationship between space and time. A broad inventory of the Romanian approaches concerned with natural hazard prediction reveals a c...
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Published in: | Natural hazards (Dordrecht) 2015-07, Vol.77 (3), p.1573-1592 |
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description | The main objective of the study was to determine the landslide hazard in the drainage basin of the Niraj River taking into account as far as possible the dichotomous relationship between space and time. A broad inventory of the Romanian approaches concerned with natural hazard prediction reveals a clear preference for spatial analysis, while the temporal scale was almost totally neglected. To fill this gap, the proposed methodological approach combines GIS techniques for quantitative analysis with statistical analysis and detailed observation in the field, both directly and indirectly through remote sensing. Niraj River drainage basin is extended over an area of 658 km
2
in the east-central part of Transylvania Depression, one of Romania’s major geographic units. Due to the substrate composition, consisting essentially of marls, clays and sands, this area is often affected by rotational and shallow landslides causing important material damages. The first step of this approach was to develop a spatial model for determining the susceptibility to landslide occurrence related to several causative factors: lithology, geomorphology, structural, hydroclimatic, seismic, land use and anthropogenic factors. In order to develop the temporal side of the prediction, two subsidiary objectives were assumed. The first one, to obtain a more detailed database which contains also the temporal moments of the landslides activation or reactivation. Secondly, to realise a statistical analysis of cumulative rainfall, over a period of 90 days prior to the time of each sliding event, which allows us to identify the correlation between cumulative rainfall which had triggered recorded landslides (beginning with the year 2005) and the landslide occurrence moments. On this basis, the main results obtained were: (1) the identification the recurring interval of each value of precipitation amount; (2) the assessment of the temporal probability of landslide occurrence, accepting the assumption that the precipitation amount which led to landslide activation in the past will have the same effects in the future; and (3) the development of four scenarios of landslide occurrence, starting from the events of May 2005, April 2006, July 2010 and February 2013, which were used to determine the annual probability of landslide occurrence under similar precipitation conditions. Finally, by identifying the correlation curves between the probability of landslides and time, taking into account the suscep |
doi_str_mv | 10.1007/s11069-015-1665-2 |
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2
in the east-central part of Transylvania Depression, one of Romania’s major geographic units. Due to the substrate composition, consisting essentially of marls, clays and sands, this area is often affected by rotational and shallow landslides causing important material damages. The first step of this approach was to develop a spatial model for determining the susceptibility to landslide occurrence related to several causative factors: lithology, geomorphology, structural, hydroclimatic, seismic, land use and anthropogenic factors. In order to develop the temporal side of the prediction, two subsidiary objectives were assumed. The first one, to obtain a more detailed database which contains also the temporal moments of the landslides activation or reactivation. Secondly, to realise a statistical analysis of cumulative rainfall, over a period of 90 days prior to the time of each sliding event, which allows us to identify the correlation between cumulative rainfall which had triggered recorded landslides (beginning with the year 2005) and the landslide occurrence moments. On this basis, the main results obtained were: (1) the identification the recurring interval of each value of precipitation amount; (2) the assessment of the temporal probability of landslide occurrence, accepting the assumption that the precipitation amount which led to landslide activation in the past will have the same effects in the future; and (3) the development of four scenarios of landslide occurrence, starting from the events of May 2005, April 2006, July 2010 and February 2013, which were used to determine the annual probability of landslide occurrence under similar precipitation conditions. Finally, by identifying the correlation curves between the probability of landslides and time, taking into account the susceptibility classes, additional scenarios were determined for representative years in the future (2021, 2050, 2071 and 2100). The probability values were used to create correlation curves for each susceptibility class, the corresponding mathematical expressions facilitating the computation of annual probability. The results from the study area highlight the fact that there is an acceleration trend of landslide processes in the high susceptibility area.</description><identifier>ISSN: 0921-030X</identifier><identifier>EISSN: 1573-0840</identifier><identifier>DOI: 10.1007/s11069-015-1665-2</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Activation ; Anthropogenic factors ; Civil Engineering ; Correlation ; Drainage basins ; Earth and Environmental Science ; Earth Sciences ; Environmental Management ; Geological hazards ; Geomorphology ; Geophysics/Geodesy ; Geotechnical Engineering & Applied Earth Sciences ; Hazards ; Hydrogeology ; Land use ; Landslides ; Landslides & mudslides ; Lithology ; Mathematical models ; Natural Hazards ; Original Paper ; Rainfall ; Remote sensing ; Risk assessment ; River basins ; Rivers ; Spatial analysis ; Statistical analysis</subject><ispartof>Natural hazards (Dordrecht), 2015-07, Vol.77 (3), p.1573-1592</ispartof><rights>Springer Science+Business Media Dordrecht 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a405t-a09657affa50933e1988e5424048b3ca7004fa9eff322aef2c2b40b95b3aefd63</citedby><cites>FETCH-LOGICAL-a405t-a09657affa50933e1988e5424048b3ca7004fa9eff322aef2c2b40b95b3aefd63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Sanda, Roşca</creatorcontrib><creatorcontrib>Ştefan, Bilaşco</creatorcontrib><creatorcontrib>Dănuţ, Petrea</creatorcontrib><creatorcontrib>Ioan, Fodorean</creatorcontrib><creatorcontrib>Iuliu, Vescan</creatorcontrib><creatorcontrib>Sorin, Filip</creatorcontrib><title>Application of landslide hazard scenarios at annual scale in the Niraj River basin (Transylvania Depression, Romania)</title><title>Natural hazards (Dordrecht)</title><addtitle>Nat Hazards</addtitle><description>The main objective of the study was to determine the landslide hazard in the drainage basin of the Niraj River taking into account as far as possible the dichotomous relationship between space and time. A broad inventory of the Romanian approaches concerned with natural hazard prediction reveals a clear preference for spatial analysis, while the temporal scale was almost totally neglected. To fill this gap, the proposed methodological approach combines GIS techniques for quantitative analysis with statistical analysis and detailed observation in the field, both directly and indirectly through remote sensing. Niraj River drainage basin is extended over an area of 658 km
2
in the east-central part of Transylvania Depression, one of Romania’s major geographic units. Due to the substrate composition, consisting essentially of marls, clays and sands, this area is often affected by rotational and shallow landslides causing important material damages. The first step of this approach was to develop a spatial model for determining the susceptibility to landslide occurrence related to several causative factors: lithology, geomorphology, structural, hydroclimatic, seismic, land use and anthropogenic factors. In order to develop the temporal side of the prediction, two subsidiary objectives were assumed. The first one, to obtain a more detailed database which contains also the temporal moments of the landslides activation or reactivation. Secondly, to realise a statistical analysis of cumulative rainfall, over a period of 90 days prior to the time of each sliding event, which allows us to identify the correlation between cumulative rainfall which had triggered recorded landslides (beginning with the year 2005) and the landslide occurrence moments. On this basis, the main results obtained were: (1) the identification the recurring interval of each value of precipitation amount; (2) the assessment of the temporal probability of landslide occurrence, accepting the assumption that the precipitation amount which led to landslide activation in the past will have the same effects in the future; and (3) the development of four scenarios of landslide occurrence, starting from the events of May 2005, April 2006, July 2010 and February 2013, which were used to determine the annual probability of landslide occurrence under similar precipitation conditions. Finally, by identifying the correlation curves between the probability of landslides and time, taking into account the susceptibility classes, additional scenarios were determined for representative years in the future (2021, 2050, 2071 and 2100). The probability values were used to create correlation curves for each susceptibility class, the corresponding mathematical expressions facilitating the computation of annual probability. The results from the study area highlight the fact that there is an acceleration trend of landslide processes in the high susceptibility area.</description><subject>Activation</subject><subject>Anthropogenic factors</subject><subject>Civil Engineering</subject><subject>Correlation</subject><subject>Drainage basins</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environmental Management</subject><subject>Geological hazards</subject><subject>Geomorphology</subject><subject>Geophysics/Geodesy</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Hazards</subject><subject>Hydrogeology</subject><subject>Land use</subject><subject>Landslides</subject><subject>Landslides & mudslides</subject><subject>Lithology</subject><subject>Mathematical models</subject><subject>Natural Hazards</subject><subject>Original Paper</subject><subject>Rainfall</subject><subject>Remote sensing</subject><subject>Risk assessment</subject><subject>River basins</subject><subject>Rivers</subject><subject>Spatial analysis</subject><subject>Statistical analysis</subject><issn>0921-030X</issn><issn>1573-0840</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqFkUtLxDAUhYMoOD5-gLuAGwWrN0nTNkvxDaIgI7gLt53EydBJa9IK-uvNMC5EEFchh-8cOPcQcsDglAGUZ5ExKFQGTGasKGTGN8iEyVJkUOWwSSagOMtAwMs22YlxAcBYwdWEjOd937oGB9d52lnaop_F1s0MneMnhhmNjfEYXBcpDhS9H7FNGraGOk-HuaEPLuCCPrl3E2iNMalH04A-frTv6B3SS9MHE2PKP6FP3XKlHe-RLYttNPvf7y55vr6aXtxm9483dxfn9xnmIIcMQRWyRGtRghLCMFVVRuY8h7yqRYMlQG5RGWsF52gsb3idQ61kLdJvVohdcrTO7UP3Npo46KVLhdrU0nRj1KxKCQoKIf5HyzLdtSxFldDDX-iiG4NPRTQrKslyXnFIFFtTTehiDMbqPrglhg_NQK820-vNdNpMrzbTPHn42hMT619N-JH8p-kL2XaZTg</recordid><startdate>20150701</startdate><enddate>20150701</enddate><creator>Sanda, Roşca</creator><creator>Ştefan, Bilaşco</creator><creator>Dănuţ, Petrea</creator><creator>Ioan, 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Hazards</stitle><date>2015-07-01</date><risdate>2015</risdate><volume>77</volume><issue>3</issue><spage>1573</spage><epage>1592</epage><pages>1573-1592</pages><issn>0921-030X</issn><eissn>1573-0840</eissn><abstract>The main objective of the study was to determine the landslide hazard in the drainage basin of the Niraj River taking into account as far as possible the dichotomous relationship between space and time. A broad inventory of the Romanian approaches concerned with natural hazard prediction reveals a clear preference for spatial analysis, while the temporal scale was almost totally neglected. To fill this gap, the proposed methodological approach combines GIS techniques for quantitative analysis with statistical analysis and detailed observation in the field, both directly and indirectly through remote sensing. Niraj River drainage basin is extended over an area of 658 km
2
in the east-central part of Transylvania Depression, one of Romania’s major geographic units. Due to the substrate composition, consisting essentially of marls, clays and sands, this area is often affected by rotational and shallow landslides causing important material damages. The first step of this approach was to develop a spatial model for determining the susceptibility to landslide occurrence related to several causative factors: lithology, geomorphology, structural, hydroclimatic, seismic, land use and anthropogenic factors. In order to develop the temporal side of the prediction, two subsidiary objectives were assumed. The first one, to obtain a more detailed database which contains also the temporal moments of the landslides activation or reactivation. Secondly, to realise a statistical analysis of cumulative rainfall, over a period of 90 days prior to the time of each sliding event, which allows us to identify the correlation between cumulative rainfall which had triggered recorded landslides (beginning with the year 2005) and the landslide occurrence moments. On this basis, the main results obtained were: (1) the identification the recurring interval of each value of precipitation amount; (2) the assessment of the temporal probability of landslide occurrence, accepting the assumption that the precipitation amount which led to landslide activation in the past will have the same effects in the future; and (3) the development of four scenarios of landslide occurrence, starting from the events of May 2005, April 2006, July 2010 and February 2013, which were used to determine the annual probability of landslide occurrence under similar precipitation conditions. Finally, by identifying the correlation curves between the probability of landslides and time, taking into account the susceptibility classes, additional scenarios were determined for representative years in the future (2021, 2050, 2071 and 2100). The probability values were used to create correlation curves for each susceptibility class, the corresponding mathematical expressions facilitating the computation of annual probability. The results from the study area highlight the fact that there is an acceleration trend of landslide processes in the high susceptibility area.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11069-015-1665-2</doi><tpages>20</tpages></addata></record> |
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subjects | Activation Anthropogenic factors Civil Engineering Correlation Drainage basins Earth and Environmental Science Earth Sciences Environmental Management Geological hazards Geomorphology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Hazards Hydrogeology Land use Landslides Landslides & mudslides Lithology Mathematical models Natural Hazards Original Paper Rainfall Remote sensing Risk assessment River basins Rivers Spatial analysis Statistical analysis |
title | Application of landslide hazard scenarios at annual scale in the Niraj River basin (Transylvania Depression, Romania) |
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