Coupled groundwater hydrodynamic and pollution transport modelling using Cellular Automata approach

High urbanization puts many groundwater resources at risk of quality deterioration. Analyzing all viable potential groundwater contamination scenarios for good decision making requires reliable tool. Coupling several complex models in integrated modelling can often fail to perform in reasonable time. Possible solution in that case could be usage of simplified models in order to speed up long-term continuous calculations and simulations. The paper presents the application of the Cellular Automata (CA) approach in modelling of the contaminant transport under unsteady groundwater conditions. It compares the results obtained using coupled CA models with well-known analytical solutions and standard methods used for pollution transport modelling in groundwater conditions, such as coupled MODFLOW and MT3DMS. Results obtained in this paper show that CA approach can be satisfactorily used for simulations of unsteady groundwater conditions, caused by surface-groundwater interaction, and pollution transport, especially in diffusion dominant cases, gaining the reduction of simulation time up to 10 times

Random Finite Set Based Data Assimilation for Dynamic Data Driven Simulation of Maritime Pirate Activity

Maritime piracy is posing a genuine threat to maritime transport. The main purpose of simulation is to predict the behaviors of many actual systems, and it has been successfully applied in many fields. But the application of simulation in the maritime domain is still scarce. The rapid development of network and measurement technologies brings about higher accuracy and better availability of online measurements. This makes the simulation paradigm named as dynamic data driven simulation increasingly popular. It can assimilate the online measurements into the running simulation models and ensure much more accurate prediction of the complex systems under study. In this paper, we study how to utilize the online measurements in the agent based simulation of the maritime pirate activity. A new random finite set based data assimilation algorithm is proposed to overcome the limitations of the conventional vectors based data assimilation algorithms. The random finite set based general data model, measurement model, and simulation model are introduced to support the proposed algorithm. The details of the proposed algorithm are presented in the context of agent based simulation of maritime pirate activity. Two groups of experiments are used to practically prove the effectiveness and superiority of the proposed algorithm

Reliable and Resilient Surface Water Management through Rapid Scenario Screening

Surface water flooding causes significant damage, disruption and loss of life in cities, both in the UK and globally. These impacts have historically been managed through application of conventional urban drainage systems designed to meet specified design standards. Conventional strategies have performed well in the past, but are becoming increasingly unfit for purpose due to intensifying hazards caused by several emerging challenges, including climate change, urban growth and aging drainage infrastructure. In response, an extensive range of alternative novel interventions has been developed. These have been successfully applied across many case studies and their performance to meet design standards on specific sites is now well understood. However, application is still limited and challenges exist regarding how to maximise performance at the urban catchment scale and incorporate resilience to extreme rainfall events within design. This thesis addresses these challenges through evaluating intervention performance using a rapid scenario screening framework. This framework delivers insight into the complex permutations of intervention strategies at a catchment scale through evaluating alternatives, scales, spatial interactions and responses to a range of rainfall events. The study achieves novelty through developing a new modelling methodology which applies cell parameterisation to represent urban drainage systems and interventions using an existing cellular automata model. The framework is applied at a high level to screen intervention performance using easily accessible data and simplified intervention strategies, it is envisaged that this style of analysis is appropriate for initial catchment assessment to evidence and direct future flood management actions. The research finds intervention scale, distribution and placement to be important factors in determining performance within the context of initial catchment screening using theoretical modelling parameters. Although localised interventions provide benefit at a smaller scale, catchment based strategies are required to substantially reduce estimated annual damage costs across urban areas. The most effective intervention was consistently found to be extensive application of decentralised rainfall capture, which reduced expected annual damage in a UK case study by up to 76%. Intervention distribution and placement are also demonstrated to significantly influence cost effectiveness of strategies, with a wide range of ratios predicted, ranging from £0.10 to £26.0 saved per £1 spent. The most cost effective interventions across the case studies investigated were found to be high volume local drainage interventions targeted in areas of intense flooding. Results demonstrate significant variation in strategy performance depending on rainfall intensity and duration. Analysis across events ranging from 2 to 1000 year return periods found many interventions which performed well during design standard events demonstrate substantial decreases in effectiveness during higher magnitude rainfall. Of particular note are interventions with finite storage capacities, which exhibit considerable decreases in performance at certain threshold levels. The implications of this finding are that designing interventions with resilient performance requires simulation of many rainfall scenarios, and that interventions with resilient properties, such as green infrastructure, do not necessarily achieve resilient performance. The research also identifies that rapid screening frameworks contribute an adaptable and useful tool for stakeholder engagement, intervention design and scenario exploration. Case study application of the framework alongside catchment stakeholders in Melbourne, Australia, facilitated an efficient and collaborative design screening process which benefitted from enhanced communication across a wide range of expertise. The simplified development of intervention strategies provided a clear communication tool which supported the multi-disciplinary investigations required for urban planning in a complex environment. Analysis of many strategy permutations highlighted the advantage of multiple smaller intervention strategies accumulating towards catchment scale benefits, a possibility which is advantaged through stakeholder communication tools, such as this framework. Overall, this thesis demonstrates that reliable and resilient surface water management can be achieved through decentralised catchment scale implementation of interventions, complemented by targeted and cost effective high volume measures. Complexity and variation of outcomes across a range of scenarios indicates the importance of encapsulating the complex permutations of options when evaluating interventions and provides justification for future application of rapid scenario screening frameworks.Engineering and Physical Sciences Research Council (EPSRC