基于水生态模型的区域气候变化对浅水库水质的影响机制及不确定性研究

Climate change is an important factor affecting water quality in lakes and reservoirs. The proposing of the research is that data mining discovers underlying rules by statistical model; to calibrate the statistical model, the mechanisms of impacts of climate change on water quality are illustrated by a coupled water quality - macrophytes model..The Yuqiao Reservoir as a case study for the shallow reservoir of water source region, the objectives are the following: (1) to quantify the impacts of different climate indicators on water quality with quantitative assessment method; (2) to analyze the influence mechanisms of climate change on water quality with the coupled water quality - macrophytes model; (3) to predict the regional impacts of climate scenarios uncertainty on water quality in medium-long term..Considering the effects of human activity and climate change on water quality, non-parametric regression is performed to explore potential key climate drivers of water quality using historical climate indicators and water quality parameters datasets in 30 years. Anthropogenic factors are separated from synthetical impacts by extended kalman filter method. The coupled water quality - macrophytes model calibrates the statistical model to illustrate the influence mechanisms. Climate scenarios (RCP8.5, RCP4.5, RCP2.6) in 2020-2030 and 2030-2050 and extreme weather are conducted based on the COordinated Regional climate Downscaling EXperiment (CORDEX)-East Asia climate data..The study will provide theoretic foundation for mechanisms of climate change affect on water quality and will be of great significance for guaranteeing water security in China.

气候变化对湖库水质的影响是目前广泛关注但比较难于解决的问题。本项目的研究思路为“统计模型发掘数据规律，水生态模型验证统计模型从机理上揭示影响机制”。遵循“定量贡献-阐明机制-应对变化”的研究主线，以于桥水库及其流域为例，依据30年的气候要素和水质历史数据，考虑人类活动对水质的影响，利用非参数回归等统计模型定量分析气候变化和人类活动对水质的贡献；基于扩展型卡尔曼滤波法剔除人为因素干扰，通过水动力-水质-水生态模型从机理上模拟验证统计模型，阐明气候变化对水库水质直接和间接影响机制；基于CMIP5多模式的CORDEX降尺度气象数据，形成气候情景不确定性方案组（3+3+1），模拟预测中、远期气候情景和极端气候对水质影响程度，提出保障供水安全的气候变化应对建议。项目为阐明气候变化对湖库水质的影响机制提供理论依据，在制定适应对策和用水安全方面具有重要的科学意义。

全球气候变化造成的影响已引起各国政府和公众的广泛关注，气候变化对水文水资源的影响逐渐成为全球气候变化研究的重要组成部分。本项目以大型浅水湖库为例，研究人类活动和气候变化对浅水湖库水质的影响。项目遵循“定量贡献-阐明机制-应对变化”的研究主线，以“统计模型发掘数据规律，水生态模型验证统计模型从机理上揭示机制”为研究思路，开展了三点研究内容：①气候变化和人类活动对浅水库水质的影响规律和定量贡献研究；②基于水生态模型的气候变化对浅水库水质的影响机制研究；③中远期区域气候情景的不确定性对浅水库水质影响程度预测分析。研究开发了数据同化算法，定量评估气候变化和调水对水质指标的季节性影响规律，如于桥水库例中，自产水、引水、气温、风速对TP浓度的贡献率分别为37%，40%，17%，6%；集成水质-水生态模型揭示湍流对浅水湖泊藻类的能量传递潜在机制，并首次提出大尺度气候和水文情势下河湖系统水质模型缺乏敏感地湖沼过程响应；创建了气候-水文-水动力水质集合模拟框架，阐明了中远期区域气候情景下浅水湖库水质退化机制及缓解措施。在中期和远期RCP4.5和RCP8.5情景下，于桥水库总磷浓度将急剧增加，而调水方案措施将有效缓解水质退化，未来两种情景下50-60%的总磷浓度将低于60 μg l-1。项目研究成果为制定全球气候变化背景下的河湖调控应对措施提供理论支撑，为我国碳减排政策的可行方案提供借鉴参考。