Assessing the effects of climate change on water quality of plateau deep-water lake - A study case of Hongfeng Lake

被引:52
作者
Longyang, Qianqiu [1 ]
机构
[1] China Univ Geosci, Sch Lisiguang, Wuhan 430074, Hubei, Peoples R China
关键词
Climate change; Artificial neural network model; Deep-water lake; Eutrophication; Non-point pollution; BLUE-GREEN-ALGAE; NEURAL-NETWORKS; LAND-USE; PHOSPHORUS; EUTROPHICATION; MODEL; NITROGEN; SENSITIVITY; PREDICTION; DOMINANCE;
D O I
10.1016/j.scitotenv.2018.08.031
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Climate change-related temperature increases and sea level rise have a significant impact on the atmosphere, hydrosphere, biosphere, and anthroposphere. Impacts on ecosystems will mostly occur over the long term and short-term effects may consequently attract comparatively less attention from researchers and decision-makers. In this study, we investigate eight meteorological factors and eleven water quality indicators of deep-water lakes in the Yunnan-Guizhou Plateau in southwestern China. A robust proxy model based on a seven-year dataset (2010-2016) was established to predict the effects of climate change on water quality in Hongfeng Lake over the coming years. Perturbation analysis revealed that global warming has a more significant effect on chlorophyll a levels than on total phosphorus or total nitrogen in the lake area, and that external nutrient loading is a key factor aggravating eutrophication. Non-point source pollution induced by heavy precipitation will likely lead to an increase in total nitrogen and the lake may become more phosphorus-restricted. Reducing external inputs and controlling endogenous releases will help alleviate eutrophication. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:1518 / 1530
页数:13
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