scholarly journals Lake Morphometry and River Network Controls on Evasion of Terrestrially Sourced Headwater CO 2

Author(s):  
C. B. Brinkerhoff ◽  
P. A. Raymond ◽  
T. Maavara ◽  
Y. Ishitsuka ◽  
K. S. Aho ◽  
...  
2019 ◽  
Author(s):  
Brian Sockness ◽  
◽  
Karen B. Gran ◽  
Cecilia Cullen ◽  
Alison Anders ◽  
...  

2021 ◽  
Vol 121 ◽  
pp. 107188
Author(s):  
Zhengfei Li ◽  
Jani Heino ◽  
Xiao Chen ◽  
Zhenyuan Liu ◽  
Xingliang Meng ◽  
...  

2021 ◽  
Vol 275 ◽  
pp. 116651
Author(s):  
Xinchen He ◽  
Hua Wang ◽  
Wei Zhuang ◽  
Dongfang Liang ◽  
Yanhui Ao

Author(s):  
Alexander Y. Karatayev ◽  
Vadim A. Karatayev ◽  
Lyubov E. Burlakova ◽  
Knut Mehler ◽  
Mark D. Rowe ◽  
...  

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du

Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.


Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1147
Author(s):  
Zhiyuan Zhang ◽  
Yuqing Lin

The confluences of rivers are important nodes for energy conversion and material transport in the river network. A slight morphological alteration of the confluences may trigger the “butterfly effect”, which will bring about changes in the ecology and environment of the entire river network. During the transition period of the wet and dry seasons, the variation of discharge ratio will make the originally balanced river bed change again, which will bring a series of follow-up effects. This research mainly studied the features of water flow itself and results showed that the variation of discharge ratio caused secondary erosion of the balanced bed surface and transported the sediment downstream. Thus, the zone of maximum velocity was enlarged and the maximum flow velocity at the equal discharge was reduced, and more intense vortex and turbulence were generated. The lateral velocity, vertical velocity, and turbulent structure were mainly controlled by the quantity and ratio of the discharge, and the varying topography only played a minor role in local areas. Nowadays, some scholars have been studying the combination of flow field features and various environmental substances and biological habitats, and the basic work done in this article has laid the foundation for these studies.


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