Landslide Hazards and Climate Change Adaptation of Transport Infrastructures in Germany

Klose, Martin; Auerbach, Markus; Herrmann, Carina; Kumerics, Christine; Gratzki, A.

doi:10.1007/978-3-319-59469-9_48

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…Landslides are influenced by land use (Chen & Huang, 2013;Chen et al, 2019;Glade, 2003;Karsli et al, 2009;Meneses et al, 2019;Reichenbach et al, 2014;Van Beek & Van Asch, 2004), climatic factors (Borgatti & Soldati, 2018;Khan et al, 2021;Klose et al, 2017;Ma et al, 2020a;Pánek, 2019;Patton et al, 2019;Peres & Cancelliere, 2018;Wood et al, 2020;Zhou et al, 2018), soil type (Cerri et al, 2017;Marin & Velásquez, 2020;Strauch et al, 2018;Wang et al, 2020;Yu et al, 2021;Zhuo et al, 2019), slopes (Marc et al, 2018;Nguyen et al, 2017), and others (Forte et al, 2019;Mind'je et al, 2020;Palladino et al, 2018;Xu et al, 2018). Based on the above, the variables of precipitation, temperature, evapotranspiration, altitude, slope, latitude and longitude, soil type, and land use (high Andean grassland, agricultural zone, and urban zone) were considered.…”

Section: Data Selection Training and Validation Of The Mass Movement ...mentioning

confidence: 99%

Influence of high Andean grasslands on landslide reduction in Peru

Cerna Cueva,

Uriarte-Barraza,

Lobaton-Tarazona

et al. 2024

Sci. agropecu

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Agricultural and urban expansion has caused considerable degradation of ecosystems. In the case of Peruvian high Andean grasslands, it was reported that between 2000 and 2009, this ecosystem was reduced by 7%. The limited or no protection they receive is partly due to the fact that the benefits of ecosystem services are not widely known. This research aims to establish and predict the influence of high Andean grasslands on the annual occurrence of landslides. To do so, we identified occurrences of landslides, falls, huaycos, avalanches, and alluviums in high Andean grasslands. We also examined urban areas and agricultural zones of Peru for the period from 2003 to 2016. Subsequently, we extracted data on precipitation, temperature, slopes, soil types, and geographical variables. This data was used to train a machine learning model. The results show that 96% of landslides occurred in human-intervened areas, and only 4% in high Andean grasslands. Precipitation and slope thresholds for landslide occurrence are higher in high Andean grasslands compared to agricultural and urban areas. The best-performing machine learning models were linear regression, Gaussian processes, random forest, and support vector machine. They had coefficients of determination of R² = 0.80, 0.80, 0.66, and 0.64, respectively. Predictions show that if agricultural or urban areas are established in wet or dry puna grasslands, the average number of occurrences multiplies. The multiplier factors are 2.1 and 7.08, the number of deaths by 2.8 and 10.49, the number of houses destroyed by 2.4 and 7.51, and the number of roads destroyed by 2.2 and 7.37, respectively. The study demonstrates that conserving high Andean grasslands significantly reduces landslides compared to urban or agricultural areas.

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Section: Data Selection Training and Validation Of The Mass Movement ...mentioning

confidence: 99%

Influence of high Andean grasslands on landslide reduction in Peru

Cerna Cueva,

Uriarte-Barraza,

Lobaton-Tarazona

et al. 2024

Sci. agropecu

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“…In the 21 st century, flooding is expected to cause annual losses of €89 million for Australian railways (Kellermann et al, 2016). Climate-change-induced floods result in yearly losses of around €2.5 billion and €581 million for the European transport and railway networks, respectively (Klose et al, 2017;Bubeck et al, 2019). Over the next 4 decades (2040-2050), precipitation-induced damages to railways are projected to increase, leading to an 80% rise in railway transportation costs, and railway network risks are expected to increase by 255%-310% (Bubeck et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The impact of precipitation changes on the safety of railway operations in China under the background of climate change

Jiang,

Chen,

Wang

et al. 2024

Front. Earth Sci.

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Global climate change has intensified the water cycle, leading to frequent extreme precipitation events, posing a significant threat to railway infrastructure and safety operations. Based on the analysis of past and future precipitation changes in China, this study investigates the impact of climate change on railway safety operations. The study reveals the following findings: (1) Under the influence of the intensified East Asian summer monsoon and the northward shift of the subtropical high during the 2017–2021 compared to the 2012–2016, precipitation has significantly decreased (120 mm) in the regions south of the Yangtze River and South China, while it has increased (60 mm) in the regions from the eastern of Northwest China to the middle and lower reaches of Yangtze River; The operational precipitation risk has decreased for Urumqi, Lanzhou, Qinghai-Tibet Group, Xi’an, and Wuhan railway bureaus (abbreviated as Bureau), while it has increased for Nanchang, Chengdu, Zhengzhou, Shanghai, and Shenyang Bureaus. Particularly noteworthy is that despite a decrease in total annual precipitation for Nanchang bureau (15.3 mm/a), the frequency of intense precipitation events has increased, leading to an increased operational precipitation risk. (2) During the 21st century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that most of the China will experience an increasing trend in precipitation, with significant increases in precipitation observed in the regions south of the Yangtze Rive, South and Southwest China. The higher the greenhouse gas emissions, the more pronounced the increasing trend in precipitation. (3) Compared to the 20th century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that the total annual precipitation hours, railway inspection, speed limit, and closure risk hours have all increased on a national scale during the 21st century. The operational precipitation risk for railways has also increased. The higher the alert level for railway precipitation (precipitation < inspection < speed limit < closure), the higher the proportion of risk hours compared to the 20th century. By the late 21st century, the railway inspection, speed limit, and closure risk hours have increased by 175%, 463%, and 647%, respectively, compared to the 20th century.

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“…This aim is particularly important, also because much research (Nemry and Demirel, 2012;Michaelides, 2014;Strauch et al, 2015;Klose et al, 2017;Matulla et al, 2017) has stressed that the exposure of road networks to slope instabilities could increase as a consequence of the climate change and of the economic rising income in different countries.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Bordoni

Persichillo

Meisina

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides cause severe damage to the road network of the hit zone, in terms of both direct (partial or complete destruction of a road or blockages) and indirect (traffic restriction or the cut-off of a certain area) costs. Thus, the identification of the parts of the road network that are more susceptible to landslides is fundamental to reduce the risk to the population potentially exposed and the financial expense caused by the damage. For these reasons, this paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to being hit by shallow landslides triggered in slopes upstream from the infrastructure. This model was based on the Generalized Additive Method, where the function relating predictors and response variable is an empirically fitted smooth function that allows fitting the data in the more likely functional form, considering also non-linear relations. This work also analyzed the importance, on the estimation of the susceptibility, of considering or not the sediment connectivity, which influences the path and the travel distance of the materials mobilized by a slope failure until hitting a potential barrier such as a road. The study was carried out in a catchment of northeastern Oltrepò Pavese (northern Italy), where several shallow landslides affected roads in the last 8 years. The most significant explanatory variables were selected by a random partition of the available dataset in two parts (training and test subsets), 100 times according to a bootstrap procedure. These variables (selected 80 times by the bootstrap procedure) were used to build the final susceptibility model, the accuracy of which was estimated through a 100-fold repetition of the holdout method for regression, based on the training and test sets created through the 100 bootstrap model selection. The presented methodology allows the identification, in a robust and reliable way, of the most susceptible road sectors that could be hit by sediments delivered by landslides. The best predictive capability was obtained using a model in which the index of connectivity was also calculated according to a linear relationship, was considered. Most susceptible road traits resulted to be located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. Different land use scenarios were considered in order to estimate possible changes in road susceptibility. Land use classes of the study area were characterized by similar connectivity features. As a consequence, variations on the susceptibility of the road network according to different scenarios of distribution of land cover were limited. The results of this research demonstrate the ability of the developed methodology in the assessment of susceptible roads. This could give the managers of infrastructure information about the criticality of the different road traits, thereby allowing attention and economic budgets to be shifted towards the most critical assets, where structural and non-structur...

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Landslide Hazards and Climate Change Adaptation of Transport Infrastructures in Germany

Cited by 7 publications

References 5 publications

Influence of high Andean grasslands on landslide reduction in Peru

Influence of high Andean grasslands on landslide reduction in Peru

The impact of precipitation changes on the safety of railway operations in China under the background of climate change

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

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