{"title":"利用地面激光扫描技术调查降水、融雪和冻融对科罗拉多州格伦伍德峡谷落石的影响","authors":"Luke Weidner, Gabriel Walton, Cameron Phillips","doi":"10.1007/s10346-024-02266-0","DOIUrl":null,"url":null,"abstract":"<p>Understanding the triggering factors leading to rockfall is essential in managing their risk to transportation infrastructure. Precipitation and freeze-thaw (FT) are widely studied rockfall triggers, but developing reliable, quantitative methods to forecast rockfall in response to weather events remains challenging. Terrestrial laser scanning (TLS) is a powerful tool for high-accuracy modeling of rock slopes, but the frequency of scanning is often too low to correlate rockfall behavior with weather events or seasonal trends. We conducted a TLS campaign between 2017 and 2022 in Glenwood Canyon, Colorado, to investigate the seasonal variability in rockfall triggering and conditioning mechanisms. A total of 44 scans were collected over 5 years and were processed to allow for consistent detection of rockfalls larger than 0.0036 m<sup>3</sup> in volume. Meteorological variables relating to precipitation, snowpack, and temperature were modeled using the National Weather Service SNODAS product and were used to complete an exploratory analysis of the correlation of various weather indices with rockfall rate over time. It was found that the short-term sum of liquid precipitation and snowmelt (averaged over the scanning interval or the max single-day total) was a strong predictor of rockfall volume rate between 2018 and 2020, especially in the spring and summer months; a linear model of max daily liquid was able to explain 65% of the variance (<i>R</i><sup>2</sup><sub>adj</sub>) in rockfall volume rate in March through August. This implicates springtime snowmelt and rain-on-snow events as strong predictors of rockfall at the study site. We interpret these observations to indicate that snowmelt and rainfall are acting to trigger blocks that have been conditioned (destabilized) over the preceding winter.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating the influences of precipitation, snowmelt, and freeze-thaw on rockfall in Glenwood Canyon, Colorado using terrestrial laser scanning\",\"authors\":\"Luke Weidner, Gabriel Walton, Cameron Phillips\",\"doi\":\"10.1007/s10346-024-02266-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Understanding the triggering factors leading to rockfall is essential in managing their risk to transportation infrastructure. Precipitation and freeze-thaw (FT) are widely studied rockfall triggers, but developing reliable, quantitative methods to forecast rockfall in response to weather events remains challenging. Terrestrial laser scanning (TLS) is a powerful tool for high-accuracy modeling of rock slopes, but the frequency of scanning is often too low to correlate rockfall behavior with weather events or seasonal trends. We conducted a TLS campaign between 2017 and 2022 in Glenwood Canyon, Colorado, to investigate the seasonal variability in rockfall triggering and conditioning mechanisms. A total of 44 scans were collected over 5 years and were processed to allow for consistent detection of rockfalls larger than 0.0036 m<sup>3</sup> in volume. Meteorological variables relating to precipitation, snowpack, and temperature were modeled using the National Weather Service SNODAS product and were used to complete an exploratory analysis of the correlation of various weather indices with rockfall rate over time. It was found that the short-term sum of liquid precipitation and snowmelt (averaged over the scanning interval or the max single-day total) was a strong predictor of rockfall volume rate between 2018 and 2020, especially in the spring and summer months; a linear model of max daily liquid was able to explain 65% of the variance (<i>R</i><sup>2</sup><sub>adj</sub>) in rockfall volume rate in March through August. This implicates springtime snowmelt and rain-on-snow events as strong predictors of rockfall at the study site. We interpret these observations to indicate that snowmelt and rainfall are acting to trigger blocks that have been conditioned (destabilized) over the preceding winter.</p>\",\"PeriodicalId\":17938,\"journal\":{\"name\":\"Landslides\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Landslides\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s10346-024-02266-0\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, GEOLOGICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Landslides","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s10346-024-02266-0","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
Investigating the influences of precipitation, snowmelt, and freeze-thaw on rockfall in Glenwood Canyon, Colorado using terrestrial laser scanning
Understanding the triggering factors leading to rockfall is essential in managing their risk to transportation infrastructure. Precipitation and freeze-thaw (FT) are widely studied rockfall triggers, but developing reliable, quantitative methods to forecast rockfall in response to weather events remains challenging. Terrestrial laser scanning (TLS) is a powerful tool for high-accuracy modeling of rock slopes, but the frequency of scanning is often too low to correlate rockfall behavior with weather events or seasonal trends. We conducted a TLS campaign between 2017 and 2022 in Glenwood Canyon, Colorado, to investigate the seasonal variability in rockfall triggering and conditioning mechanisms. A total of 44 scans were collected over 5 years and were processed to allow for consistent detection of rockfalls larger than 0.0036 m3 in volume. Meteorological variables relating to precipitation, snowpack, and temperature were modeled using the National Weather Service SNODAS product and were used to complete an exploratory analysis of the correlation of various weather indices with rockfall rate over time. It was found that the short-term sum of liquid precipitation and snowmelt (averaged over the scanning interval or the max single-day total) was a strong predictor of rockfall volume rate between 2018 and 2020, especially in the spring and summer months; a linear model of max daily liquid was able to explain 65% of the variance (R2adj) in rockfall volume rate in March through August. This implicates springtime snowmelt and rain-on-snow events as strong predictors of rockfall at the study site. We interpret these observations to indicate that snowmelt and rainfall are acting to trigger blocks that have been conditioned (destabilized) over the preceding winter.
期刊介绍:
Landslides are gravitational mass movements of rock, debris or earth. They may occur in conjunction with other major natural disasters such as floods, earthquakes and volcanic eruptions. Expanding urbanization and changing land-use practices have increased the incidence of landslide disasters. Landslides as catastrophic events include human injury, loss of life and economic devastation and are studied as part of the fields of earth, water and engineering sciences. The aim of the journal Landslides is to be the common platform for the publication of integrated research on landslide processes, hazards, risk analysis, mitigation, and the protection of our cultural heritage and the environment. The journal publishes research papers, news of recent landslide events and information on the activities of the International Consortium on Landslides.
- Landslide dynamics, mechanisms and processes
- Landslide risk evaluation: hazard assessment, hazard mapping, and vulnerability assessment
- Geological, Geotechnical, Hydrological and Geophysical modeling
- Effects of meteorological, hydrological and global climatic change factors
- Monitoring including remote sensing and other non-invasive systems
- New technology, expert and intelligent systems
- Application of GIS techniques
- Rock slides, rock falls, debris flows, earth flows, and lateral spreads
- Large-scale landslides, lahars and pyroclastic flows in volcanic zones
- Marine and reservoir related landslides
- Landslide related tsunamis and seiches
- Landslide disasters in urban areas and along critical infrastructure
- Landslides and natural resources
- Land development and land-use practices
- Landslide remedial measures / prevention works
- Temporal and spatial prediction of landslides
- Early warning and evacuation
- Global landslide database