Evidence map›Paper›PMID 30469345›Full record

ArticleInternational journal of environmental research and public health2018

Water Regime Evolution of Large Seasonal Lakes: Indicators for Characterization and an Application in Poyang Lake, China.

Feng Huang, Bo Yan, Xiao Zhang, Dayong Zhao, Lidan Guo, Yuankun Wang, Ziqiang Xia

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Feng HuangCollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, China. huangfeng1987@hhu.edu.cn.
Bo YanChangjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan 430015, China. byanhhu@163.com.
Xiao ZhangBureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430012, China. zxhhu1991@163.com.
Dayong ZhaoCollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, China. dyzhao@hhu.edu.cn.
Lidan GuoInternational River Research Centre, Hohai University, Nanjing 210098, China. ldguohhu@163.com.
Yuankun WangSchool of Earth Sciences and Engineering, Nanjing University, Nanjing 210093, China. yuankunw@nju.edu.cn.
Ziqiang XiaCollege of Hydrology and Water Resources, Hohai University, Nanjing 210098, China. zqxia@hhu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Impacted by ongoing climate change and anthropogenic activities, large seasonal lakes experience water regime evolution, which raises challenges for the management of water resources and environment. The water regime evolution refers to the spatial and temporal alterations in the hydrological features of lakes. Characterizing the lake water regime and its alteration may help policymakers design effective adaption strategies. Therefore, total 47 hydrological indicators were proposed, considering intra-annual fluctuations, flood and drought features, and rate and frequency of water level variations. Combined with Mann-Kendall algorithm and Sen's slope, the indicators were applied in Poyang Lake, a typically large seasonal lake in China, as a case study. The results revealed temporal and spatial variations in different hydrological indicators. The most dramatic alteration was the water level decline in October and November over the entire study phase, especially over the past 30 years. This was an urgent environmental problem that Poyang Lake faced, partially caused by the increased hydraulic gradient between southern and northern lake. It could trigger the drought occurring earlier, prolong the drought duration, and impair the wetland ecosystem. Environmental water requirements of both Poyang Lake and Yangtze River were suggested for regional sustainable development. The application in Poyang Lake showed the practicability and reliability of the indicators, which are applicable in international seasonal lakes. The series of indicators can be used in whole or in part, determined by the ecohydrological characters of a specific lake and the research objectives.

Indexed as

LakesSeasonsChinaClimate ChangeEcosystemEnvironmental MonitoringFresh WaterHydrologyReproducibility of Resultsenvironmental problemevolutionindicatorsPoyang Lakeseasonal lakesspatio-temporal variationswater regime

Identifiers

PMID30469345
PMCPMC6266152

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.