scholarly journals Effects of salinity and particle size on radium desorption from river sediments in the Qinghai-Tibet Plateau

2022 ◽  
Vol 241 ◽  
pp. 106771
Author(s):  
Weigang Su ◽  
Yujun Ma ◽  
Qiugui Wang ◽  
Qiongxiong Yan ◽  
Xiaohang Lu ◽  
...  
Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2265 ◽  
Author(s):  
Ma ◽  
Zhao ◽  
Yang ◽  
Xiao ◽  
Zhang ◽  
...  

Raindrop size distribution (DSD) can reflect the fundamental microphysics of precipitation and provide an accurate estimation of its amount and characteristics; however, there are few observations and investigations of DSD in cold, mountainous regions. We used the second-generation particle size and velocity disdrometer Parsivel2 to establish a quality control scheme for raindrop spectral data obtained for the Qinghai–Tibet Plateau in 2015. This scheme included the elimination of particles in the lowest two size classes, particles >10 mm in diameter and rain rates <0.01 mm∙h−1. We analyzed the DSD characteristics for different types of precipitation and rain rates in both permafrost regions and regions with seasonally frozen ground. The precipitation in the permafrost regions during the summer were mainly solid with a large particle size and slow fall velocity, whereas the precipitation in the regions with seasonally frozen ground were mainly liquid. The DSD of snow had a broader drop spectrum, the largest particle size, the slowest fall velocity, and the largest number of particles, followed by hail. Rain and sleet shared similar DSD characteristics, with a smaller particle size, slower velocity, and smaller number of particles. The particle concentration for different classes of rain rate decreased with an increase in particle size and decreased gradually with an increase in rain rate. Precipitation with a rain rate >2 mm∙h−1 was the main contributor to the annual precipitation. The dewpoint thresholds for snow and rain in permafrost regions were 0 and 1.5 °C, respectively. The dewpoint range 0–1.5 °C was characterized by mixed precipitation with a large proportion of hail. This study provides valuable DSD information on the Qinghai–Tibet Plateau and can be used as an important reference for the quality control of raindrop spectral data in regions dominated by solid precipitation.


2020 ◽  
Vol 173 ◽  
pp. 115589 ◽  
Author(s):  
Sibo Zhang ◽  
Wei Qin ◽  
Xinghui Xia ◽  
Lingzi Xia ◽  
Siling Li ◽  
...  

2021 ◽  
Vol 13 (7) ◽  
pp. 1392
Author(s):  
Chong Wang ◽  
Lin Zhao ◽  
Hongbing Fang ◽  
Lingxiao Wang ◽  
Zanpin Xing ◽  
...  

Spatial information of particle size fractions (PSFs) is primary for understanding the thermal state of permafrost in the Qinghai-Tibet Plateau (QTP) in response to climate change. However, the limitation of field observations and the tremendous spatial heterogeneity hamper the digital mapping of PSF. This study integrated log-ratio transformation approaches, variable searching methods, and machine learning techniques to map the surficial soil PSF distribution of two typical permafrost regions. Results showed that the Boruta technique identified different covariates but retained those covariates of vegetation and land surface temperature in both regions. Variable selection techniques effectively decreased the data redundancy and improved model performance. In addition, the spatial distribution of soil PSFs generated by four log-ratio models presented similar patterns. Isometric log-ratio random forest (ILR-RF) outperformed the other models in both regions (i.e., R2 ranged between 0.36 to 0.56, RMSE ranged between 0.02 and 0.10). Compared with three legacy datasets, our prediction better captured the spatial pattern of PSFs with higher accuracy. Although this study largely improved the accuracy of spatial distribution of soil PSFs, further endeavors should also be made to improve model accuracy and interpretability for a better understanding of the interaction and processes between environmental predictors and soil PSFs at permafrost regions.


2021 ◽  
Vol 166 ◽  
pp. 104093
Author(s):  
Fei Peng ◽  
Wenjuan Zhang ◽  
Chimin Lai ◽  
Chengyang Li ◽  
Quangang You ◽  
...  

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