Effects of local factors and climate on permafrost conditions and distribution in Beiluhe basin, Qinghai-Tibet Plateau, China

Yin, Guoan; Niu, Fujun; Lin, Zhijun; Luo, Jing; Liu, Minghao

doi:10.1016/j.scitotenv.2016.12.155

Cited by 97 publications

(77 citation statements)

References 49 publications

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“…Xu et al indicated that the total area of permafrost decreased by 2.48 × 10 5 km 2 on the QTP over the past three decades (1981 to 2010) [30]. Yin et al indicated that the active layer depth around the Beilu River (in the northern part of our study area) increased by at least 42 cm from 2003 to 2016 [13]. This agrees with our findings.…”

Section: Relationships Among Climate Change Permafrost Degradation supporting

confidence: 92%

“…The mean active layer depth-the thickness of the layer of the ground subject to annual thawing and freezing in areas underlain by permafrost-around the Beilu River increased by at least 42 cm from 2003 to 2016 [13]. Between 2002 and 2012, the spring onset of soil thawing at a depth of 50 cm advanced by approximately 20 days within alpine meadows and 18 days within alpine steppes [12].…”

Section: Introductionmentioning

confidence: 98%

“…Some studies have indicated that the permafrost on the QT Plateau has degraded in recent decades [12,13]. The mean active layer depth-the thickness of the layer of the ground subject to annual thawing and freezing in areas underlain by permafrost-around the Beilu River increased by at least 42 cm from 2003 to 2016 [13].…”

Section: Introductionmentioning

confidence: 99%

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Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

2018

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Abstract:The Qinghai-Tibet (QT) Plateau Engineering Corridor is located in the hinterland of the QT Plateau, which is highly sensitive to global climate change. Climate change causes permafrost degradation, which subsequently affects vegetation growth. This study focused on the vegetation dynamics and their relationships with climate change and human activities in the region surrounding the QT Plateau Engineering Corridor. The vegetation changes were inferred by applying trend analysis, the Mann-Kendall trend test and abrupt change analysis. Six key regions, each containing 40 nested quadrats that ranged in size from 500 × 500 m to 20 × 20 km, were selected to determine the spatial scales of the impacts from different factors. Cumulative growing season integrated enhanced vegetation index (CGSIEVI) values were calculated for each of the nested quadrats of different sizes to indicate the overall vegetation state over the entire year at different spatial scales. The impacts from human activities, a sudden increase in precipitation and permafrost degradation were quantified at different spatial scales using the CGSIEVI values and meteorological data based on the double mass curve method. Three conclusions were derived. First, the vegetation displayed a significant increasing trend over 23.6% of the study area. The areas displaying increases were mainly distributed in the Hoh Xil. Of the area where the vegetation displayed a significant decreasing trend, 72.4% was made up of alpine meadows. Second, more vegetation, especially the alpine meadows, has begun to degenerate or experience more rapid degradation since 2007 due to permafrost degradation and overgrazing. Finally, an active layer depth of 3 m to 3.2 m represents a limiting depth for alpine meadows.

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Section: Relationships Among Climate Change Permafrost Degradation supporting

confidence: 92%

Section: Introductionmentioning

confidence: 98%

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Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

2018

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“…Previous studies in the QTP (1) used one or two indices, such as MAAT and MAGST, to evaluate the permafrost changes ; (2) presented a static permafrost distribution that constructed a regression analysis method through the relationship between MAGT and elevation, latitude, and slope-aspects (Nan, 2005;Yin et al, 2017); and (3) weather stations of QTP were introduced, which can approximately resolve the spatial change directions of the permafrost area. The QTEC region is an example of spatial modeling, which classifies land cover and topographic features to determine the input spatial parameters.…”

Section: Advantagesmentioning

confidence: 99%

“…Such an increase can warm the ground through energy exchange at the surface and result in significant permafrost degradation. The distribution and changes of permafrost with climate is necessary for infrastructure development, ecological and environmental assessments, and climate system modeling (Luo et al, 2017;Luo et 15 al., 2012;Zhang et al, 2014).…”

mentioning

confidence: 99%

PIC: Comprehensive R package for permafrost indices computing with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau

Luo

Zhang

et al. 2018

Preprint

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Abstract. An R package permafrost indices computing (PIC) was developed, which integrates meteorological observations, remote sensing data, and field measurements to compute the factors or indices of permafrost and seasonal frozen soil. At present, 16 temperature/depth-related indices are integrated into the R package PIC to estimate the possible change trends of frozen soil in the Qinghai-Tibet Plateau (QTP). These indices include the mean annual air temperature, mean annual ground 15 surface temperature, mean annual ground temperature, seasonal thawing/freezing n factor (nt/nf), thawing/freezing degreedays of air and ground surface (DDTa/DDTs/DDFa/DDFs), temperature at the top of the permafrost, active layer thickness, and maximum seasonal freeze depth. The PIC package supports two computational modes, namely, the stations and region calculation that enables statistical analysis and intuitive visualization on the time series and spatial simulations. Over 10 statistical methods were adopted to evaluate these indices in stations, and a sequential Mann-Kendall trend test and spatial 20 trend method were adopted. Multiple visual manners display the temporal and spatial variabilities on the stations and region.The data sets of 52 weather stations and a central region of QTP were prepared and simulated to evaluate the temporal-spatial change trends of permafrost with the climate. Simulation results show extensive permafrost degradation in QTP, and the temporal-spatial trends of the permafrost conditions in QTP were consistent with those of previous studies. The PIC package Geosci. Model Dev. Discuss., https://doi

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Effects of permafrost degradation on thermokarst lake hydrochemistry in the Qinghai‐Tibet Plateau, China

Gao

Niu

Lin

2020

Hydrological Processes

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Thermokarst lakes play a key role in the hydrological and biogeochemical cycles of permafrost regions. Current knowledge regarding the changes caused by permafrost degradation to the hydrochemistry of lakes in the Qinghai-Tibet Plateau (QTP) is limited. To address this gap, a systematic investigation of thermokarst lake water, suprapermafrost water, ground ice, and precipitation was conducted in the hinterland

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Effects of local factors and climate on permafrost conditions and distribution in Beiluhe basin, Qinghai-Tibet Plateau, China

Cited by 97 publications

References 49 publications

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

Vegetation Changes along the Qinghai-Tibet Plateau Engineering Corridor Since 2000 Induced by Climate Change and Human Activities

PIC: Comprehensive R package for permafrost indices computing with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau

Effects of permafrost degradation on thermokarst lake hydrochemistry in the Qinghai‐Tibet Plateau, China

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