Remote sensing spatiotemporal patterns of frozen soil and the environmental controls over the Tibetan Plateau during 2002–2016

Zheng, Guilang; Yang, Yuting; Yang, Dawen; Dafflon, Baptiste; Yi, Yujun; Zhang, Shulei; Chen, Deliang; Gao, Bing; Wang, Taihua; Shi, Runhe; Wu, Qingbai

doi:10.1016/j.rse.2020.111927

Cited by 54 publications

(29 citation statements)

References 74 publications

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“…In a recent study, Zheng et al (2019b) used a maximum entropy production-based parameterization of surface energy balance to replace the originally turbulent theory-based scheme in GBEHM to make it fully driven by satellite data and capable of capturing the waterheat coupled processes within soil layers. The model was applied to simulate the frozen soil distribution and recent changes across the entire Tibetan Plateau (Zheng et al, 2020). The satellite-based model simulations showed overall higher accuracy, comparing with previous Tibetan Plateau permafrost maps generated using ground-based measurements (Figure 3, adapted from Zheng et al, 2020).…”

Section: Integrate Remote Sensing Data With Process-based Models To Imentioning

confidence: 97%

“…The model was applied to simulate the frozen soil distribution and recent changes across the entire Tibetan Plateau (Zheng et al, 2020). The satellite-based model simulations showed overall higher accuracy, comparing with previous Tibetan Plateau permafrost maps generated using ground-based measurements (Figure 3, adapted from Zheng et al, 2020). In addition to the physics-based scheme, machine learning and artificial intelligence have also obtained reliable performance in solving the surface energy budget (Adnan et al, 2017;Zhao et al, 2019) as well as in regional permafrost mapping (Pastick et al, 2015;Aalto et al, 2018).…”

Section: Integrate Remote Sensing Data With Process-based Models To Imentioning

confidence: 98%

“…Snow cover plays an important role in determining how soil responds to surface warming due to its strong insulation effects and impact on surface energy balance associated with changes in surface albedo and snow water phase change (Zhang, 2005). Different from the overall thicker snow cover in the northern high latitude region, snow in the Tibetan Plateau often melts quickly due to strong solar radiation, and snow cover is generally shallow and ephemeral, with overall low albedo of fresh snow and limited insulation effects (Wang et al, 2020;Zheng et al, 2020). Therefore, snow cover in the Tibetan Plateau may have a cooling effect on underlying soil temperature due to the dissipated latent heat resulted from frequent snow melting or sublimation (Zhu et al, 2017).…”

Section: Environmental Controls On Tibetan Plateau Permafrost Distribmentioning

confidence: 99%

“…The permafrost classification is based on the international permafrost association permafrost map (Brown et al, 1997), and the "high" and "low" in the legend refer to the ice content of permafrost. Green dots represent meteorological stations from China Meteorological Administration, black triangles refer to the borehole sites with deeper soil temperature measurements from previous studies (Wu and Zhang, 2008;Luo et al, 2012;Cao et al, 2019), and red dots are regular observation sites with soil temperature observations within a depth of a few meters (data source including Yang et al, 2013a;Cao et al, 2019;Zheng et al, 2020). temperatures at 10 m depth have increased by ∼0.14°C during the same period (Wu et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…The limited number of in-situ sites poses great challenges for a comprehensive, regional-scale assessment of the Tibetan Plateau permafrost thermal state. For example, there are large discrepancies among the current Tibetan Plateau permafrost coverage maps (Zou et al, 2017;Wu et al, 2018;Zheng et al, 2020), and it is difficult to accurately evaluate these maps due to the different compilation approaches and insufficient in-situ observations (Cao et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Progress and Challenges in Studying Regional Permafrost in the Tibetan Plateau Using Satellite Remote Sensing and Models

Jiang

Zheng

et al. 2020

Front. Earth Sci.

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Recent climate change has induced widespread soil thawing and permafrost degradation in the Tibetan Plateau. Significant advances have been made in better characterizing Tibetan Plateau soil freeze/thaw dynamics, and their interaction with local-scale ecohydrological processes. However, factors such as sparse networks of in-situ sites and short observational period still limit our understanding of the Tibetan Plateau permafrost. Satellite-based optical and infrared remote sensing can provide information on land surface conditions at high spatial resolution, allowing for better representation of spatial heterogeneity in the Tibetan Plateau and further infer the related permafrost states. Being able to operate at “all-weather” conditions, microwave remote sensing has been widely used to retrieve surface soil moisture, freeze/thaw state, and surface deformation, that are critical to understand the Tibetan Plateau permafrost state and changes. However, coarse resolution (>10 km) of current passive microwave sensors can add large uncertainties to the above retrievals in the Tibetan Plateau area with high topographic relief. In addition, current microwave remote sensing methods are limited to detections in the upper soil layer within a few centimetres. On the other hand, algorithms that can link surface properties and soil freeze/thaw indices to permafrost properties at regional scale still need improvements. For example, most methods using InSAR (interferometric synthetic aperture radar) derived surface deformation to estimate active layer thickness either ignore the effects of vertical variability of soil water content and soil properties, or use site-specific soil moisture profiles. This can introduce non-negligible errors when upscaled to the broader Tibetan Plateau area. Integrating satellite remote sensing retrievals with process models will allow for more accurate representation of Tibetan Plateau permafrost conditions. However, such applications are still limiting due to a number of factors, including large uncertainties in current satellite products in the Tibetan Plateau area, and mismatch between model input data needs and information provided by current satellite sensors. Novel approaches to combine diverse datasets with models through model initialization, parameterization and data assimilation are needed to address the above challenges. Finally, we call for expansion of local-scale observational network, to obtain more information on deep soil temperature and moisture, soil organic carbon content, and ground ice content.

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Section: Integrate Remote Sensing Data With Process-based Models To Imentioning

confidence: 97%

Section: Integrate Remote Sensing Data With Process-based Models To Imentioning

confidence: 98%

Section: Environmental Controls On Tibetan Plateau Permafrost Distribmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Progress and Challenges in Studying Regional Permafrost in the Tibetan Plateau Using Satellite Remote Sensing and Models

Jiang

Zheng

et al. 2020

Front. Earth Sci.

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Stable isotopes and remote sensing techniques reveal changes in water surplus and loss in alpine inland river basins

Wang

Cao

et al. 2023

Hydrological Processes

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Although the hydrological process of the alpine inland river basin has been extensively studied, the changes of water budget in the alpine inland river basin are still less revealed. Here, a new method combining stable isotopes and remote sensing technology is used to reveal the changes of water surplus and loss in the alpine inland river basin, and accurately identify the water storage areas (water production zone) and water evaporation areas (water consuming zone) during the hydrological changes of basin, providing new insights for the optimal management of water resources of basin. The results showed the monthly water volume showed a surplus state from May to September 2018 to 2019 in the Shaliu River basin. However, there was a serious water loss in the basin from July to September 2020. This is due to the low precipitation, strong evaporation, and high runoff during this period. In response to such significant changes of hydrological processes, the results indicated that there was significant spatial heterogeneity in the variation of water surplus and loss. Based on the hydrological change, we found that the eastern part of basin was water‐producing zone and the southern part of basin was water‐consuming zone. In addition, the upper reaches of the basin were mainly dominated by water storage. This indicated that the upper part of basin was an important water‐conserving area. The results can provide data support for the effective management and planning of water resources in alpine inland river basins.

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Impacts of frozen ground degradation and vegetation greening on upper Brahmaputra runoff during 1981–2019

Wang

Bibi

Zhou

et al. 2023

Intl Journal of Climatology

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The Tibetan Plateau (TP) contains the largest permafrost region in the mid–low latitudes and the largest area of glaciers outside of the polar regions. In recent decades, this region has experienced vegetation greening (e.g., increasing leaf area index) due to climate change. As the largest exorheic river on the TP, the Upper Brahmaputra Basin (UBB) is very sensitive to climate change, experiencing the humidifying and significant warming. In this study, we investigated the spatiotemporal variability of frozen ground and vegetation over the last four decades in the UBB and explored how these changes have impacted river runoff using a water‐ and energy‐budget distributed hydrological model (WEB‐DHM). We found that almost 50% of permafrost transformed into seasonally frozen or unfrozen ground from 1981 to 2019 with the great improvement of vegetation leaf area index (LAI). Based on the variable‐controlling approach (set the air temperature or vegetation unchanged), we revealed that frozen ground degradation caused an average of 9.3 billion m3 of water loss per year, accounting for 5.4% of total UBB river runoff, even if frozen ground degradation can increase water resources at the early stage. However, vegetation greening has caused a runoff decline by 10.9 billion m3 (6.4%) annually due to enhanced evapotranspiration. These findings highlight that it is critical to understand and mitigate the impacts of changing frozen ground and vegetation, when managing water resources availability and ecosystem conservation under rapid climate change.

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Remote sensing spatiotemporal patterns of frozen soil and the environmental controls over the Tibetan Plateau during 2002–2016

Cited by 54 publications

References 74 publications

Progress and Challenges in Studying Regional Permafrost in the Tibetan Plateau Using Satellite Remote Sensing and Models

Progress and Challenges in Studying Regional Permafrost in the Tibetan Plateau Using Satellite Remote Sensing and Models

Stable isotopes and remote sensing techniques reveal changes in water surplus and loss in alpine inland river basins

Impacts of frozen ground degradation and vegetation greening on upper Brahmaputra runoff during 1981–2019

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