Qiangqiang Pang

Environmental controls on soil organic carbon and nitrogen stocks in the high-altitude arid western Qinghai-Tibetan Plateau permafrost region

While permafrost in the circum-Artic has great influence on soil organic carbon (SOC) and total nitrogen (TN) stocks, this might not be the case in low-latitude arid permafrost regions. We test this hypothesis in the western Qinghai-Tibetan Plateau (QTP) permafrost region. Fifty-nine soil profiles were analyzed to examine the SOC and TN distribution and the controlling factors in western QTP, which is a desert steppe ecoregion. Mean stocks of SOC (5.29 kg m−2) and TN (0.56 kg m−2) for the top 200 cm in this area were lower than those of the east QTP and circum-Arctic regions. The SOC and TN stocks under vegetative cover with permafrost conditions were significantly higher than those of desert conditions. The SOC and TN stocks for the layers of different depths were related to the content of clay, silt, and moisture. Although the active layer thickness (ALT) had a significant negative correlation to soil moisture, the ALT explained little or no variance in the SOC and TN stocks. The results showed that in the vast permafrost regions of the western QTP, the SOC and TN stocks are very low, and the main controlling factors for the SOC and TN are soil texture, moisture, and vegetation type. The SOC pool in this area may not be as vulnerable to degradation associated with climate warming and thus not emit greenhouse gases at the same rate as other permafrost regions. The different response of the SOC in this region should be considered in carbon cycling models.

Modeling ground surface temperature by means of remote sensing data in high-altitude areas: test in the central Tibetan Plateau with application of moderate-resolution imaging spectroradiometer Terra/Aqua land surface temperature and ground-based infrared radiometer

Abstract Ground surface temperature (GST) is a crucial parameter of surface energy budgets and controls the thermal state of the active layer and permafrost in permafrost regions. However, with limited observed datasets available for the Tibetan Plateau, a greater bias existed for GST products from remote sensing data. Model validation (the whole year 2012 data) showed that all three models performed well, with a determination ( R 2 ), mean error, mean absolute error, and root mean squared error of 0.86 to 0.93, − 0.61 to 1°C, 2.28 to 3.06°C, and 2.96 to 3.83°C, respectively. The model established by observations of Terra and Aqua satellites during the daytime and nighttime showed the highest correlation, with R 2 values ranging from 0.91 to 0.93, as well as the lowest MAE and RMSE of 2.28 to 2.42 and 2.96 to 3.05°C, respectively. However, the application of this model substantially reduced the available pixels. Models established with the automatic weather station observations at the satellite overpass times performed better than those using the moderate-resolution imaging spectroradiometer land surface temperature observations. The results might be useful to produce a more reliable dataset for monitoring and modeling permafrost changes.

Modeling permafrost properties in the Qinghai-Xizang (Tibet) Plateau

Water and heat dynamics in the active layer at a monitoring site in the Tanggula Mountains, located in the permafrost region of the Qinghai-Xizang (Tibet) Plateau (QXP), were studied using the physical-process-based COUPMODEL model, including the interaction between soil temperature and moisture under freeze-thaw cycles. Meteorological, ground temperature and moisture data from different depths within the active layer were used to calibrate and validate the model. The results indicate that the calibrated model satisfactorily simulates the soil temperatures from the top to the bottom of the soil layers as well as the moisture content of the active layer in permafrost regions. The simulated soil heat flux at depths of 0 to 20 cm was consistent with the monitoring data, and the simulations of the radiation balance components were reasonable. Energy consumed for phase change was estimated from the simulated ice content during the freeze/thaw processes from 2007 to 2008. Using this model, the active layer thickness and the energy consumed for phase change were predicted for future climate warming scenarios. The model predicts an increase of the active layer thickness from the current 330 cm to approximately 350–390 cm as a result of a 1–2°C warming. However, the effect active layer thickness of more precipitation is limited when the precipitation is increased by 20%–50%. The COUPMODEL provides a useful tool for predicting and understanding the fate of permafrost in the QXP under a warming climate.

Some Characteristics of Permafrost and Its Distribution in the Gaize Area on the Qinghai—Tibet Plateau, China

ABSTRACT An investigation of permafrost in the Gaize area in the west Qinghai—Tibet Plateau in China was conducted in October and November of 2010 and 2011. It was found that mean annual ground temperature was >-1 °C with a permafrost thickness of <60 m in the widespread alpine steppe below an altitude of 5400 m a.s.l. The active layer thickness was usually deeper than 3 m with a maximum of about 5.7 m. Overall, the ice/water content of the top 15 m of frozen soil was usually <10%. The altitudinal limit of permafrost in the alpine steppe was about 5100, 5000, and 4950 m a.s.l. on south-, east-west-, and north-facing slopes, respectively. A permafrost map was constructed using the ARCGIS platform and topographic information from the TOPO 30 digital elevation model. Statistical analysis of the map revealed that permafrost is primarily distributed in the hilly/mountainous areas of Gaize, covering 51% of the study area. The area of permafrost in this map is considerably less than in the Permafrost Map of the Qinghai—Tibet Plateau drawn in 1996. Further analysis revealed that the large difference between the two maps could be attributed to both errors in the earlier mapping method and permafrost degradation.

Numerical Modeling of the Active Layer Thickness and Permafrost Thermal State Across Qinghai‐Tibetan Plateau

The dynamics of permafrost (including the permafrost thermal state and active layer thicknesses (ALT)) across the Qinghai-Tibetan Plateau (QTP) have not been well understood on a large scale. Here, we simulate the ALT and permafrost thermal state using the Geophysical Institute Permafrost Lab Version 2 (GIPL2) model across the QTP. Based on the single-point simulations, the model is upscaled to the entire QTP. The upscaled model is validated with five investigated regions (IRs), including Wenquan (WQIR), Gaize (GZIR), Aerjin (AEJIR), Xikunlun (XKLIR) and Qinghai-Tibetan highway (G109IR). The results show that the modified GIPL2 model improves the accuracy of the permafrost thermal state simulations. Due to our simulated results on the QTP, the average ALT is of 2.30 m (2.21 - 2.40 m). The ALT decreases with an increase in the altitude and decreases from the southeast to the northwest. The ALT is thin in the central QTP, but it is thick in the high-elevation mountain areas and some areas surrounding glaciers and lakes. The largest ALT is found in the border areas between permafrost and seasonally frozen ground regions. The simulated results of the MAGT (the mean annual ground temperature) indicate that most of the permafrost is sub-stable, which is sensitive to climate warming. The simulated results would be of great significance on assessing the impacts of permafrost dynamics on local hydrology, ecology, and engineering construction.

Modeling Hydrothermal Transfer Processes in Permafrost Regions of Qinghai-Tibet Plateau in China

Hydrothermal processes are key components in permafrost dynamics; these processes are integral to global warming. In this study the coupled heat and mass transfer model for (CoupModel) the soil-plant-atmosphere-system is applied in high-altitude permafrost regions and to model hydrothermal transfer processes in freeze-thaw cycles. Measured meteorological forcing and soil and vegetation properties are used in the CoupModel for the period from January 1, 2009 to December 31, 2012 at the Tanggula observation site in the Qinghai-Tibet Plateau. A 24-h time step is used in the model simulation. The results show that the simulated soil temperature and water content, as well as the frozen depth compare well with the measured data. The coefficient of determination (R2) is 0.97 for the mean soil temperature and 0.73 for the mean soil water content, respectively. The simulated soil heat flux at a depth of 0–20 cm is also consistent with the monitored data. An analysis is performed on the simulated hydrothermal transfer processes from the deep soil layer to the upper one during the freezing and thawing period. At the beginning of the freezing period, the water in the deep soil layer moves upward to the freezing front and releases heat during the freezing process. When the soil layer is completely frozen, there are no vertical water exchanges between the soil layers, and the heat exchange process is controlled by the vertical soil temperature gradient. During the thawing period, the downward heat process becomes more active due to increased incoming shortwave radiation at the ground surface. The melt water is quickly dissolved in the soil, and the soil water movement only changes in the shallow soil layer. Subsequently, the model was used to provide an evaluation of the potential response of the active layer to different scenarios of initial water content and climate warming at the Tanggula site. The results reveal that the soil water content and the organic layer provide protection against active layer deepening in summer, so climate warming will cause the permafrost active layer to become deeper and permafrost degradation.

Soil organic carbon and total nitrogen pools in permafrost zones of the Qinghai-Tibetan Plateau

There are several publications related to the soil organic carbon (SOC) on the Qinghai-Tibetan Plateau (QTP). However, most of these reports were from different parts of the plateau with various sampling depth. Here, we present the results from a systematic sampling and analysis of 200 soil pits. Most of the pits were deeper than 2 m from an east-west transect across the plateau. The SOC and total nitrogen (TN) pools of the 148 × 104 km2, the area of the permafrost zone, for the upper 2 m soils calculated from the vegetation map were estimated to be 17.07 Pg (interquartile range: 11.34–25.33 Pg) and 1.72 Pg (interquartile range: 1.08–2.06 Pg), respectively. We also predicted the distribution of land cover types in 2050 and 2070 using decision tree rules and climate scenarios, and then predicted SOC and TN pools of this region. The results suggested that the SOC and TN pools will decrease in the future. The results not only contribute to the carbon and nitrogen storage and stocks in the permafrost regions as a whole but most importantly, to our knowledge of the possible changes of C and N storage on the QTP in the future.