Oxygen dynamics in large reservoirs: A new framework for understanding the formation of metalimnetic oxygen minima

大型储层中的氧动力学：理解金属金属氧极小值形成的新框架

• 批准号: 410560381
• 负责人: Professor Johannes Barth, Ph.D.
• 金额: --
• 依托单位: Department Seenforschung
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/410560381?language=en
• 关键词: Oxygen; dynamics; large; reservoirs; new

Dissolved oxygen (DO) is a key quantity in water quality management of lakes and reservoirs. It is essential for the ecosystem functioning of these lentic ecosystems. Too low concentrations (anoxia) limit the usability of water for drinking and other purposes. Additional health issues arise from anoxic waters. Last and not least, water treatment becomes expensive. Hence, a healthy and sustainable operation of our freshwater bodies is of prime public interest. Therefore, we propose cooperation between scientists of a leading Chinese and German research institutions involved in water research with a reputation for approaching novel and challenging environmental concerns inside and outside their own countries. Both, numerical simulation tools as well as field experiments & measurements will be operated at the forefront of currently available equipment. From this collaboration, we anticipate a mutual understanding for existing water issues, an intensive exchange about modern field equipment and the implementation of such data in numerical simulations and finally more sensibility of how new knowledge about water issues and reservoir management are put into practice in the other country. Water is a central health issue and the public profits from improved water quality. Oxygen reacts highly sensitive against environmental stressors like organic pollution, eutrophication or climate change. The prediction of its dynamics is a challenging task due to the complex interaction of ecological, biogeochemical, and physical processes. While the dynamics of hypolimnetic DO have been studied intensively and, as a consequence, can be predicted with sufficient accuracy for many purposes, the dynamics of DO in the metalimnion (i.e. the layer between the warm upper epilimnion and the cold, deep hypolimnion) have been understood far less. Metalimnetic oxygen minima (MOM), a phenomenon known from freshwater and marine systems, arise from a combination of high oxygen demand and low vertical exchange. The causal factors of the increased DO demand within the metalimnion are subjected to speculation and involve alternative mechanisms like plankton respiration, imported allochthonous material, turbidity-bound respiration or the breakdown of sedimenting material. The aim of this proposal is the implementation of high-resolution DO-monitoring in German and Chinese Reservoirs (Rappbode Reservoir and Panjiakou Reservoir) together with field and laboratory experiments for testing various hypotheses about the drivers of DO consumption. Results of the field and lab experiments as well as high-resolution monitoring studies are conceptualized by mathematical process descriptions that are embedded in 1D and 3D coupled hydrodynamic-biogeochemical lake models. The developed model tools are provided to the scientific community in model frameworks based on open source codes.

溶解氧（DO）是湖泊水库水质管理中的一个重要指标。这对这些缓慢生态系统的生态系统功能至关重要。浓度太低（缺氧）限制了饮用水和其他用途的可用性。缺氧沃茨会产生其他健康问题。最后也是最重要的一点，水处理变得昂贵。因此，本港淡水水体的健康和可持续运作，是公众的首要利益。因此，我们建议中国和德国在水研究领域的领先研究机构的科学家进行合作，这些研究机构在国内外都以解决新颖和具有挑战性的环境问题而闻名。数值模拟工具以及现场实验和测量都将在现有设备的最前沿进行操作。通过这次合作，我们期待着对现有水资源问题的相互理解，对现代现场设备的深入交流，以及在数值模拟中实施这些数据，最后对如何将有关水资源问题和水库管理的新知识在另一个国家付诸实践更加敏感。水是一个核心的健康问题，公众从改善水质中获益。 氧气对有机污染、富营养化或气候变化等环境压力源高度敏感。由于生态、地球化学和物理过程的复杂相互作用，其动态预测是一项具有挑战性的任务。虽然已经深入研究了深湖溶解氧的动态，并且因此可以对许多目的进行足够准确的预测，但浅湖溶解氧的动态（即温暖的上层水层和寒冷的深层下层水层之间的层）的了解要少得多。金属潜水氧极小值（Metalimnetic oxygen minima，简称O2）是淡水和海洋系统中的一种现象，由高需氧量和低垂直交换的组合引起。的因果因素增加的溶解氧的需求内的metalimunion受到猜测，并涉及替代机制，如浮游生物呼吸，进口外来物质，浊度约束呼吸或沉淀物质的分解。该提案的目的是在德国和中国水库（Rappbode水库和潘家口水库）实施高分辨率DO监测，并进行现场和实验室实验，以测试有关DO消耗驱动因素的各种假设。现场和实验室实验以及高分辨率监测研究的结果是概念化的数学过程描述，嵌入在1D和3D耦合水动力-地球化学湖泊模型。所开发的模型工具以基于开放源代码的模型框架的形式提供给科学界。