Elevation dependence of landslide activity induced by climate change in the eastern Pamirs

Pei, Yanqian; Qiu, Haijun; Zhu, Yaru; Wang, Jiading; Yang, Dan; Tang, Bingzhe; Wang, Fei; Cao, Mingming

doi:10.1007/s10346-023-02030-w

Cited by 40 publications

(18 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Performance assess is one of the most importance steps in scientific works (Huang et al, 2021a(Huang et al, , 2021bZhuo et al, 2022Pei et al, 2023Zhu et al, 2023). The accuracy of a model is determined by the Receiver Operating Characteristic (ROC) curve approach, a widely used method for model evaluation.…”

Section: Area Under the Receiver Operating Characteristicmentioning

confidence: 99%

Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology

Li,

Meng,

Arabameri

et al. 2023

Preprint

View full text Add to dashboard Cite

Droughts as a natural calamity have wreaked havoc on human health, environment, and the economy around the world. Due to its complex and multi-faceted nature, the risk assessment of drought requires the analysis of diverse parameters and machine learning techniques provide an effective tool to approach this problem. In the present work, we have employed four machine learning models, Naïve Bayes (NB), Rotational tree- Forest by Penalizing Attributes (RF-FPA), Multi-Layer Perceptron (MLP), and Linear Discriminant Analysis (LDA) for the drought vulnerability mapping in the Najafabad watershed, Isfahan Province, Iran. The country faces serious challenge from hydrological and meteorological drought conditions. A total of 20 conditioning factors comprising of 3 topographical (slope, elevation, geomorphology), 6 environmental (NDVI, soil depth, LU/LC, soil texture, EC, soil moisture), 4 hydrological (groundwater level, drainage density, distance to stream, TWI), 4 meteorological (annual precipitation and temperature, evaporation, humidity), and 3 socio-economic (ADP, deep tune, population density) were included for the drought vulnerability mapping. The collinearity effects were checked with multicollinearity analysis prior to the spatial modelling. The variable importance of the different parameters was analysed using AdaBoost model. The results show that soil moisture is the most important parameters among all variables. It also came into the results that the RF-FPA, among all four models, is the most successful model during training (AUC = 0.976) and validation (AUC = 0.968).

show abstract

Section: Area Under the Receiver Operating Characteristicmentioning

confidence: 99%

Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology

Li,

Meng,

Arabameri

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The Qinghai‐Tibet Plateau (QTP) contains the largest permafrost region outside the northern circumpolar region and is the key geomorphological unit in Asia that affects the regional and even global climate (Yao et al., 2012; Zou et al., 2017). However, this geomorphological unit is extremely vulnerable to climate change due to elevation‐dependent warming and its delicate natural environment (Kuang & Jiao, 2016; Pei et al., 2023b; Pepin et al., 2015). There is abundant evidence proving that the warming rate on the QTP has been almost twice the global rate during the last four decades (Cheng et al., 2019; CMA Climate Change Centre, 2022; Kang et al., 2010), which is responsible for permafrost degradation and its associated hazards (Ma et al., 2023; Mu et al., 2020; Niu et al., 2012; Qiu et al., 2022; Sun et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

“…RTSs further increase erosion, sediment fluxes, and thus affect hydropower systems, water quality, and the carbon cycle (East et al, 2022;Li et al, 2021a;Pei et al, 2023a;Zhang et al, 2022a).The Qinghai-Tibet Plateau (QTP) contains the largest permafrost region outside the northern circumpolar region and is the key geomorphological unit in Asia that affects the regional and even global climate (Yao et al, 2012;Zou et al, 2017). However, this geomorphological unit is extremely vulnerable to climate change due to elevation-dependent warming and its delicate natural environment (Kuang & Jiao, 2016;Pei et al, 2023b;Pepin et al, 2015). There is abundant evidence proving that the warming rate on the QTP has been almost twice…”

mentioning

confidence: 99%

Distribution and Recurrence of Warming‐Induced Retrogressive Thaw Slumps on the Central Qinghai‐Tibet Plateau

Yang

Qiu

et al. 2023

JGR Earth Surface

Self Cite

View full text Add to dashboard Cite

Retrogressive thaw slumps (RTSs) have become a dominant geomorphic event in permafrost regions due to the modern climate change. However, the roles of topographic, vegetation, and soil factors in influencing the spatial distribution and recurrence of RTSs remain not fully understood. Here, we identified the formation and recurrence of 459 RTSs during 2008–2021 using satellite images of the central Qinghai‐Tibet Plateau (Northwest of the Beiluhe Basin, 239 km2). We found that the topographic and environmental attributes of the RTSs exhibited strong correlations with the variation in the RTS density. The RTS‐affected areas had a higher slope, elevation, relative slope position, normalized difference vegetation index, soil water content, and lower soil bulk density than other landscapes. Regarding the influence of topographic and environmental attributes on the activity status of RTSs during 2018–2020, we found that the higher slope, elevation, and soil water content were advantageous for the activity of the RTSs. The RTSs with larger sizes and presenting an elongated shape were more likely to be active. Additionally, we examined the variation of the headwall shape of RTSs based on the fractal dimension and UAV‐based orthophoto. We found that the headwall shape of RTSs becomes more complicated due to the small‐scale thawing of ice‐rich permafrost, which may further induce subsequent thaw slumping. Higher air temperature triggers new RTSs, and increased precipitation may be responsible for the further activity of RTSs. Our findings can enhance our understanding of the development pattern and mechanism of RTSs in permafrost regions.

show abstract

“…It alters underlying dynamic patterns of both large-scale oceanic [5] and small-scale atmospheric events such as floods and droughts [6,7]. Local hydrometeorological patterns are also changing through growing urbanization, deforestation, and other anthropogenic activities [8][9][10]. Although climate change is mostly claimed as the main reason behind the increase in droughts' frequency and intensity [11], the impacts of anthropogenic activities on large depletion in water storage and degradation in lakes' levels must not be ignored [12,13].…”

Section: Introductionmentioning

confidence: 99%

VMD-GP: A New Evolutionary Explicit Model for Meteorological Drought Prediction at Ungauged Catchments

Danandeh Mehr,

Reihanifar,

Alee

et al. 2023

Water

View full text Add to dashboard Cite

Meteorological drought is a common hydrological hazard that affects human life. It is one of the significant factors leading to water and food scarcity. Early detection of drought events is necessary for sustainable agricultural and water resources management. For the catchments with scarce meteorological observatory stations, the lack of observed data is the main leading cause of unfeasible sustainable watershed management plans. However, various earth science and environmental databases are available that can be used for hydrological studies, even at a catchment scale. In this study, the Global Drought Monitoring (GDM) data repository that provides real-time monthly Standardized Precipitation and Evapotranspiration Index (SPEI) across the globe was used to develop a new explicit evolutionary model for SPEI prediction at ungauged catchments. The proposed model, called VMD-GP, uses an inverse distance weighting technique to transfer the GDM data to the desired area. Then, the variational mode decomposition (VMD), in conjunction with state-of-the-art genetic programming, is implemented to map the intrinsic mode functions of the GMD series to the subsequent SPEI values in the study area. The suggested model was applied for the month-ahead prediction of the SPEI series at Erbil, Iraq. The results showed a significant improvement in the prediction accuracy over the classic GP and gene expression programming models developed as the benchmarks.

show abstract

Elevation dependence of landslide activity induced by climate change in the eastern Pamirs

Cited by 40 publications

References 83 publications

Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology

Spatial Distribution of Drought Vulnerability Mapping: Introducing a new methodology

Distribution and Recurrence of Warming‐Induced Retrogressive Thaw Slumps on the Central Qinghai‐Tibet Plateau

VMD-GP: A New Evolutionary Explicit Model for Meteorological Drought Prediction at Ungauged Catchments

Contact Info

Product

Resources

About