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气候变化对汉江水华影响评价的参数模型分析方法及其应用研究(英文)
引用本文:夏瑞,陈志,周云.气候变化对汉江水华影响评价的参数模型分析方法及其应用研究(英文)[J].资源与生态学报(英文版),2012(3):209-219.
作者姓名:夏瑞  陈志  周云
作者单位:[1]中国环境科学研究院,北京100012 [2]康考迪亚大学工程与计算机学院,加拿大魁北克蒙特利尔1455de Maisonneuve Blvd.
基金项目:supported by the Commonweal Project (200801001) of Ministry of Water Resources, People’s Republic of China
摘    要:气候变化对河流和湖泊水环境的影响是当前国际国内关注的热点问题和学科前沿问题之一。但是由于其复杂性和不确定性,目前对该问题的科学研究和成果仍然十分有限。本文针对水质污染中的富营养化问题,以中国南水北调中线工程调水区的汉江流域为例,开发和应用了多元线性回归、多元非线性回归、人工神经网络及河流富营养化模型等多种评价方法,建立了与气象要素、水文要素、营养盐负荷相联系的多输入单输出富营养化系统参数模型,深入分析了在人类活动和经济发展所产生的影响以外,气候变化在此基础上对水体富营养化的增益作用。最后本文通过单因子和多因子分析法,甄别出不同情景下各要素对汉江水华的影响。通过计算得出,当其中某一项要素变化而其他两项不变时,其导致河流富营养化的贡献度依次为:污染负荷(14.82%)、水文要素(5.56%)、气象要素(3.7%);当污染负荷和水文要素同时变化时对水华的贡献度最大(20.37%),其次是当污染负荷和气象要素同时变化其贡献度为(15.82%),最后为水文要素和气象要素同时变化时的贡献度为(11.11%)。研究结果表明,对于中国这样的发展中国家来说,当控源和治污不能在短时间内达到良好的效果的时候,气候因素会增加水污染的风险性。即使水体内部污染源稳定,气候变化依然会通过改变水温和水文情势进而影响水体富营养化程度。最后本文通过多种方法比较,根据预测和评估得出的结果制定相应的防治对策,从而对今后的相关研究可起澄清概念和指明方向的作用。

关 键 词:气候变化影响  富营养化  水华  参数模型  汉江  中国

Impact Assessment of Climate Change on Algal Blooms by a Parametric Modeling Study in Han River
XlA Rui,CHEN Zhi. and ZHOU Yun.Impact Assessment of Climate Change on Algal Blooms by a Parametric Modeling Study in Han River[J].Journal of Resources and Ecology,2012(3):209-219.
Authors:XlA Rui  CHEN Zhi and ZHOU Yun
Institution:1 Chinese Research Academy of Environmental Sciences (CRAES), Beijing 100012, China; 2 Department of Building, Civil & Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd., West Montreal, Quebec, Canada
Abstract:The potential impact of climate change on international and domestic concern. This study aims water eutrophication and ecosystems is of great to analyze the impact of climate change on algal bloom problems in large river systems by utilizing a parametric river eutrophication model that is established using indicators of climate change, hydrological regimes, water quality and nutrient loads. Specifically, the developed parametric modeling method is based on statistical and simulation methods including: Multiple Linear Regressions (MLR), Multiple Non-linear Regressions (MNR), Artificial Neural Network (ANN) based on Back-propagation (BP) algorithms, as well as an integrated river eutrophication model. The developed model was applied to Han River, which is one of the major sources of fresh water in Wuhan City, China. The impacts of climate change and human activities on the occurrence mechanisms of algal blooms in the Hart River were identified by scenarios analysis. The individual assessment result indicates that the waste nutrient P load has the most significant impact (14.82%), followed by the flow rate (5.56%) and then by temperature (3.7%). For the integrated climate change assessment, it has been found that there is a significant impact (20.37%) when waste load increases and flow rate decreases at the same time. This is followed by increases but flow rate decreases, increase of both waste load and the impact is predicted to be 11 temperature (15.82%). If temperature 11%. The final results point to human activities as a significant influence on water quality and the Han River ecosystem, temperature is also one of the main factors which directly contribute to algal blooms in Han River. The results in present study are expected to give theoretical supports for further relevant research on water eutrophication.
Keywords:climate change impact  eutrophication  algal blooms  parametric models  Han River  China
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