Multi-factor identification and modelling analyses for managing large river algal blooms

doi:10.1016/j.envpol.2019.113056

	Multi-factor identification and modelling analyses for managing large river algal blooms
	Xia, Rui 2,3; Zhang, Yuan 2,3; Wang, Gangsheng 4,5,6; Zhang, Yongyong 1; Dou, Ming 7; Hou, Xikang 2,3; Qiao, Yunfeng 7,8; Wang, Qiang 9; Yang, Zhongwen 2,10
刊名	ENVIRONMENTAL POLLUTION
	2019-11-01
卷号	254 页码:11
关键词	Cause analysis Multifactor influence Modelling research River algal bloom Water project
ISSN号	0269-7491
DOI	10.1016/j.envpol.2019.113056
通讯作者	Zhang, Yuan(zhangyuan@craes.org.cn)
英文摘要	River algal blooms have become a newly emerging global environmental issue in recent decades. Compared with water eutrophication in lakes and reservoirs, algal blooms in large river systems can cause more severe consequences to watershed ecosystems at the watershed scale. However, reveal the causes of river algal blooms remains challenging in the interdisciplinary of hydrological-ecological environmental research, due to its complex interaction mechanisms impacted by multiple factors. In addition, there were still considerable uncertainties on the characteristics, impacts, driving factors, as well as the applicable water system models for river algal blooms. In this paper, we reviewed existing literature to elaborate the definition and negative effects of river algal blooms. We analyzed sensitive factors including nutrient, hydrological and climatic elements. We also discussed the application of ecohydrological models under complicated hydrological conditions. Finally, we explored the essence of the river algal bloom by the interaction effects of physical and biogeochemical process impacted by of climate change and human activities. The model-data integration accounting for multi-factor effects was expected to provide scientific guidance for the prevent and control of algal blooms in large river systems. (C) 2019 Elsevier Ltd. All rights reserved.
资助项目	National Natural Science Foundation of China[51879252]
WOS关键词	3 GORGES RESERVOIR ; ARTIFICIAL NEURAL-NETWORK ; LOWER HAN RIVER ; CLIMATE-CHANGE ; FRESH-WATER ; PHYTOPLANKTON COMMUNITY ; CHLOROPHYLL-A ; DANING RIVER ; BLUE-GREEN ; CONTROLLING EUTROPHICATION
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000488887600002
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/129713]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Yuan
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 2.Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China 3.Chinese Res Inst Environm Sci, Lab Aquat Ecol Conservat & Restorat, Beijing 100012, Peoples R China 4.Univ Oklahoma, Inst Environm Genom, Norman, OK 73019 USA 5.Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA 6.Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA 7.Zhengzhou Univ, Coll Water Conservancy & Environm, Zhengzhou 450001, Henan, Peoples R China 8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100012, Peoples R China 9.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, 8 Donghu South Rd, Wuhan 430072, Hubei, Peoples R China 10.Chinese Res Inst Environm Sci, Lab Aquat Ecol Conservat & Restorat, Beijing 100012, Peoples R China
推荐引用方式 GB/T 7714	Xia, Rui,Zhang, Yuan,Wang, Gangsheng,et al. Multi-factor identification and modelling analyses for managing large river algal blooms[J]. ENVIRONMENTAL POLLUTION,2019,254:11.
APA	Xia, Rui.,Zhang, Yuan.,Wang, Gangsheng.,Zhang, Yongyong.,Dou, Ming.,...&Yang, Zhongwen.(2019).Multi-factor identification and modelling analyses for managing large river algal blooms.ENVIRONMENTAL POLLUTION,254,11.
MLA	Xia, Rui,et al."Multi-factor identification and modelling analyses for managing large river algal blooms".ENVIRONMENTAL POLLUTION 254(2019):11.