Evidence map›Paper›PMID 34110515›Full record

ArticleEnvironmental monitoring and assessment2021

Interannual variation in riparian vegetation cover and its relationship with river flow under a high level of human intervention: an example from the Yongding River Basin.

Liangsuo Ren, Shurong Zhang, Xulin Guo, Lirong Cheng, Yujing Guo, Aizhong Ding

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Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Liangsuo RenCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China.ORCID http://orcid.org/0000-0003-1133-1238
Shurong ZhangCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China.
Xulin GuoDepartment of Geography and Planning, University of Saskatchewan, Saskatoon, SK, S7N 5C8, Canada.
Lirong ChengCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China.
Yujing GuoCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China.
Aizhong DingCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China. ading@bnu.edu.cn.

Funding

Natural Science Foundation of Beijing Municipality Z170004the National Key R&D Program of China 2018YFC1800905the National Natural Science Foundation of China 41672227
6 · The paper itself

Abstract

Riparian vegetation cover is significantly affected by a river's hydrological conditions. Especially in arid and semiarid areas, low flow will degrade riparian vegetation, and recent, intensive human activities in the Yongding River Basin have caused a sharp decrease in river flow. We analyzed interannual change in riparian vegetation, river flow effects, and land use on vegetation coverage using the 40 years (1977-2016) of remote sensing images and river flow, combined with 38 years (1980-2018) of land use data. The normalized difference vegetation index (NDVI) was used to determine vegetation cover in five different categories: extremely low, low, medium, high, and extremely high based on the pixel dichotomy model. The weighted average was calculated to obtain vegetation cover trends. We show that riparian vegetation cover from four rivers increased. Compared with 1977, in 2016, combined high and extremely high vegetation covers at the Dongyang, Yang, Sanggan, and Yongding Rivers increased by 20.3%, 26.7%, 50.0%, and 39.2%, respectively. High (R =  -0.976, P < 0.01) and extremely high (R =  -0.762, P < 0.05) vegetation covers are negatively correlated with flow in the Yongding River. The high vegetation cover of the Sanggan River riparian zone is negatively correlated with river flow (R =  -0.683, P < 0.05). In the Dongyang and Sanggan Rivers, land use analysis in the riparian zone showed that change in cultivated land, grassland, and forest were significantly correlated with high and extremely high vegetation cover. The abundant cultivated land and restoration activities are likely responsible for the increase of riparian vegetation cover as river flows decline.

Indexed as

EcosystemRiversEnvironmental MonitoringHumansHydrologyLand useNDVIPixel dichotomy modelRemote sensingRiparian zone

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