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A Parametric Modeling Study of the Climate Change Impact on River Eutrophication and Water Quality ud

机译:气候变化对河流富营养化和水质影响的参数建模研究

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摘要

The potential impact of climate change on river eutrophication and ecosystems are emerging problems that are of great concern to international and domestic societies. Scientific research and developing methods to address these problems are challenging. This study aims 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 involving indicators of climate changes, 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. ududThe developed modeling method has been applied to the Wuhan section of Han River, which is one of major freshwater sources in China. The predicted probability of algal bloom occurrence for the next 40 years by the method is used to identify the impacts of climate change and human activities on the formation mechanisms of river algal blooms under three scenarios. The principles of possible adaptation options are discussed in this thesis.ududThe modeling results indicate the temperature is one of the direct factors contributing to river eutrophication and the change of river water quality. It has also been recognized that the climate change, which can alter water temperature and hydrological regimes, in conjunction with human activities can significantly influence water quality and the river ecosystem. The present study is expected to give theoretical supports and directions for further relevant research.ud
机译:气候变化对河流富营养化和生态系统的潜在影响是国际社会和国内社会极为关注的新出现问题。解决这些问题的科学研究和开发方法具有挑战性。本研究旨在通过利用参数化河流富营养化模型来分析气候变化对大型河流系统中的藻华问题的影响,该模型建立了涉及气候变化,水文状况,水质和养分含量指标的参数。具体而言,开发的参数建模方法基于统计和仿真方法,包括:多个线性回归(MLR),多个非线性回归(MNR),基于反向传播(BP)算法的人工神经网络(ANN)作为河流富营养化综合模型。 ud ud开发的建模方法已应用于汉江武汉断面,这是中国的主要淡水源之一。通过该方法对未来40年藻华发生的预测概率被用于识别三种情况下气候变化和人类活动对河藻华形成机制的影响。本文讨论了可能的适应方案。 ud ud模拟结果表明,温度是导致河流富营养化和河流水质变化的直接因素之一。人们还认识到,气候变化会改变水温和水文状况,并伴随人类活动,会大大影响水质和河流生态系统。本研究有望为进一步的相关研究提供理论支持和指导。 ud

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    Xia Rui;

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  • 年度 2011
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