Modelling Pollution transport in Constructed Wetlands

项目重点：-开发能够模拟人工湿地中溶质和微塑料运输过程、营养物去除效率和水力效率的稳健模型。-开发基于机器学习的贝叶斯方法不确定性量化方法，以研究关键建模参数，并反向量化和减少本研究中开发的数值建模工具的不确定性。我们将使用现有的实地数据进行验证和校准过程。-进行情景模拟，研究气候变化、植被组成的季节和年际变化，以及池塘的几何设计对人工湿地的性能和除污效率的影响。概述：人工湿地（CWs）是一种利用土壤、植被和生物来处理水并去除溶质和固体污染的生态工程系统。水-植被-土壤之间的相互作用决定了湿地的物理、化学和生物处理过程。这些“自然资本”资产是处理城市和工业废水、灰水和雨水径流的最有效措施之一。水的运动动力学对污染物的去除起着关键作用，因为它影响着处理污染物的水力停留时间。植物群落对湿地水动力和性能有显著影响，它们产生流动阻力，改变流速场，影响混合特性，使悬浮物落到湿地床上。植被生长和枯死的季节变化影响着系统的性能。此外，随着时间的推移，微生物群落将对作为污水成分的有机和金属污染物作出反应。近年来，一些研究对人工湿地的污染传输机制进行了研究。然而，在模拟影响湿地溶质和固体迁移的物理、生物过程方面，仍然存在重大的知识空白。主要目的是开发一个强大的数值模拟工具，能够准确地模拟人工湿地中的污染运输和储存过程，以量化人工湿地的营养物去除效率和水力效率。这种模型的开发对于这些自然资本资产的优化和有效设计、运营和维护至关重要。模型验证和微调将使用我们与诺福克河信托基金会合作的现有项目中基于现场的示踪剂研究数据进行。本项目亦会研究和量化气候变率、植被组成的季节和年际变化对化粪池性能、混合和分散过程的影响，为化粪池的设计和运作提供参考。因此，该项目将通过模拟和优化人工湿地自然资本资产的性能，为环境保护和综合集水区管理提供一个阶段性的改变，并且在水务行业对这些系统进行大量投资的时候，具有重要的影响。

Project Highlights: - Development of robust model capable of simulating solute and microplastic transport processes, nutrient removal efficiency, and hydraulic efficiency in constructed wetlands. - Development of a machine learning-based Bayesian approach uncertainty quantification methodology to investigate the key modelling parameters, and inversely quantify and reduce the uncertainties of the numerical modelling tool developed within this study. We will use existing field-based data for validation and calibration processes.- Undertaking scenario modelling to Investigate the effects of climate variability, seasonal and interannual variation in vegetation composition, as well as the geometrical design of the pond on the performance of the constructed wetlands and their pollution removal efficiency.Overview: Constructed wetlands (CWs) are ecologically engineered systems that use soil, vegetation, and organisms to treat water and remove solute and solid pollution. It is the interplay between water-vegetation-soil that governs the wetland physical, chemical, and biological treatment processes. These 'Natural Capital' assets are one of the most effective measures to treat municipal and industrial wastewater, greywater, and storm-water runoff. Dynamics of water movement plays a key role in the removal of pollutants, as it influences the hydraulic residence time for treating the pollutants. Plant communities have a prominent effect on the wetland hydrodynamics and performance, as they generate flow resistance, changes the velocity field, and affect mixing characteristics, enabling suspended material to fall to the wetland bed. Seasonal variation in vegetation growth and die-back influences the performance of the system. In addition, the microbial community will respond over time to the organic and metal pollutants that are constituents of the effluents. In recent years, several studies investigated the pollution transport mechanisms in constructed wetlands. However, critical knowledge gaps remain in modelling the physical, biological processes affecting solute and solid transport in wetlands. The main aim is to develop a robust numerical simulation tool capable of accurately modelling pollution transport and storage processes in the constructed wetlands to quantify the nutrient removal efficiency, and the hydraulic efficiency of constructed wetlands. Development of such model is critical for optimal and efficient design, operation, and maintenance of these natural capital assets. The model validation and fine-tunning with be undertaken using field-based tracer study data from our existing project in collaboration with the Norfolk Rivers Trust. This project will also investigate and quantify the effects of climate variability and seasonal and interannual variation in vegetation composition on the performance, mixing and dispersion processes within the CWs to inform the design and operation of CWs. Hence, this project will provide a step change in environmental protection and integrated catchment management by modelling and optimising the performance of constructed wetland natural capital assets, and significantly, be influential at a time of considerable investment in these systems by the water industry.