Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change

Lin, Qigen; Steger, Stefan; Pittore, Massimiliano; Zhang, Jiahui; Wang, Leibin; Jiang, Tong; Wang, Ying

doi:10.1016/j.scitotenv.2022.158049

Cited by 41 publications

(13 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But, we already envision a next step where the whole space-time domain is exploited to model HMP impact levels per Chinese catchments and opting this time for a yearly or even seasonal temporal partition of the thirty years under examination. Such a model should be able to shed more light in the role of climate change with respect to HMP losses (Lin et al, 2022), but also on how urban expansion correlates to them (Zhao et al, 2022). Notably, China has undergone a large urbanization phase in the last few decades, which has certainly been associated…”

Section: Discussionmentioning

confidence: 99%

Impact-based probabilistic modeling of hydro-morphological processes in China (1985-2015)

Wang¹,

Cheng²,

Zhang³

et al. 2022

Preprint

View full text Add to dashboard Cite

Hydro-morphological processes (HMP, any natural phenomenon contained within the spectrum defined between debris flows and flash floods) pose a relevant threat to infrastructure, urban and rural settlements and to lives in general. This has been widely observed in recent years and will likely become worse as climate change will influence the spatio-temporal pattern of precipitation events. The modelling of where HMP-driven hazards may occur can help define the appropriate course of actions before and during a crisis, reducing the potential losses that HMPs cause in their wake. However, the probabilistic information on locations prone to experience a given hazard is not sufficient to depict the risk our society may incur. To cover this aspect, modeling the loss information could open up to better territorial management strategies.In this work, we made use of the HMP catalogue of China. This catalogue reports reliable records from 1985 to 2015 across the whole Chinese territory. Specifically, we implemented the Light Gradient Boosting (LGB) classifier to model the impact level that locations across China have suffered from HMPs over the thirty-year record. In doing so, we estimated spatial probabilities of certain HMP impact, something that has yet to be tested in the natural hazard community, especially over such a large spatio-temporal domain.This experiment follows a project launched by the Chinese government with the aim of improving national efforts against climate change and improving societal resilience to disastrous events. In this context, the good predictive performance our model produced suggest that the cartographic output could be useful to inform authorities of locations prone to human and infrastructural losses of specific magnitudes.

show abstract

Section: Discussionmentioning

confidence: 99%

Impact-based probabilistic modeling of hydro-morphological processes in China (1985-2015)

Wang¹,

Cheng²,

Zhang³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The volatility of the monsoon climate leads to more frequent catastrophic events such as rainstorms and typhoons, and further triggers landslides and debris flows in vast mountainous areas (Wu et al., 2019). Such extreme weather events and the associated landslide hazards are likely to increase as a result of global climate change (Lin et al., 2022; Marengo et al., 2021). Since China has a large territory, the geomorphic and climatic environments of different areas have prominent spatial heterogeneity.…”

Section: Methodsmentioning

confidence: 99%

Contrasting Population Projections to Induce Divergent Estimates of Landslides Exposure Under Climate Change

Lin,

Steger,

Pittore

et al. 2023

Earth's Future

Self Cite

View full text Add to dashboard Cite

At first glance, assessing future landslide‐exposed population appears to be a straightforward task if landslide hazard estimates, climate change, and population projections are available. However, the intersection of landslide hazard with socioeconomic elements may result in significant variation of estimated landslide exposure due to considerable variations in population projections. This study aims to investigate the effects of different sources of population data on the evaluation of landslide‐exposed population in China under four Shared Socioeconomic Pathways (SSPs) scenarios. We utilize multiple global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 and six high‐resolution spatially explicit static and dynamic population data sets to drive available landslide models. The results indicate an overall rise in landslide hazard projections, with an increase in the potential impact area of 0.4%–2.7% and an increase in the landslide frequency of 4.7%–20.1%, depending on the SSPs scenarios and future periods. However, the likely changes in future landslide exposed population, as modeled by incorporating population data from different sources with landslide hazard, yield divergent outcomes depending on the population data source. Thus, some of the projections depict an increase in future landslide exposure, while others show a clear decrease. The nationwide divergence ranged from −64% to +48%. These divergent findings were mainly attributed to differences in population data and a lesser extent to variations in GCMs. The present findings highlight the need to pay closer attention to the dynamic evolution of the elements at risk and the associated data uncertainties.

show abstract

“…According to DeGroot (2003) [1], Benaissa et al (1989) [2], Belouar et al (2004) [3], Lafifi et al (2008) [4], and Ykhlef et al (2014) [5], the distribution of different strengths within a slope may have a significant impact on the time to slope failure. To understand landslide events and to consider proportionate geotechnical countermeasures, a proper calculation of the strength parameters and their spatial distribution within a slope is fundamentally necessary [6]. In the case of Constantine, the issue is mostly caused by at least these factors:…”

Section: Introductionmentioning

confidence: 99%

Experimental Studies on Some Clays Leading to Instability

2023

View full text Add to dashboard Cite

The landslide problem in the city of Constantine (Algeria) is mostly due to clayey soil, which is covering the whole area. Therefore, all the structures and foundations built over such soil are quite vulnerable. The sensitivity of this soil increases during the rainfall season, which might reach an extreme magnitude and cause damage to the structures. To understand some aspects of the failure of the mentioned soil and its mechanism, a large campaign of geotechnical characterization was undertaken using samples from the area. The specific gravity, Atterberg limits, and coefficient of lateral earth pressure at rest were determined. Samples were tested in triaxial stress path cells over a range of stresses, with the test being either stress- or strain-controlled, leading to sliding phenomena under different stress levels. The clays can be classified as over-consolidated soils. The test program and the characterization study indicated that Kois directly related to the stress history of the soil and also dependent upon the state of the sample before the test (i.e., undisturbed or disturbed). The clay minerals in the Mio-Pliocene landslide zones in Constantine are mostly montmorillonite and kaolinite, which have the lowest frictional resistance. As the montmorillonite content increases, the angle of internal friction decreases. The present study focuses on the critical state analysis since all the behavior problems of these tested samples show a peak shear strength, which is characteristic of over-consolidation materials that could lead to instability in this area. Doi: 10.28991/CEJ-2023-09-02-012 Full Text: PDF

show abstract

Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change

Cited by 41 publications

References 69 publications

Impact-based probabilistic modeling of hydro-morphological processes in China (1985-2015)

Impact-based probabilistic modeling of hydro-morphological processes in China (1985-2015)

Contrasting Population Projections to Induce Divergent Estimates of Landslides Exposure Under Climate Change

Experimental Studies on Some Clays Leading to Instability

Contact Info

Product

Resources

About