Hydrothermal processes of near-surface warm permafrost in response to strong precipitation events in the Headwater Area of the Yellow River, Tibetan Plateau

Geoderma ◽  
2020 ◽  
Vol 376 ◽  
pp. 114531 ◽  
Author(s):  
Dongliang Luo ◽  
Huijun Jin ◽  
Victor F. Bense ◽  
Xiaoying Jin ◽  
Xiaoying Li
Quaternary ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 14
Author(s):  
Zhengchen Li ◽  
Xianyan Wang ◽  
Jef Vandenberghe ◽  
Huayu Lu

The Wufo Basin at the margin of the northeastern Tibet Plateau connects the upstream reaches of the Yellow River with the lowland catchment downstream, and the fluvial terrace sequence in this basin provides crucial clues to understand the evolution history of the Yellow River drainage system in relation to the uplift and outgrowth of the Tibetan Plateau. Using field survey and analysis of Digital Elevation Model/Google Earth imagery, we found at least eight Yellow River terraces in this area. The overlying loess of the highest terrace was dated at 1.2 Ma based on paleomagnetic stratigraphy (two normal and two reversal polarities) and the loess-paleosol sequence (12 loess-paleosol cycles). This terrace shows the connections of drainage parts in and outside the Tibetan Plateau through its NE margin. In addition, we review the previously published data on the Yellow River terraces and ancient large lakes in the basins. Based on our new data and previous researches, we conclude that the modern Yellow River, with headwaters in the Tibet Plateau and debouching in the Bohai Sea, should date from at least 1.2 Ma. Ancient large lakes (such as the Hetao and Sanmen Lakes) developed as exorheic systems and flowed through the modern Yellow River at that time.


2022 ◽  
Vol 9 ◽  
Author(s):  
Huilong Lin ◽  
Yuting Zhao

The source park of the Yellow River (SPYR), as a vital ecological shelter on the Qinghai-Tibetan Plateau, is suffering different degrees of degradation and desertification, resulting in soil erosion in recent decades. Therefore, studying the mechanism, influencing factors and current situation of soil erosion in the alpine grassland ecosystems of the SPYR are significant for protecting the ecological and productive functions. Based on the 137Cs element tracing technique and machine learning algorithms, five strategic variable selection algorithms based on machine learning algorithms are used to identify the minimal optimal set and analyze the main factors that influence soil erosion in the SPYR. The optimal model for estimating soil erosion in the SPYR is obtained by comparisons model outputs between the RUSLE and machine learning algorithms combined with variable selection models. We identify the spatial distribution pattern of soil erosion in the study area by the optimal model. The results indicated that: (1) A comprehensive set of variables is more objective than the RUSLE model. In terms of verification accuracy, the simulated annealing -Cubist model (R = 0.67, RMSD = 1,368 t km–2⋅a–1) simulation results represents the best while the RUSLE model (R = 0.49, RMSD = 1,769 t⋅km–2⋅a–1) goes on the worst. (2) The soil erosion is more severe in the north than the southeast of the SPYR. The average erosion modulus is 6,460.95 t⋅km–2⋅a–1 and roughly 99% of the survey region has an intensive erosion modulus (5,000–8,000 t⋅km–2⋅a–1). (3) Total erosion loss is relatively 8.45⋅108 t⋅a–1 in the SPYR, which is commonly 12.64 times greater than the allowable soil erosion loss. The economic monetization of SOC loss caused by soil erosion in the entire research area was almost $47.90 billion in 2014. These results will help provide scientific evidences not only for farmers and herdsmen but also for environmental science managers and administrators. In addition, a new ecological policy recommendation was proposed to balance grassland protection and animal husbandry economic production based on the value of soil erosion reclassification.


2020 ◽  
Vol 11 (1) ◽  
pp. 11-21
Author(s):  
Dong-Liang LUO ◽  
Hui-Jun JIN ◽  
He-Qiang DU ◽  
Chao LI ◽  
Qiang MA ◽  
...  

2004 ◽  
Vol 62 (3) ◽  
pp. 310-315 ◽  
Author(s):  
Ke Zhang ◽  
Kaiyu Liu ◽  
Jinchun Yang

Offset fluvial valleys, including rivers beheaded and deflected by strike-slip faults, have long been used to estimate horizontal displacements on the faults. Larger rivers crossing such faults, however, sometimes show either no offset or only a small amount of offset compared to smaller rivers crossing the same faults. The larger rivers with higher erosional rates may widen their valleys asymmetrically downstream of strike-slip faults, rather than being beheaded or deflected. Examples are described from the Yellow River near the NE margin of the Tibetan Plateau. River beheading and asymmetrical widening are two end-members of a fluvial valley's response to strike-slip faulting, whereas deflection is a combination of both. Recognition of the formation of such asymmetrical valleys related to strike-slip faulting will help to understand fault activity better over longer time spans and enable a re-evaluation of many fault histories worldwide.


2020 ◽  
Vol 33 (4) ◽  
pp. 531-538
Author(s):  
Qianyun Ge ◽  
Caixia Gao ◽  
Yuan Cai ◽  
Ting Jiao ◽  
Jinqiang Quan ◽  
...  

Objective: Evidence from previous reports indicates that pig domestication in East Asia mainly occurred in the Mekong region and the middle and downstream regions of the Yangtze River. Further research identified two new origin centers for domestic pigs in the Tibetan Plateau and the islands of Southeast Asia. However, due to the small sample size of Tibetan pigs, details of the origin and spread of Tibetan pigs has not yet been established.Methods: We analyzed mitochondrial DNA control region (D-loop) variation in 1,201 individuals from nine Tibetan pig populations across five provinces. Comprehensive Tibetan pig samples were taken to perform the most detailed analysis of Tibetan pigs to date.Results: The result indicate that Rkaze pigs had the lowest level of diversity, while Changdu pigs had the highest diversity. Interestingly, these two populations were both in the Tibetan Plateau area. If we calculate diversity in terms of each province, the Tibetan Plateau area had the lowest diversity, while the Chinese province of Gansu had the highest diversity. Diversity gradient analysis of major haplotypes suggested three domestication centers of Tibetan pigs in the Tibetan Plateau and the Chinese provinces of Gansu and Yunnan.Conclusion: We found two new domestication centers for Tibetan pigs. One is in the Chinese province of Gansu, which lies in the upstream region of the Yellow River, and the other is in the Chinese province of Yunnan.


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