Structurally optimized modeling of non-linear effects of meteorological extreme events on water and solute dynamics

气象极端事件对水和溶质动力学的非线性影响的结构优化建模

• 批准号: 5445169
• 负责人: Professor Dr. Jan Fleckenstein
• 金额: --
• 依托单位: Department Hydrogeologie
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2005
• 资助国家: 德国
• 起止时间: 2004-12-31 至 2011-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5445169?language=en
• 关键词: Structurally; optimized; modeling; non; linear

Groundwater and stream water quality are affected by a multitude of processes that act at different scales and often interact in highly non-linear ways. As a consequence, the effects of anthropogenic impacts and natural variability, e.g. interanual climatic variability and longterm climate change are difficult to differentiate. Often, a few single events are much more decisive for the system's behavior than long-term mean conditions. That renders a sound assessment of the impacts of expected climate change, including changing frequencies and intensities of meteorological extreme events, on water quality difficult The Lehstenbach watershed has been the focus of numerous biogeochemical process studies and extensive monitoring since 1986. The obtained data provide an ideal basis for studying the interplay between different processes, linking upslope soil and groundwater bodies with riparian wetlands and streams. Using non-linear statistics, a methodology has been developed and applied to the data that allows an identification of prevailing processes at the watershed scale. This information shall be used to optimize model structure (processes and data explicitly included in the model) of a physically based, numerical watershed model for water flow, solute transport and turnover that would allow an integration of the findings of single process studies at the watershed scale. The optimized model can be used to study the effect of recent climatic variability on watershed solute turnover, and thus provide a tool for scenario analyses. As such it can help to link the findings of the different working groups of the Forschergruppe into an integral description of total system's water flow and solute transport behavior.

地下水和溪水水质受到多种过程的影响，这些过程在不同的规模上起作用，而且往往以高度非线性的方式相互作用。因此，很难区分人为影响和自然变化的影响，例如年际气候变化和长期气候变化。通常，几个单一事件对系统的行为比长期平均状况更具决定性。这使得对预期气候变化的影响--包括气象极端事件的变化频率和强度--对水质的影响难以得到合理评估。自1986年以来，莱斯滕巴赫流域一直是众多生物地球化学过程研究和广泛监测的重点。所获得的数据为研究不同过程之间的相互作用提供了理想的基础，将上坡土壤和地下水体与河岸湿地和溪流联系起来。利用非线性统计，制定了一种方法，并将其应用于数据，从而能够确定分水岭尺度上的主要过程。这些信息应用于优化以物理为基础的、关于水流、溶质迁移和周转的数值分水岭模型的模型结构(明确包括在模型中的过程和数据)，以便在分水岭尺度上整合单一过程研究的结果。优化后的模型可用于研究近期气候变化对流域溶质周转的影响，从而为情景分析提供工具。因此，它有助于将Forschergruppe不同工作组的调查结果联系起来，形成对整个系统的水流动和溶质迁移行为的完整描述。