A new map of permafrost distribution on the Tibetan Plateau

Abstract. The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06  ×  106 km2 (0.97–1.15  ×  106 km2, 90 % confidence interval) (40 %), 1.46  ×  106 (56 %), and 0.03  ×  106 km2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

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A New Map of the Permafrost Distribution on the Tibetan Plateau

10.5194/tc-2016-187 ◽

2016 ◽

Cited By ~ 10

Author(s):

Defu Zou ◽

Lin Zhao ◽

Yu Sheng ◽

Ji Chen ◽

Guojie Hu ◽

...

Keyword(s):

Tibetan Plateau ◽

Land Surface ◽

Water Resource Management ◽

Climate Modelling ◽

The Tibetan Plateau ◽

Freezing And Thawing ◽

Frozen Ground ◽

Data Set ◽

Distribution Maps ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. The Tibetan Plateau (TP) possesses the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. A detailed database of the distribution and characteristics of permafrost is crucial for engineering planning, water resource management, ecosystem protection, climate modelling, and carbon cycle research. Although some permafrost distribution maps have been compiled in previous studies and have been proven to be very useful, due to the limited data source, ambiguous criteria, little validation, and the deficiency of high-quality spatial datasets, there is high uncertainty in the mapping of the permafrost distribution on the TP. In this paper, a new permafrost map was generated mostly based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated by various ground-based datasets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and in situ observed soil properties (moisture content and bulk density). The Temperature at the Top of Permafrost (TTOP) model was applied to simulate the permafrost distribution. The results show that permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06×106 km2 (40 %), 1.46×106 km2 (56 %), and 0.03×106 km2 (1 %), respectively, excluding glaciers and lakes. The ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) have been used to validate the model. The result of the validation shows that the kappa coefficient varies from 0.38 to 0.78 with an average of 0.57 at the five IRs and 0.62 to 0.74 with an average of 0.68 within the three transects. Compared with two maps compiled in 1996 and 2006 (kappa coefficients in average 0.06 and 0.35 in five IRs, 0.34 and 0.50 within three transects, respectively), the result of the TTOP modelling shows greater accuracy, especially in identifying thawing regions. Overall, the results provide much more detailed maps of the permafrost distribution and could be a promising basic data set for further research on permafrost on the Tibetan Plateau.

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Impact of frozen soil processes on soil thermal characteristics at seasonal to decadal scales over the Tibetan Plateau and North China

Hydrology and Earth System Sciences ◽

10.5194/hess-25-2089-2021 ◽

2021 ◽

Vol 25 (4) ◽

pp. 2089-2107

Author(s):

Qian Li ◽

Yongkang Xue ◽

Ye Liu

Keyword(s):

Tibetan Plateau ◽

Land Surface ◽

North China ◽

Thermal Characteristics ◽

Cold Season ◽

Frozen Soil ◽

The Tibetan Plateau ◽

Soil Processes ◽

Frozen Ground ◽

Freeze Thaw

Abstract. Frozen soil processes are of great importance in controlling surface water and energy balances during the cold season and in cold regions. Over recent decades, considerable frozen soil degradation and surface soil warming have been reported over the Tibetan Plateau and North China, but most land surface models have difficulty in capturing the freeze–thaw cycle, and few validations focus on the effects of frozen soil processes on soil thermal characteristics in these regions. This paper addresses these issues by introducing a physically more realistic and computationally more stable and efficient frozen soil module (FSM) into a land surface model – the third-generation Simplified Simple Biosphere Model (SSiB3-FSM). To overcome the difficulties in achieving stable numerical solutions for frozen soil, a new semi-implicit scheme and a physics-based freezing–thawing scheme were applied to solve the governing equations. The performance of this model as well as the effects of frozen soil process on the soil temperature profile and soil thermal characteristics were investigated over the Tibetan Plateau and North China using observation sites from the China Meteorological Administration and models from 1981 to 2005. Results show that the SSiB3 model with the FSM produces a more realistic soil temperature profile and its seasonal variation than that without FSM during the freezing and thawing periods. The freezing process in soil delays the winter cooling, while the thawing process delays the summer warming. The time lag and amplitude damping of temperature become more pronounced with increasing depth. These processes are well simulated in SSiB3-FSM. The freeze–thaw processes could increase the simulated phase lag days and land memory at different soil depths as well as the soil memory change with the soil thickness. Furthermore, compared with observations, SSiB3-FSM produces a realistic change in maximum frozen soil depth at decadal scales. This study shows that the soil thermal characteristics at seasonal to decadal scales over frozen ground can be greatly improved in SSiB3-FSM, and SSiB3-FSM can be used as an effective model for TP and NC simulation during cold season. Overall, this study could help understand the vertical soil thermal characteristics over the frozen ground and provide an important scientific basis for land–atmosphere interactions.

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Spatial data-sets for geographical referencing

10.3403/00334343 ◽

1994 ◽

Keyword(s):

Spatial Data ◽

Data Sets ◽

Spatial Data Sets

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Spatial data-sets for geographical referencing

10.3403/02124652 ◽

2000 ◽

Keyword(s):

Spatial Data ◽

Data Sets ◽

Spatial Data Sets

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Spatial data-sets for geographical referencing

10.3403/02503338 ◽

2002 ◽

Keyword(s):

Spatial Data ◽

Data Sets ◽

Spatial Data Sets

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An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level

Open Geosciences ◽

10.1515/geo-2020-0159 ◽

2020 ◽

Vol 12 (1) ◽

pp. 580-597

Author(s):

Mohamad Hamzeh ◽

Farid Karimipour

Keyword(s):

Spatial Data ◽

Spatial Models ◽

Model Performance ◽

Essential Elements ◽

Petroleum System ◽

Petroleum Exploration ◽

System Level ◽

Data Sets ◽

Petroleum Potential ◽

Spatial Data Sets

AbstractAn inevitable aspect of modern petroleum exploration is the simultaneous consideration of large, complex, and disparate spatial data sets. In this context, the present article proposes the optimized fuzzy ELECTRE (OFE) approach based on combining the artificial bee colony (ABC) optimization algorithm, fuzzy logic, and an outranking method to assess petroleum potential at the petroleum system level in a spatial framework using experts’ knowledge and the information available in the discovered petroleum accumulations simultaneously. It uses the characteristics of the essential elements of a petroleum system as key criteria. To demonstrate the approach, a case study was conducted on the Red River petroleum system of the Williston Basin. Having completed the assorted preprocessing steps, eight spatial data sets associated with the criteria were integrated using the OFE to produce a map that makes it possible to delineate the areas with the highest petroleum potential and the lowest risk for further exploratory investigations. The success and prediction rate curves were used to measure the performance of the model. Both success and prediction accuracies lie in the range of 80–90%, indicating an excellent model performance. Considering the five-class petroleum potential, the proposed approach outperforms the spatial models used in the previous studies. In addition, comparing the results of the FE and OFE indicated that the optimization of the weights by the ABC algorithm has improved accuracy by approximately 15%, namely, a relatively higher success rate and lower risk in petroleum exploration.

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