High methane emissions from thermokarst lakes on the Tibetan Plateau are largely attributed to ebullition fluxes

Wang, Lei; Du, Zheng; Wei, Zhiqiang; Xu, Qian; Feng, Yaru; Lin, Penglin; Lin, Jian; Chen, Shengyun; Qiao, Yongping; Shi, Jianzong; Xiao, Cunde

doi:10.1016/j.scitotenv.2021.149692

Cited by 35 publications

(30 citation statements)

References 105 publications

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“…on Earth (Hugelius et al, 2014;McGuire et al, 2018;Schuur et al, 2015). Abrupt permafrost thaw due to rapid warming can induce profound geomorphic perturbations (Chen et al, 2018;Lewkowicz & Way, 2019;Schuur et al, 2008), which has caused accelerated permafrost soil OC decomposition and released as a greenhouse gas in both circum-Artic and high-elevation regions (Abbott & Jones, 2015;Turetsky et al, 2020;L. Wang et al, 2021).…”

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confidence: 99%

Sentinel‐Based Inventory of Thermokarst Lakes and Ponds Across Permafrost Landscapes on the Qinghai‐Tibet Plateau

Wei

Wang

et al. 2021

Earth and Space Science

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confidence: 99%

Sentinel‐Based Inventory of Thermokarst Lakes and Ponds Across Permafrost Landscapes on the Qinghai‐Tibet Plateau

Wei

Wang

et al. 2021

Earth and Space Science

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“…Meanwhile, the consequences will lead to vital feedbacks to climate systems (Zhang et al, 2020;Wang et al, 2021). Many researches have studied the complex responses and feedbacks of permafrost to climate change (Yang et al, 2019), while spatial modeling of permafrost dynamics using land surface models has become an important approach (Ji et al, 2022).…”

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confidence: 99%

A new 2010 permafrost distribution map over the Qinghai-Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling

Cao

Zhang

et al. 2022

Preprint

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Abstract. Permafrost over the Qinghai-Tibet Plateau (QTP) has gained increasing attention due to its high sensitivity to climate change. Numerous spatial modeling studies have been conducted on the QTP to assess the status of permafrost, project future changes in permafrost, and diagnose contributors to permafrost degradation. Due to very limited number of observation stations on the QTP, these modeling studies are often hampered by the lack of validation references, calibration targets, and model constraints, whereas a high-quality permafrost distribution map can be a good option as a benchmark for spatial simulation results. Existing permafrost distribution maps on the QTP can hardly serve this purpose. An ideal benchmark map for spatial modeling should be methodologically sound, have sufficient accuracy, and be based on observations collected in specific mapping years, rather than all historical data spanning several decades. Therefore, in this study, we created a new permafrost distribution map over the QTP in 2010 through a novel permafrost mapping approach with satellite-derived ground surface thawing/freezing indices as input and survey-based subregion permafrost maps as constraints. This approach was further improved in this study to reduce parametric equifinality. It accounts for the effects of local factors by incorporating into the model an empirical soil parameter whose values are optimally estimated through spatial clustering and parameter optimization constrained by survey-based subregion permafrost maps. This new map shows a total permafrost area of about 1.086×106 km2 (41.2 % of the QTP area) and seasonally frozen ground of about 1.447×106 km2 (54.9 %) in 2010, excluding glaciers and lakes. Validations using survey-based subregion permafrost maps (Kappa = 0.74) and borehole records (Overall Accuracy = 0.85 and Kappa = 0.43) showed higher accuracy of this map than two recent maps. Inspection of regions with obvious distinctions between the maps affirms that the permafrost distribution on this map is more realistic than on the Zou et al. (2017) map. Due to the excellent accuracy demonstrated, this map can serve as a benchmark map of sufficient quality to constrain/validate land surface models and as a historical reference when projecting future permafrost changes on the QTP in the context of global warming.

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“…

The evolution of lakes is essential for a better understanding of regional climate change and anthropogenic factors (Vorosmarty et al, 2000;Subin et al, 2012;Tao et al, 2015). Additionally, lakes are considered important sources of greenhouse gases in the atmosphere (Wang et al, 2021). The Qinghai-Tibet Plateau (QTP), designated by scholars as the Third Pole (Qiu, 2008;Zhang et al, 2019;Zheng et al, 2021), has a large number of lakes widely spread over it.

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confidence: 99%

Spatiotemporal variations and overflow risk analysis of the Salt Lake in the Hoh Xil Region using machine learning methods

Wang

Guo²,

Chen³

et al. 2023

Front. Earth Sci.

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Global warming is inducing dramatic changes in fluvial geomorphology and reshaping the hydrological connections between rivers and lakes. The water level and area of the Salt Lake have increased rapidly since the outburst of the Zonag Lake in the Hoh Xil region of the Qinghai–Tibet Plateau in 2011, threatening the downstream infrastructure. However, fewer studies have focused on its spatiotemporal variation and overflow risk over long time series. Here, we used three machine learning algorithms: Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) to extract the area of the Salt Lake for a long time series, analyzed its spatiotemporal variation from 1973 to 2021, and finally assessed the overflow risk. The Kappa coefficient (KAPPA) and the overall accuracy (OA) were used to evaluate the performance of the models. The results showed that Random Forest performs superior in lake extraction (KAPPA = 0.98, overall accuracy = 0.99), followed by Classification and Regression Trees and Support Vector Machine. normalized difference water index is the relatively important feature variable in both RF and CART. Before the outburst event, the area change of the Salt Lake was consistent with the variation in precipitation; after that, it showed a remarkable area increase (circa 350%) in all orientations, and the main direction was the southeast. Without the construction of the emergency drainage channel, the simulation result indicated that the earliest and latest times of the Salt Lake overflow event are predicted to occur in 2020 and 2031, respectively. The results of this paper not only demonstrate that RF is more suitable for water extraction and help understand the water system reorganization event.

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High methane emissions from thermokarst lakes on the Tibetan Plateau are largely attributed to ebullition fluxes

Cited by 35 publications

References 105 publications

Sentinel‐Based Inventory of Thermokarst Lakes and Ponds Across Permafrost Landscapes on the Qinghai‐Tibet Plateau

Sentinel‐Based Inventory of Thermokarst Lakes and Ponds Across Permafrost Landscapes on the Qinghai‐Tibet Plateau

A new 2010 permafrost distribution map over the Qinghai-Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling

Spatiotemporal variations and overflow risk analysis of the Salt Lake in the Hoh Xil Region using machine learning methods

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