scholarly journals Brief Communication: Evaluation and comparisons of permafrost map over Qinghai-Tibet Plateau based on inventory of in-situ evidence

2018 ◽  
Author(s):  
Bin Cao ◽  
Tingjun Zhang ◽  
Qinghai Wu ◽  
Yu Sheng ◽  
Lin Zhao ◽  
...  

Abstract. Many maps have been produced to estimate permafrost distribution over the Qinghai-Tibet Plateau, however, the evaluation and comparisons of them are poorly understood due to limited evidence. Using a large number data from various sources, we present the inventory of permafrost presence/absence with 1475 sites/plots over the QTP. Based on the in-situ measurements, our evaluation results showed a wide range of map performance with the overall accuracy of about 59–82 %, and the estimated permafrost region (1.42–1.84 × 106 km2) and area (0.76–1.25 × 106 km2) are extremely large. The low agreement in areas near permafrost boundary and fragile landscapes require improved method considering more controlling factors at both medium-large and local scales.

2019 ◽  
Vol 13 (2) ◽  
pp. 511-519 ◽  
Author(s):  
Bin Cao ◽  
Tingjun Zhang ◽  
Qingbai Wu ◽  
Yu Sheng ◽  
Lin Zhao ◽  
...  

Abstract. Many maps have been produced to estimate permafrost distribution over the Qinghai–Tibet Plateau (QTP), but the errors and biases among them are poorly understood due to limited field evidence. Here we evaluate and inter-compare the results of six different QTP permafrost maps with a new inventory of permafrost presence or absence comprising 1475 field sites compiled from various sources. Based on the in situ measurements, our evaluation results showed a wide range of map performance, with Cohen's kappa coefficient from 0.21 to 0.58 and an overall accuracy between about 55 % and 83 %. The low agreement in areas near the boundary between permafrost and non-permafrost and in spatially highly variable landscapes highlights the need for improved mapping methods that consider more controlling factors at both medium–large and local scales.


2015 ◽  
Vol 49 (8) ◽  
pp. 4980-4987 ◽  
Author(s):  
Shuo Li ◽  
Zhou Shi ◽  
Songchao Chen ◽  
Wenjun Ji ◽  
Lianqing Zhou ◽  
...  

2019 ◽  
Author(s):  
Edward H. Bair ◽  
Karl Rittger ◽  
Jawairia A. Ahmad ◽  
Doug Chabot

Abstract. Ice and snowmelt feed the Indus and Amu Darya rivers, yet there are limited in situ measurements of these resources. Previous work in the region has shown promise using snow water equivalent (SWE) reconstruction, which requires no in situ measurements, but validation has been a problem until recently when we were provided with daily manual snow depth measurements from Afghanistan, Tajikistan, and Pakistan by the Aga Khan Agency for Habitat (AKAH). For each station, accumulated precipitation and SWE were derived from snow depth using the SNOWPACK model. High-resolution (500 m) reconstructed SWE estimates from the ParBal model were then compared to the modeled SWE at the stations. The Alpine3D model was then used to create spatial estimates at 25 km to compare with estimates from other snow models. Additionally, the coupled SNOWPACK and Alpine3D system has the advantage of simulating snow profiles, which provide stability information. Following previous work, the median number of critical layers and percentage of facets across all of the pixels containing the AKAH stations was computed. For SWE at the point scale, the reconstructed estimates showed a bias of −42 mm (−19 %) at the peak. For the coarser spatial SWE estimates, the various models showed a wide range, with reconstruction being on the lower end. For stratigraphy, a heavily faceted snowpack is observed in both years, but 2018, a dry year, according to most of the models, showed more critical layers that persisted for a longer period.


Geomorphology ◽  
2017 ◽  
Vol 293 ◽  
pp. 1-10 ◽  
Author(s):  
Zhe Sun ◽  
Yibo Wang ◽  
Yan Sun ◽  
Fujun Niu ◽  
GuoyuLi ◽  
...  

Extremophiles ◽  
2007 ◽  
Vol 11 (3) ◽  
pp. 415-424 ◽  
Author(s):  
Gaosen Zhang ◽  
Xiaojun Ma ◽  
Fujun Niu ◽  
Maoxing Dong ◽  
Huyuan Feng ◽  
...  

2018 ◽  
Vol 10 (2) ◽  
pp. 298 ◽  
Author(s):  
Zhengjia Zhang ◽  
Chao Wang ◽  
Hong Zhang ◽  
Yixian Tang ◽  
Xiuguo Liu

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