A. Sá Marques

Sensitivity analysis of surface runoff generation in urban flood forecasting

Reliable flood forecasting requires hydraulic models capable to estimate pluvial flooding fast enough in order to enable successful operational responses. Increased computational speed can be achieved by using a 1D/1D model, since 2D models are too computationally demanding. Further changes can be made by simplifying 1D network models, removing and by changing some secondary elements. The Urban Water Research Group (UWRG) of Imperial College London developed a tool that automatically analyses, quantifies and generates 1D overland flow network. The overland flow network features (ponds and flow pathways) generated by this methodology are dependent on the number of sewer network manholes and sewer inlets, as some of the overland flow pathways start at manholes (or sewer inlets) locations. Thus, if a simplified version of the sewer network has less manholes (or sewer inlets) than the original one, the overland flow network will be consequently different. This paper compares different overland flow networks generated with different levels of sewer network skeletonisation. Sensitivity analysis is carried out in one catchment area in Coimbra, Portugal, in order to evaluate overland flow network characteristics.

Optimal integrated operation of pipeline systems and water treatment plants

Water supply systems usually include a number of components (treatment plants, pipelines, pumping stations and distribution reservoirs), each of which performs a specific function. The interconnection between components requires the integrated operation of the systems. The operation of these systems is quite expensive because the energy consumption of some components is rather high. Both reasons (interconnection between components and high energy consumption) justify the development of tools to help their integrated operation while rninizing costs. This paper presents a mixed-integer optimization model aimed at minimizing systems operation costs, over a 24-hour period. The model includes constraints related to the physical behaviour of the systems, and takes the variable electricity tariff into account. The model is solved using two different methods: “Branch-and-Bound” (an exact method) and “Simulated Amealing” (a random search method), In order to compare the efficiency and effectiveness of the two methods, the model is applied to a hypothetical example. Even though the model has not yet been tested in practice, authors are convinced that the use of this type of tool could be of great help in the operation of water distribution systems, allowing significant savings in energy costs.